A Global System for Transportation Simulation and Visualization in Emergency Evacuation Scenarios

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lu, Wei; Liu, Cheng; Thomas, Neil

2015-01-01

Simulation-based studies are frequently used for evacuation planning and decision making processes. Given the transportation systems complexity and data availability, most evacuation simulation models focus on certain geographic areas. With routine improvement of OpenStreetMap road networks and LandScanTM global population distribution data, we present WWEE, a uniform system for world-wide emergency evacuation simulations. WWEE uses unified data structure for simulation inputs. It also integrates a super-node trip distribution model as the default simulation parameter to improve the system computational performance. Two levels of visualization tools are implemented for evacuation performance analysis, including link-based macroscopic visualization and vehicle-based microscopic visualization. Formore » left-hand and right-hand traffic patterns in different countries, the authors propose a mirror technique to experiment with both scenarios without significantly changing traffic simulation models. Ten cities in US, Europe, Middle East, and Asia are modeled for demonstration. With default traffic simulation models for fast and easy-to-use evacuation estimation and visualization, WWEE also retains the capability of interactive operation for users to adopt customized traffic simulation models. For the first time, WWEE provides a unified platform for global evacuation researchers to estimate and visualize their strategies performance of transportation systems under evacuation scenarios.« less

[Medical Image Registration Method Based on a Semantic Model with Directional Visual Words].

PubMed

Jin, Yufei; Ma, Meng; Yang, Xin

2016-04-01

Medical image registration is very challenging due to the various imaging modality,image quality,wide inter-patients variability,and intra-patient variability with disease progressing of medical images,with strict requirement for robustness.Inspired by semantic model,especially the recent tremendous progress in computer vision tasks under bag-of-visual-word framework,we set up a novel semantic model to match medical images.Since most of medical images have poor contrast,small dynamic range,and involving only intensities and so on,the traditional visual word models do not perform very well.To benefit from the advantages from the relative works,we proposed a novel visual word model named directional visual words,which performs better on medical images.Then we applied this model to do medical registration.In our experiment,the critical anatomical structures were first manually specified by experts.Then we adopted the directional visual word,the strategy of spatial pyramid searching from coarse to fine,and the k-means algorithm to help us locating the positions of the key structures accurately.Sequentially,we shall register corresponding images by the areas around these positions.The results of the experiments which were performed on real cardiac images showed that our method could achieve high registration accuracy in some specific areas.

An insect-inspired model for visual binding II: functional analysis and visual attention.

PubMed

Northcutt, Brandon D; Higgins, Charles M

2017-04-01

We have developed a neural network model capable of performing visual binding inspired by neuronal circuitry in the optic glomeruli of flies: a brain area that lies just downstream of the optic lobes where early visual processing is performed. This visual binding model is able to detect objects in dynamic image sequences and bind together their respective characteristic visual features-such as color, motion, and orientation-by taking advantage of their common temporal fluctuations. Visual binding is represented in the form of an inhibitory weight matrix which learns over time which features originate from a given visual object. In the present work, we show that information represented implicitly in this weight matrix can be used to explicitly count the number of objects present in the visual image, to enumerate their specific visual characteristics, and even to create an enhanced image in which one particular object is emphasized over others, thus implementing a simple form of visual attention. Further, we present a detailed analysis which reveals the function and theoretical limitations of the visual binding network and in this context describe a novel network learning rule which is optimized for visual binding.

An evaluation of attention models for use in SLAM

NASA Astrophysics Data System (ADS)

Dodge, Samuel; Karam, Lina

2013-12-01

In this paper we study the application of visual saliency models for the simultaneous localization and mapping (SLAM) problem. We consider visual SLAM, where the location of the camera and a map of the environment can be generated using images from a single moving camera. In visual SLAM, the interest point detector is of key importance. This detector must be invariant to certain image transformations so that features can be matched across di erent frames. Recent work has used a model of human visual attention to detect interest points, however it is unclear as to what is the best attention model for this purpose. To this aim, we compare the performance of interest points from four saliency models (Itti, GBVS, RARE, and AWS) with the performance of four traditional interest point detectors (Harris, Shi-Tomasi, SIFT, and FAST). We evaluate these detectors under several di erent types of image transformation and nd that the Itti saliency model, in general, achieves the best performance in terms of keypoint repeatability.

External and Internal Representations in the Acquisition and Use of Knowledge: Visualization Effects on Mental Model Construction

ERIC Educational Resources Information Center

Schnotz, Wolfgang; Kurschner, Christian

2008-01-01

This article investigates whether different formats of visualizing information result in different mental models constructed in learning from pictures, whether the different mental models lead to different patterns of performance in subsequently presented tasks, and how these visualization effects can be modified by further external…

Processing of Visual Imagery by an Adaptive Model of the Visual System: Its Performance and its Significance. Final Report, June 1969-March 1970.

ERIC Educational Resources Information Center

Tallman, Oliver H.

A digital simulation of a model for the processing of visual images is derived from known aspects of the human visual system. The fundamental principle of computation suggested by a biological model is a transformation that distributes information contained in an input stimulus everywhere in a transform domain. Each sensory input contributes under…

Investigation of Neural Strategies of Visual Search

NASA Technical Reports Server (NTRS)

Krauzlis, Richard J.

2003-01-01

The goal of this project was to measure how neurons in the superior colliculus (SC) change their activity during a visual search task. Specifically, we proposed to measure how the activity of these neurons was altered by the discriminability of visual targets and to test how these changes might predict the changes in the subjects performance. The primary rationale for this study was that understanding how the information encoded by these neurons constrains overall search performance would foster the development of better models of human performance. Work performed during the period supported by this grant has achieved these aims. First, we have recorded from neurons in the superior colliculus (SC) during a visual search task in which the difficulty of the task and the performance of the subject was systematically varied. The results from these single-neuron physiology experiments shows that prior to eye movement onset, the difference in activity across the ensemble of neurons reaches a fixed threshold value, reflecting the operation of a winner-take-all mechanism. Second, we have developed a model of eye movement decisions based on the principle of winner-take-all . The model incorporates the idea that the overt saccade choice reflects only one of the multiple saccades prepared during visual discrimination, consistent with our physiological data. The value of the model is that, unlike previous models, it is able to account for both the latency and the percent correct of saccade choices.

Slushy weightings for the optimal pilot model. [considering visual tracking task

NASA Technical Reports Server (NTRS)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Spatial Visualization--A Gateway to Computer-Based Technology.

ERIC Educational Resources Information Center

Norman, Kent L.

1994-01-01

A model is proposed for the influence of individual differences on performance when computer-based technology is introduced. The primary cognitive factor driving differences in performance is spatial visualization ability. Four techniques for mitigating the negative impact of low spatial visualization are discussed: spatial metaphors, graphical…

Visual search and coordination changes in response to video and point-light demonstrations without KR.

PubMed

Horn, R R; Williams, A M; Scott, M A; Hodges, N J

2005-07-01

The authors examined the observational learning of 24 participants whom they constrained to use the model by removing intrinsic visual knowledge of results (KR). Matched participants assigned to video (VID), point-light (PL), and no-model (CON) groups performed a soccer-chipping task in which vision was occluded at ball contact. Pre- and posttests were interspersed with alternating periods of demonstration and acquisition. The authors assessed delayed retention 2-3 days later. In support of the visual perception perspective, the participants who observed the models showed immediate and enduring changes to more closely imitate the model's relative motion. While observing the demonstration, the PL group participants were more selective in their visual search than were the VID group participants but did not perform more accurately or learn more.

Local spatio-temporal analysis in vision systems

NASA Astrophysics Data System (ADS)

Geisler, Wilson S.; Bovik, Alan; Cormack, Lawrence; Ghosh, Joydeep; Gildeen, David

1994-07-01

The aims of this project are the following: (1) develop a physiologically and psychophysically based model of low-level human visual processing (a key component of which are local frequency coding mechanisms); (2) develop image models and image-processing methods based upon local frequency coding; (3) develop algorithms for performing certain complex visual tasks based upon local frequency representations, (4) develop models of human performance in certain complex tasks based upon our understanding of low-level processing; and (5) develop a computational testbed for implementing, evaluating and visualizing the proposed models and algorithms, using a massively parallel computer. Progress has been substantial on all aims. The highlights include the following: (1) completion of a number of psychophysical and physiological experiments revealing new, systematic and exciting properties of the primate (human and monkey) visual system; (2) further development of image models that can accurately represent the local frequency structure in complex images; (3) near completion in the construction of the Texas Active Vision Testbed; (4) development and testing of several new computer vision algorithms dealing with shape-from-texture, shape-from-stereo, and depth-from-focus; (5) implementation and evaluation of several new models of human visual performance; and (6) evaluation, purchase and installation of a MasPar parallel computer.

[Hybrid 3-D rendering of the thorax and surface-based virtual bronchoscopy in surgical and interventional therapy control].

PubMed

Seemann, M D; Gebicke, K; Luboldt, W; Albes, J M; Vollmar, J; Schäfer, J F; Beinert, T; Englmeier, K H; Bitzer, M; Claussen, C D

2001-07-01

The aim of this study was to demonstrate the possibilities of a hybrid rendering method, the combination of a color-coded surface and volume rendering method, with the feasibility of performing surface-based virtual endoscopy with different representation models in the operative and interventional therapy control of the chest. In 6 consecutive patients with partial lung resection (n = 2) and lung transplantation (n = 4) a thin-section spiral computed tomography of the chest was performed. The tracheobronchial system and the introduced metallic stents were visualized using a color-coded surface rendering method. The remaining thoracic structures were visualized using a volume rendering method. For virtual bronchoscopy, the tracheobronchial system was visualized using a triangle surface model, a shaded-surface model and a transparent shaded-surface model. The hybrid 3D visualization uses the advantages of both the color-coded surface and volume rendering methods and facilitates a clear representation of the tracheobronchial system and the complex topographical relationship of morphological and pathological changes without loss of diagnostic information. Performing virtual bronchoscopy with the transparent shaded-surface model facilitates a reasonable to optimal, simultaneous visualization and assessment of the surface structure of the tracheobronchial system and the surrounding mediastinal structures and lesions. Hybrid rendering relieve the morphological assessment of anatomical and pathological changes without the need for time-consuming detailed analysis and presentation of source images. Performing virtual bronchoscopy with a transparent shaded-surface model offers a promising alternative to flexible fiberoptic bronchoscopy.

Modeling visual problem solving as analogical reasoning.

PubMed

Lovett, Andrew; Forbus, Kenneth

2017-01-01

We present a computational model of visual problem solving, designed to solve problems from the Raven's Progressive Matrices intelligence test. The model builds on the claim that analogical reasoning lies at the heart of visual problem solving, and intelligence more broadly. Images are compared via structure mapping, aligning the common relational structure in 2 images to identify commonalities and differences. These commonalities or differences can themselves be reified and used as the input for future comparisons. When images fail to align, the model dynamically rerepresents them to facilitate the comparison. In our analysis, we find that the model matches adult human performance on the Standard Progressive Matrices test, and that problems which are difficult for the model are also difficult for people. Furthermore, we show that model operations involving abstraction and rerepresentation are particularly difficult for people, suggesting that these operations may be critical for performing visual problem solving, and reasoning more generally, at the highest level. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Models for Improving the Delivery of Services to: Gifted Students in the Areas of Visual and Performing Arts. Research & Demonstration Series in Gifted Education.

ERIC Educational Resources Information Center

Ohio State Dept. of Education, Columbus. Div. of Special Education.

This report describes three model demonstration projects in Ohio school districts which focused on strategies for identifying students gifted in visual and performing arts and delivering hands-on arts education and appreciation experiences. Presented for each program is information on: identifying characteristics (district, location, school…

Performance enhancement for audio-visual speaker identification using dynamic facial muscle model.

PubMed

Asadpour, Vahid; Towhidkhah, Farzad; Homayounpour, Mohammad Mehdi

2006-10-01

Science of human identification using physiological characteristics or biometry has been of great concern in security systems. However, robust multimodal identification systems based on audio-visual information has not been thoroughly investigated yet. Therefore, the aim of this work to propose a model-based feature extraction method which employs physiological characteristics of facial muscles producing lip movements. This approach adopts the intrinsic properties of muscles such as viscosity, elasticity, and mass which are extracted from the dynamic lip model. These parameters are exclusively dependent on the neuro-muscular properties of speaker; consequently, imitation of valid speakers could be reduced to a large extent. These parameters are applied to a hidden Markov model (HMM) audio-visual identification system. In this work, a combination of audio and video features has been employed by adopting a multistream pseudo-synchronized HMM training method. Noise robust audio features such as Mel-frequency cepstral coefficients (MFCC), spectral subtraction (SS), and relative spectra perceptual linear prediction (J-RASTA-PLP) have been used to evaluate the performance of the multimodal system once efficient audio feature extraction methods have been utilized. The superior performance of the proposed system is demonstrated on a large multispeaker database of continuously spoken digits, along with a sentence that is phonetically rich. To evaluate the robustness of algorithms, some experiments were performed on genetically identical twins. Furthermore, changes in speaker voice were simulated with drug inhalation tests. In 3 dB signal to noise ratio (SNR), the dynamic muscle model improved the identification rate of the audio-visual system from 91 to 98%. Results on identical twins revealed that there was an apparent improvement on the performance for the dynamic muscle model-based system, in which the identification rate of the audio-visual system was enhanced from 87 to 96%.

A computational model of spatial visualization capacity.

PubMed

Lyon, Don R; Gunzelmann, Glenn; Gluck, Kevin A

2008-09-01

Visualizing spatial material is a cornerstone of human problem solving, but human visualization capacity is sharply limited. To investigate the sources of this limit, we developed a new task to measure visualization accuracy for verbally-described spatial paths (similar to street directions), and implemented a computational process model to perform it. In this model, developed within the Adaptive Control of Thought-Rational (ACT-R) architecture, visualization capacity is limited by three mechanisms. Two of these (associative interference and decay) are longstanding characteristics of ACT-R's declarative memory. A third (spatial interference) is a new mechanism motivated by spatial proximity effects in our data. We tested the model in two experiments, one with parameter-value fitting, and a replication without further fitting. Correspondence between model and data was close in both experiments, suggesting that the model may be useful for understanding why visualizing new, complex spatial material is so difficult.

A stable biologically motivated learning mechanism for visual feature extraction to handle facial categorization.

PubMed

Rajaei, Karim; Khaligh-Razavi, Seyed-Mahdi; Ghodrati, Masoud; Ebrahimpour, Reza; Shiri Ahmad Abadi, Mohammad Ebrahim

2012-01-01

The brain mechanism of extracting visual features for recognizing various objects has consistently been a controversial issue in computational models of object recognition. To extract visual features, we introduce a new, biologically motivated model for facial categorization, which is an extension of the Hubel and Wiesel simple-to-complex cell hierarchy. To address the synaptic stability versus plasticity dilemma, we apply the Adaptive Resonance Theory (ART) for extracting informative intermediate level visual features during the learning process, which also makes this model stable against the destruction of previously learned information while learning new information. Such a mechanism has been suggested to be embedded within known laminar microcircuits of the cerebral cortex. To reveal the strength of the proposed visual feature learning mechanism, we show that when we use this mechanism in the training process of a well-known biologically motivated object recognition model (the HMAX model), it performs better than the HMAX model in face/non-face classification tasks. Furthermore, we demonstrate that our proposed mechanism is capable of following similar trends in performance as humans in a psychophysical experiment using a face versus non-face rapid categorization task.

A human visual model-based approach of the visual attention and performance evaluation

NASA Astrophysics Data System (ADS)

Le Meur, Olivier; Barba, Dominique; Le Callet, Patrick; Thoreau, Dominique

2005-03-01

In this paper, a coherent computational model of visual selective attention for color pictures is described and its performances are precisely evaluated. The model based on some important behaviours of the human visual system is composed of four parts: visibility, perception, perceptual grouping and saliency map construction. This paper focuses mainly on its performances assessment by achieving extended subjective and objective comparisons with real fixation points captured by an eye-tracking system used by the observers in a task-free viewing mode. From the knowledge of the ground truth, qualitatively and quantitatively comparisons have been made in terms of the measurement of the linear correlation coefficient (CC) and of the Kulback Liebler divergence (KL). On a set of 10 natural color images, the results show that the linear correlation coefficient and the Kullback Leibler divergence are of about 0.71 and 0.46, respectively. CC and Kl measures with this model are respectively improved by about 4% and 7% compared to the best model proposed by L.Itti. Moreover, by comparing the ability of our model to predict eye movements produced by an average observer, we can conclude that our model succeeds quite well in predicting the spatial locations of the most important areas of the image content.

Top-Down Visual Saliency via Joint CRF and Dictionary Learning.

PubMed

Yang, Jimei; Yang, Ming-Hsuan

2017-03-01

Top-down visual saliency is an important module of visual attention. In this work, we propose a novel top-down saliency model that jointly learns a Conditional Random Field (CRF) and a visual dictionary. The proposed model incorporates a layered structure from top to bottom: CRF, sparse coding and image patches. With sparse coding as an intermediate layer, CRF is learned in a feature-adaptive manner; meanwhile with CRF as the output layer, the dictionary is learned under structured supervision. For efficient and effective joint learning, we develop a max-margin approach via a stochastic gradient descent algorithm. Experimental results on the Graz-02 and PASCAL VOC datasets show that our model performs favorably against state-of-the-art top-down saliency methods for target object localization. In addition, the dictionary update significantly improves the performance of our model. We demonstrate the merits of the proposed top-down saliency model by applying it to prioritizing object proposals for detection and predicting human fixations.

Simulating the Role of Visual Selective Attention during the Development of Perceptual Completion

ERIC Educational Resources Information Center

Schlesinger, Matthew; Amso, Dima; Johnson, Scott P.

2012-01-01

We recently proposed a multi-channel, image-filtering model for simulating the development of visual selective attention in young infants (Schlesinger, Amso & Johnson, 2007). The model not only captures the performance of 3-month-olds on a visual search task, but also implicates two cortical regions that may play a role in the development of…

An Ideal Observer Analysis of Visual Working Memory

PubMed Central

Sims, Chris R.; Jacobs, Robert A.; Knill, David C.

2013-01-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this paper we develop an ideal observer analysis of human visual working memory, by deriving the expected behavior of an optimally performing, but limited-capacity memory system. This analysis is framed around rate–distortion theory, a branch of information theory that provides optimal bounds on the accuracy of information transmission subject to a fixed information capacity. The result of the ideal observer analysis is a theoretical framework that provides a task-independent and quantitative definition of visual memory capacity and yields novel predictions regarding human performance. These predictions are subsequently evaluated and confirmed in two empirical studies. Further, the framework is general enough to allow the specification and testing of alternative models of visual memory (for example, how capacity is distributed across multiple items). We demonstrate that a simple model developed on the basis of the ideal observer analysis—one which allows variability in the number of stored memory representations, but does not assume the presence of a fixed item limit—provides an excellent account of the empirical data, and further offers a principled re-interpretation of existing models of visual working memory. PMID:22946744

A probabilistic model of overt visual attention for cognitive robots.

PubMed

Begum, Momotaz; Karray, Fakhri; Mann, George K I; Gosine, Raymond G

2010-10-01

Visual attention is one of the major requirements for a robot to serve as a cognitive companion for human. The robotic visual attention is mostly concerned with overt attention which accompanies head and eye movements of a robot. In this case, each movement of the camera head triggers a number of events, namely transformation of the camera and the image coordinate systems, change of content of the visual field, and partial appearance of the stimuli. All of these events contribute to the reduction in probability of meaningful identification of the next focus of attention. These events are specific to overt attention with head movement and, therefore, their effects are not addressed in the classical models of covert visual attention. This paper proposes a Bayesian model as a robot-centric solution for the overt visual attention problem. The proposed model, while taking inspiration from the primates visual attention mechanism, guides a robot to direct its camera toward behaviorally relevant and/or visually demanding stimuli. A particle filter implementation of this model addresses the challenges involved in overt attention with head movement. Experimental results demonstrate the performance of the proposed model.

Influence of combined visual and vestibular cues on human perception and control of horizontal rotation

NASA Technical Reports Server (NTRS)

Zacharias, G. L.; Young, L. R.

1981-01-01

Measurements are made of manual control performance in the closed-loop task of nulling perceived self-rotation velocity about an earth-vertical axis. Self-velocity estimation is modeled as a function of the simultaneous presentation of vestibular and peripheral visual field motion cues. Based on measured low-frequency operator behavior in three visual field environments, a parallel channel linear model is proposed which has separate visual and vestibular pathways summing in a complementary manner. A dual-input describing function analysis supports the complementary model; vestibular cues dominate sensation at higher frequencies. The describing function model is extended by the proposal of a nonlinear cue conflict model, in which cue weighting depends on the level of agreement between visual and vestibular cues.

Enhanced visual performance in obsessive compulsive personality disorder.

PubMed

Ansari, Zohreh; Fadardi, Javad Salehi

2016-12-01

Visual performance is considered as commanding modality in human perception. We tested whether Obsessive-compulsive personality disorder (OCPD) people do differently in visual performance tasks than people without OCPD. One hundred ten students of Ferdowsi University of Mashhad and non-student participants were tested by Structured Clinical Interview for DSM-IV Axis II Personality Disorders (SCID-II), among whom 18 (mean age = 29.55; SD = 5.26; 84% female) met the criteria for OCPD classification; controls were 20 persons (mean age = 27.85; SD = 5.26; female = 84%), who did not met the OCPD criteria. Both groups were tested on a modified Flicker task for two dimensions of visual performance (i.e., visual acuity: detecting the location of change, complexity, and size; and visual contrast sensitivity). The OCPD group had responded more accurately on pairs related to size, complexity, and contrast, but spent more time to detect a change on pairs related to complexity and contrast. The OCPD individuals seem to have more accurate visual performance than non-OCPD controls. The findings support the relationship between personality characteristics and visual performance within the framework of top-down processing model. © 2016 Scandinavian Psychological Associations and John Wiley & Sons Ltd.

A Model of Manual Control with Perspective Scene Viewing

NASA Technical Reports Server (NTRS)

Sweet, Barbara Townsend

2013-01-01

A model of manual control during perspective scene viewing is presented, which combines the Crossover Model with a simpli ed model of perspective-scene viewing and visual- cue selection. The model is developed for a particular example task: an idealized constant- altitude task in which the operator controls longitudinal position in the presence of both longitudinal and pitch disturbances. An experiment is performed to develop and vali- date the model. The model corresponds closely with the experimental measurements, and identi ed model parameters are highly consistent with the visual cues available in the perspective scene. The modeling results indicate that operators used one visual cue for position control, and another visual cue for velocity control (lead generation). Additionally, operators responded more quickly to rotation (pitch) than translation (longitudinal).

Verbal and visual-spatial working memory and mathematical ability in different domains throughout primary school.

PubMed

Van de Weijer-Bergsma, Eva; Kroesbergen, Evelyn H; Van Luit, Johannes E H

2015-04-01

The relative importance of visual-spatial and verbal working memory for mathematics performance and learning seems to vary with age, the novelty of the material, and the specific math domain that is investigated. In this study, the relations between verbal and visual-spatial working memory and performance in four math domains (i.e., addition, subtraction, multiplication, and division) at different ages during primary school are investigated. Children (N = 4337) from grades 2 through 6 participated. Visual-spatial and verbal working memory were assessed using online computerized tasks. Math performance was assessed at the start, middle, and end of the school year using a speeded arithmetic test. Multilevel Multigroup Latent Growth Modeling was used to model individual differences in level and growth in math performance, and examine the predictive value of working memory per grade, while controlling for effects of classroom membership. The results showed that as grade level progressed, the predictive value of visual-spatial working memory for individual differences in level of mathematics performance waned, while the predictive value of verbal working memory increased. Working memory did not predict individual differences between children in their rate of performance growth throughout the school year. These findings are discussed in relation to three, not mutually exclusive, explanations for such age-related findings.

Human visual performance model for crewstation design

NASA Technical Reports Server (NTRS)

Larimer, James; Prevost, Michael; Arditi, Aries; Azueta, Steven; Bergen, James; Lubin, Jeffrey

1991-01-01

An account is given of a Visibility Modeling Tool (VMT) which furnishes a crew-station designer with the means to assess configurational tradeoffs, with a view to the impact of various options on the unambiguous access of information to the pilot. The interactive interface of the VMT allows the manipulation of cockpit geometry, ambient lighting, pilot ergonomics, and the displayed symbology. Performance data can be displayed in the form of 3D contours into the crewstation graphic model, thereby yielding an indication of the operator's visual capabilities.

Public Health Analysis Transport Optimization Model v. 1.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Beyeler, Walt; Finley, Patrick; Walser, Alex

PHANTOM models logistic functions of national public health systems. The system enables public health officials to visualize and coordinate options for public health surveillance, diagnosis, response and administration in an integrated analytical environment. Users may simulate and analyze system performance applying scenarios that represent current conditions or future contingencies what-if analyses of potential systemic improvements. Public health networks are visualized as interactive maps, with graphical displays of relevant system performance metrics as calculated by the simulation modeling components.

Fast neuromimetic object recognition using FPGA outperforms GPU implementations.

PubMed

Orchard, Garrick; Martin, Jacob G; Vogelstein, R Jacob; Etienne-Cummings, Ralph

2013-08-01

Recognition of objects in still images has traditionally been regarded as a difficult computational problem. Although modern automated methods for visual object recognition have achieved steadily increasing recognition accuracy, even the most advanced computational vision approaches are unable to obtain performance equal to that of humans. This has led to the creation of many biologically inspired models of visual object recognition, among them the hierarchical model and X (HMAX) model. HMAX is traditionally known to achieve high accuracy in visual object recognition tasks at the expense of significant computational complexity. Increasing complexity, in turn, increases computation time, reducing the number of images that can be processed per unit time. In this paper we describe how the computationally intensive and biologically inspired HMAX model for visual object recognition can be modified for implementation on a commercial field-programmable aate Array, specifically the Xilinx Virtex 6 ML605 evaluation board with XC6VLX240T FPGA. We show that with minor modifications to the traditional HMAX model we can perform recognition on images of size 128 × 128 pixels at a rate of 190 images per second with a less than 1% loss in recognition accuracy in both binary and multiclass visual object recognition tasks.

Functional Imaging of Audio-Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed

Rinne, Teemu; Muers, Ross S; Salo, Emma; Slater, Heather; Petkov, Christopher I

2017-06-01

The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio-visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio-visual selective attention modulates the primate brain, identify sources for "lost" attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. © The Author 2017. Published by Oxford University Press.

Functional Imaging of Audio–Visual Selective Attention in Monkeys and Humans: How do Lapses in Monkey Performance Affect Cross-Species Correspondences?

PubMed Central

Muers, Ross S.; Salo, Emma; Slater, Heather; Petkov, Christopher I.

2017-01-01

Abstract The cross-species correspondences and differences in how attention modulates brain responses in humans and animal models are poorly understood. We trained 2 monkeys to perform an audio–visual selective attention task during functional magnetic resonance imaging (fMRI), rewarding them to attend to stimuli in one modality while ignoring those in the other. Monkey fMRI identified regions strongly modulated by auditory or visual attention. Surprisingly, auditory attention-related modulations were much more restricted in monkeys than humans performing the same tasks during fMRI. Further analyses ruled out trivial explanations, suggesting that labile selective-attention performance was associated with inhomogeneous modulations in wide cortical regions in the monkeys. The findings provide initial insights into how audio–visual selective attention modulates the primate brain, identify sources for “lost” attention effects in monkeys, and carry implications for modeling the neurobiology of human cognition with nonhuman animals. PMID:28419201

Large Terrain Modeling and Visualization for Planets

NASA Technical Reports Server (NTRS)

Myint, Steven; Jain, Abhinandan; Cameron, Jonathan; Lim, Christopher

2011-01-01

Physics-based simulations are actively used in the design, testing, and operations phases of surface and near-surface planetary space missions. One of the challenges in realtime simulations is the ability to handle large multi-resolution terrain data sets within models as well as for visualization. In this paper, we describe special techniques that we have developed for visualization, paging, and data storage for dealing with these large data sets. The visualization technique uses a real-time GPU-based continuous level-of-detail technique that delivers multiple frames a second performance even for planetary scale terrain model sizes.

The performance & flow visualization studies of three-dimensional (3-D) wind turbine blade models

NASA Astrophysics Data System (ADS)

Sutrisno, Prajitno, Purnomo, W., Setyawan B.

2016-06-01

Recently, studies on the design of 3-D wind turbine blades have a less attention even though 3-D blade products are widely sold. In contrary, advanced studies in 3-D helicopter blade tip have been studied rigorously. Studies in wind turbine blade modeling are mostly assumed that blade spanwise sections behave as independent two-dimensional airfoils, implying that there is no exchange of momentum in the spanwise direction. Moreover, flow visualization experiments are infrequently conducted. Therefore, a modeling study of wind turbine blade with visualization experiment is needed to be improved to obtain a better understanding. The purpose of this study is to investigate the performance of 3-D wind turbine blade models with backward-forward swept and verify the flow patterns using flow visualization. In this research, the blade models are constructed based on the twist and chord distributions following Schmitz's formula. Forward and backward swept are added to the rotating blades. Based on this, the additional swept would enhance or diminish outward flow disturbance or stall development propagation on the spanwise blade surfaces to give better blade design. Some combinations, i. e., b lades with backward swept, provide a better 3-D favorable rotational force of the rotor system. The performance of the 3-D wind turbine system model is measured by a torque meter, employing Prony's braking system. Furthermore, the 3-D flow patterns around the rotating blade models are investigated by applying "tuft-visualization technique", to study the appearance of laminar, separated, and boundary layer flow patterns surrounding the 3-dimentional blade system.

A Closed-Loop Model of Operator Visual Attention, Situation Awareness, and Performance Across Automation Mode Transitions.

PubMed

Johnson, Aaron W; Duda, Kevin R; Sheridan, Thomas B; Oman, Charles M

2017-03-01

This article describes a closed-loop, integrated human-vehicle model designed to help understand the underlying cognitive processes that influenced changes in subject visual attention, mental workload, and situation awareness across control mode transitions in a simulated human-in-the-loop lunar landing experiment. Control mode transitions from autopilot to manual flight may cause total attentional demands to exceed operator capacity. Attentional resources must be reallocated and reprioritized, which can increase the average uncertainty in the operator's estimates of low-priority system states. We define this increase in uncertainty as a reduction in situation awareness. We present a model built upon the optimal control model for state estimation, the crossover model for manual control, and the SEEV (salience, effort, expectancy, value) model for visual attention. We modify the SEEV attention executive to direct visual attention based, in part, on the uncertainty in the operator's estimates of system states. The model was validated using the simulated lunar landing experimental data, demonstrating an average difference in the percentage of attention ≤3.6% for all simulator instruments. The model's predictions of mental workload and situation awareness, measured by task performance and system state uncertainty, also mimicked the experimental data. Our model supports the hypothesis that visual attention is influenced by the uncertainty in system state estimates. Conceptualizing situation awareness around the metric of system state uncertainty is a valuable way for system designers to understand and predict how reallocations in the operator's visual attention during control mode transitions can produce reallocations in situation awareness of certain states.

Visualising Earth's Mantle based on Global Adjoint Tomography

NASA Astrophysics Data System (ADS)

Bozdag, E.; Pugmire, D.; Lefebvre, M. P.; Hill, J.; Komatitsch, D.; Peter, D. B.; Podhorszki, N.; Tromp, J.

2017-12-01

Recent advances in 3D wave propagation solvers and high-performance computing have enabled regional and global full-waveform inversions. Interpretation of tomographic models is often done on visually. Robust and efficient visualization tools are necessary to thoroughly investigate large model files, particularly at the global scale. In collaboration with Oak Ridge National Laboratory (ORNL), we have developed effective visualization tools and used for visualization of our first-generation global model, GLAD-M15 (Bozdag et al. 2016). VisIt (https://wci.llnl.gov/simulation/computer-codes/visit/) is used for initial exploration of the models and for extraction of seismological features. The broad capability of VisIt, and its demonstrated scalability proved valuable for experimenting with different visualization techniques, and in the creation of timely results. Utilizing VisIt's plugin-architecture, a data reader plugin was developed, which reads the ADIOS (https://www.olcf.ornl.gov/center-projects/adios/) format of our model files. Blender (https://www.blender.org) is used for the setup of lighting, materials, camera paths and rendering of geometry. Python scripting was used to control the orchestration of different geometries, as well as camera animation for 3D movies. While we continue producing 3D contour plots and movies for various seismic parameters to better visualize plume- and slab-like features as well as anisotropy throughout the mantle, our aim is to make visualization an integral part of our global adjoint tomography workflow to routinely produce various 2D cross-sections to facilitate examination of our models after each iteration. This will ultimately form the basis for use of pattern recognition techniques in our investigations. Simulations for global adjoint tomography are performed on ORNL's Titan system and visualization is done in parallel on ORNL's post-processing cluster Rhea.

visCOS: An R-package to evaluate model performance of hydrological models

NASA Astrophysics Data System (ADS)

Klotz, Daniel; Herrnegger, Mathew; Wesemann, Johannes; Schulz, Karsten

2016-04-01

The evaluation of model performance is a central part of (hydrological) modelling. Much attention has been given to the development of evaluation criteria and diagnostic frameworks. (Klemeš, 1986; Gupta et al., 2008; among many others). Nevertheless, many applications exist for which objective functions do not yet provide satisfying summaries. Thus, the necessity to visualize results arises in order to explore a wider range of model capacities, be it strengths or deficiencies. Visualizations are usually devised for specific projects and these efforts are often not distributed to a broader community (e.g. via open source software packages). Hence, the opportunity to explicitly discuss a state-of-the-art presentation technique is often missed. We therefore present a comprehensive R-package for evaluating model performance by visualizing and exploring different aspects of hydrological time-series. The presented package comprises a set of useful plots and visualization methods, which complement existing packages, such as hydroGOF (Zambrano-Bigiarini et al., 2012). It is derived from practical applications of the hydrological models COSERO and COSEROreg (Kling et al., 2014). visCOS, providing an interface in R, represents an easy-to-use software package for visualizing and assessing model performance and can be implemented in the process of model calibration or model development. The package provides functions to load hydrological data into R, clean the data, process, visualize, explore and finally save the results in a consistent way. Together with an interactive zoom function of the time series, an online calculation of the objective functions for variable time-windows is included. Common hydrological objective functions, such as the Nash-Sutcliffe Efficiency and the Kling-Gupta Efficiency, can also be evaluated and visualized in different ways for defined sub-periods like hydrological years or seasonal sections. Many hydrologists use long-term water-balances as a pivotal tool in model evaluation. They allow inferences about different systematic model-shortcomings and are an efficient way for communicating these in practice (Schulz et al., 2015). The evaluation and construction of such water balances is implemented with the presented package. During the (manual) calibration of a model or in the scope of model development, many model runs and iterations are necessary. Thus, users are often interested in comparing different model results in a visual way in order to learn about the model and to analyse parameter-changes on the output. A method to illuminate these differences and the evolution of changes is also included. References: • Gupta, H.V.; Wagener, T.; Liu, Y. (2008): Reconciling theory with observations: elements of a diagnostic approach to model evaluation, Hydrol. Process. 22, doi: 10.1002/hyp.6989. • Klemeš, V. (1986): Operational testing of hydrological simulation models, Hydrolog. Sci. J., doi: 10.1080/02626668609491024. • Kling, H.; Stanzel, P.; Fuchs, M.; and Nachtnebel, H. P. (2014): Performance of the COSERO precipitation-runoff model under non-stationary conditions in basins with different climates, Hydrolog. Sci. J., doi: 10.1080/02626667.2014.959956. • Schulz, K., Herrnegger, M., Wesemann, J., Klotz, D. Senoner, T. (2015): Kalibrierung COSERO - Mur für Pro Vis, Verbund Trading GmbH (Abteilung STG), final report, Institute of Water Management, Hydrology and Hydraulic Engineering, University of Natural Resources and Applied Life Sciences, Vienna, Austria, 217pp. • Zambrano-Bigiarini, M; Bellin, A. (2010): Comparing Goodness-of-fit Measures for Calibration of Models Focused on Extreme Events. European Geosciences Union (EGU), Geophysical Research Abstracts 14, EGU2012-11549-1.

3D visualization of ultra-fine ICON climate simulation data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Spickermann, Dela; Böttinger, Michael

2016-04-01

Advances in high performance computing and model development allow the simulation of finer and more detailed climate experiments. The new ICON model is based on an unstructured triangular grid and can be used for a wide range of applications, ranging from global coupled climate simulations down to very detailed and high resolution regional experiments. It consists of an atmospheric and an oceanic component and scales very well for high numbers of cores. This allows us to conduct very detailed climate experiments with ultra-fine resolutions. ICON is jointly developed in partnership with DKRZ by the Max Planck Institute for Meteorology and the German Weather Service. This presentation discusses our current workflow for analyzing and visualizing this high resolution data. The ICON model has been used for eddy resolving (<10km) ocean simulations, as well as for ultra-fine cloud resolving (120m) atmospheric simulations. This results in very large 3D time dependent multi-variate data that need to be displayed and analyzed. We have developed specific plugins for the free available visualization software ParaView and Vapor, which allows us to read and handle that much data. Within ParaView, we can additionally compare prognostic variables with performance data side by side to investigate the performance and scalability of the model. With the simulation running in parallel on several hundred nodes, an equal load balance is imperative. In our presentation we show visualizations of high-resolution ICON oceanographic and HDCP2 atmospheric simulations that were created using ParaView and Vapor. Furthermore we discuss our current efforts to improve our visualization capabilities, thereby exploring the potential of regular in-situ visualization, as well as of in-situ compression / post visualization.

Phenomenological model of visual acuity

NASA Astrophysics Data System (ADS)

Gómez-Pedrero, José A.; Alonso, José

2016-12-01

We propose in this work a model for describing visual acuity (V) as a function of defocus and pupil diameter. Although the model is mainly based on geometrical optics, it also incorporates nongeometrical effects phenomenologically. Compared to similar visual acuity models, the proposed one considers the effect of astigmatism and the variability of best corrected V among individuals; it also takes into account the accommodation and the "tolerance to defocus," the latter through a phenomenological parameter. We have fitted the model to the V data provided in the works of Holladay et al. and Peters, showing the ability of this model to accurately describe the variation of V against blur and pupil diameter. We have also performed a comparison between the proposed model and others previously published in the literature. The model is mainly intended for use in the design of ophthalmic compensations, but it can also be useful in other fields such as visual ergonomics, design of visual tests, and optical instrumentation.

Visualization and Analysis of Climate Simulation Performance Data

NASA Astrophysics Data System (ADS)

Röber, Niklas; Adamidis, Panagiotis; Behrens, Jörg

2015-04-01

Visualization is the key process of transforming abstract (scientific) data into a graphical representation, to aid in the understanding of the information hidden within the data. Climate simulation data sets are typically quite large, time varying, and consist of many different variables sampled on an underlying grid. A large variety of climate models - and sub models - exist to simulate various aspects of the climate system. Generally, one is mainly interested in the physical variables produced by the simulation runs, but model developers are also interested in performance data measured along with these simulations. Climate simulation models are carefully developed complex software systems, designed to run in parallel on large HPC systems. An important goal thereby is to utilize the entire hardware as efficiently as possible, that is, to distribute the workload as even as possible among the individual components. This is a very challenging task, and detailed performance data, such as timings, cache misses etc. have to be used to locate and understand performance problems in order to optimize the model implementation. Furthermore, the correlation of performance data to the processes of the application and the sub-domains of the decomposed underlying grid is vital when addressing communication and load imbalance issues. High resolution climate simulations are carried out on tens to hundreds of thousands of cores, thus yielding a vast amount of profiling data, which cannot be analyzed without appropriate visualization techniques. This PICO presentation displays and discusses the ICON simulation model, which is jointly developed by the Max Planck Institute for Meteorology and the German Weather Service and in partnership with DKRZ. The visualization and analysis of the models performance data allows us to optimize and fine tune the model, as well as to understand its execution on the HPC system. We show and discuss our workflow, as well as present new ideas and solutions that greatly aided our understanding. The software employed is based on Avizo Green, ParaView and SimVis, as well as own developed software extensions.

A rodent model for the study of invariant visual object recognition

PubMed Central

Zoccolan, Davide; Oertelt, Nadja; DiCarlo, James J.; Cox, David D.

2009-01-01

The human visual system is able to recognize objects despite tremendous variation in their appearance on the retina resulting from variation in view, size, lighting, etc. This ability—known as “invariant” object recognition—is central to visual perception, yet its computational underpinnings are poorly understood. Traditionally, nonhuman primates have been the animal model-of-choice for investigating the neuronal substrates of invariant recognition, because their visual systems closely mirror our own. Meanwhile, simpler and more accessible animal models such as rodents have been largely overlooked as possible models of higher-level visual functions, because their brains are often assumed to lack advanced visual processing machinery. As a result, little is known about rodents' ability to process complex visual stimuli in the face of real-world image variation. In the present work, we show that rats possess more advanced visual abilities than previously appreciated. Specifically, we trained pigmented rats to perform a visual task that required them to recognize objects despite substantial variation in their appearance, due to changes in size, view, and lighting. Critically, rats were able to spontaneously generalize to previously unseen transformations of learned objects. These results provide the first systematic evidence for invariant object recognition in rats and argue for an increased focus on rodents as models for studying high-level visual processing. PMID:19429704

Visual influence on path integration in darkness indicates a multimodal representation of large-scale space

PubMed Central

Tcheang, Lili; Bülthoff, Heinrich H.; Burgess, Neil

2011-01-01

Our ability to return to the start of a route recently performed in darkness is thought to reflect path integration of motion-related information. Here we provide evidence that motion-related interoceptive representations (proprioceptive, vestibular, and motor efference copy) combine with visual representations to form a single multimodal representation guiding navigation. We used immersive virtual reality to decouple visual input from motion-related interoception by manipulating the rotation or translation gain of the visual projection. First, participants walked an outbound path with both visual and interoceptive input, and returned to the start in darkness, demonstrating the influences of both visual and interoceptive information in a virtual reality environment. Next, participants adapted to visual rotation gains in the virtual environment, and then performed the path integration task entirely in darkness. Our findings were accurately predicted by a quantitative model in which visual and interoceptive inputs combine into a single multimodal representation guiding navigation, and are incompatible with a model of separate visual and interoceptive influences on action (in which path integration in darkness must rely solely on interoceptive representations). Overall, our findings suggest that a combined multimodal representation guides large-scale navigation, consistent with a role for visual imagery or a cognitive map. PMID:21199934

The effect of visual representation style in problem-solving: a perspective from cognitive processes.

PubMed

Nyamsuren, Enkhbold; Taatgen, Niels A

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving.

The Effect of Visual Representation Style in Problem-Solving: A Perspective from Cognitive Processes

PubMed Central

Nyamsuren, Enkhbold; Taatgen, Niels A.

2013-01-01

Using results from a controlled experiment and simulations based on cognitive models, we show that visual presentation style can have a significant impact on performance in a complex problem-solving task. We compared subject performances in two isomorphic, but visually different, tasks based on a card game of SET. Although subjects used the same strategy in both tasks, the difference in presentation style resulted in radically different reaction times and significant deviations in scanpath patterns in the two tasks. Results from our study indicate that low-level subconscious visual processes, such as differential acuity in peripheral vision and low-level iconic memory, can have indirect, but significant effects on decision making during a problem-solving task. We have developed two ACT-R models that employ the same basic strategy but deal with different presentations styles. Our ACT-R models confirm that changes in low-level visual processes triggered by changes in presentation style can propagate to higher-level cognitive processes. Such a domino effect can significantly affect reaction times and eye movements, without affecting the overall strategy of problem solving. PMID:24260415

Dissociating 'what' and 'how' in visual form agnosia: a computational investigation.

PubMed

Vecera, S P

2002-01-01

Patients with visual form agnosia exhibit a profound impairment in shape perception (what an object is) coupled with intact visuomotor functions (how to act on an object), demonstrating a dissociation between visual perception and action. How can these patients act on objects that they cannot perceive? Although two explanations of this 'what-how' dissociation have been offered, each explanation has shortcomings. A 'pathway information' account of the 'what-how' dissociation is presented in this paper. This account hypothesizes that 'where' and 'how' tasks require less information than 'what' tasks, thereby allowing 'where/how' to remain relatively spared in the face of neurological damage. Simulations with a neural network model test the predictions of the pathway information account. Following damage to an input layer common to the 'what' and 'where/how' pathways, the model performs object identification more poorly than spatial localization. Thus, the model offers a parsimonious explanation of differential 'what-how' performance in visual form agnosia. The simulation results are discussed in terms of their implications for visual form agnosia and other neuropsychological syndromes.

Visual face-movement sensitive cortex is relevant for auditory-only speech recognition.

PubMed

Riedel, Philipp; Ragert, Patrick; Schelinski, Stefanie; Kiebel, Stefan J; von Kriegstein, Katharina

2015-07-01

It is commonly assumed that the recruitment of visual areas during audition is not relevant for performing auditory tasks ('auditory-only view'). According to an alternative view, however, the recruitment of visual cortices is thought to optimize auditory-only task performance ('auditory-visual view'). This alternative view is based on functional magnetic resonance imaging (fMRI) studies. These studies have shown, for example, that even if there is only auditory input available, face-movement sensitive areas within the posterior superior temporal sulcus (pSTS) are involved in understanding what is said (auditory-only speech recognition). This is particularly the case when speakers are known audio-visually, that is, after brief voice-face learning. Here we tested whether the left pSTS involvement is causally related to performance in auditory-only speech recognition when speakers are known by face. To test this hypothesis, we applied cathodal transcranial direct current stimulation (tDCS) to the pSTS during (i) visual-only speech recognition of a speaker known only visually to participants and (ii) auditory-only speech recognition of speakers they learned by voice and face. We defined the cathode as active electrode to down-regulate cortical excitability by hyperpolarization of neurons. tDCS to the pSTS interfered with visual-only speech recognition performance compared to a control group without pSTS stimulation (tDCS to BA6/44 or sham). Critically, compared to controls, pSTS stimulation additionally decreased auditory-only speech recognition performance selectively for voice-face learned speakers. These results are important in two ways. First, they provide direct evidence that the pSTS is causally involved in visual-only speech recognition; this confirms a long-standing prediction of current face-processing models. Secondly, they show that visual face-sensitive pSTS is causally involved in optimizing auditory-only speech recognition. These results are in line with the 'auditory-visual view' of auditory speech perception, which assumes that auditory speech recognition is optimized by using predictions from previously encoded speaker-specific audio-visual internal models. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comprehensive decision tree models in bioinformatics.

PubMed

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics.

Comprehensive Decision Tree Models in Bioinformatics

PubMed Central

Stiglic, Gregor; Kocbek, Simon; Pernek, Igor; Kokol, Peter

2012-01-01

Purpose Classification is an important and widely used machine learning technique in bioinformatics. Researchers and other end-users of machine learning software often prefer to work with comprehensible models where knowledge extraction and explanation of reasoning behind the classification model are possible. Methods This paper presents an extension to an existing machine learning environment and a study on visual tuning of decision tree classifiers. The motivation for this research comes from the need to build effective and easily interpretable decision tree models by so called one-button data mining approach where no parameter tuning is needed. To avoid bias in classification, no classification performance measure is used during the tuning of the model that is constrained exclusively by the dimensions of the produced decision tree. Results The proposed visual tuning of decision trees was evaluated on 40 datasets containing classical machine learning problems and 31 datasets from the field of bioinformatics. Although we did not expected significant differences in classification performance, the results demonstrate a significant increase of accuracy in less complex visually tuned decision trees. In contrast to classical machine learning benchmarking datasets, we observe higher accuracy gains in bioinformatics datasets. Additionally, a user study was carried out to confirm the assumption that the tree tuning times are significantly lower for the proposed method in comparison to manual tuning of the decision tree. Conclusions The empirical results demonstrate that by building simple models constrained by predefined visual boundaries, one not only achieves good comprehensibility, but also very good classification performance that does not differ from usually more complex models built using default settings of the classical decision tree algorithm. In addition, our study demonstrates the suitability of visually tuned decision trees for datasets with binary class attributes and a high number of possibly redundant attributes that are very common in bioinformatics. PMID:22479449

Autonomous visual exploration creates developmental change in familiarity and novelty seeking behaviors

PubMed Central

Perone, Sammy; Spencer, John P.

2013-01-01

What motivates children to radically transform themselves during early development? We addressed this question in the domain of infant visual exploration. Over the first year, infants' exploration shifts from familiarity to novelty seeking. This shift is delayed in preterm relative to term infants and is stable within individuals over the course of the first year. Laboratory tasks have shed light on the nature of this familiarity-to-novelty shift, but it is not clear what motivates the infant to change her exploratory style. We probed this by letting a Dynamic Neural Field (DNF) model of visual exploration develop itself via accumulating experience in a virtual world. We then situated it in a canonical laboratory task. Much like infants, the model exhibited a familiarity-to-novelty shift. When we manipulated the initial conditions of the model, the model's performance was developmentally delayed much like preterm infants. This delay was overcome by enhancing the model's experience during development. We also found that the model's performance was stable at the level of the individual. Our simulations indicate that novelty seeking emerges with no explicit motivational source via the accumulation of visual experience within a complex, dynamical exploratory system. PMID:24065948

A probabilistic model for analysing the effect of performance levels on visual behaviour patterns of young sailors in simulated navigation.

PubMed

Manzanares, Aarón; Menayo, Ruperto; Segado, Francisco; Salmerón, Diego; Cano, Juan Antonio

2015-01-01

The visual behaviour is a determining factor in sailing due to the influence of the environmental conditions. The aim of this research was to determine the visual behaviour pattern in sailors with different practice time in one star race, applying a probabilistic model based on Markov chains. The sample of this study consisted of 20 sailors, distributed in two groups, top ranking (n = 10) and bottom ranking (n = 10), all of them competed in the Optimist Class. An automated system of measurement, which integrates the VSail-Trainer sail simulator and the Eye Tracking System(TM) was used. The variables under consideration were the sequence of fixations and the fixation recurrence time performed on each location by the sailors. The event consisted of one of simulated regatta start, with stable conditions of wind, competitor and sea. Results show that top ranking sailors perform a low recurrence time on relevant locations and higher on irrelevant locations while bottom ranking sailors make a low recurrence time in most of the locations. The visual pattern performed by bottom ranking sailors is focused around two visual pivots, which does not happen in the top ranking sailor's pattern. In conclusion, the Markov chains analysis has allowed knowing the visual behaviour pattern of the top and bottom ranking sailors and its comparison.

Feedforward object-vision models only tolerate small image variations compared to human

PubMed Central

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi

2014-01-01

Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modeling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well in image categorization under more complex image variations. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e., briefly presented masked stimuli with complex image variations), human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modeling. We show that this approach is not of significant help in solving the computational crux of object recognition (i.e., invariant object recognition) when the identity-preserving image variations become more complex. PMID:25100986

Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project

ERIC Educational Resources Information Center

Yap, Melvin J.; Balota, David A.; Sibley, Daragh E.; Ratcliff, Roger

2012-01-01

Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences among individuals who contributed to the English…

A non-invasive method for studying an index of pupil diameter and visual performance in the rhesus monkey.

PubMed

Fairhall, Sarah J; Dickson, Carol A; Scott, Leah; Pearce, Peter C

2006-04-01

A non-invasive model has been developed to estimate gaze direction and relative pupil diameter, in minimally restrained rhesus monkeys, to investigate the effects of low doses of ocularly administered cholinergic compounds on visual performance. Animals were trained to co-operate with a novel device, which enabled eye movements to be recorded using modified human eye-tracking equipment, and to perform a task which determined visual threshold contrast. Responses were made by gaze transfer under twilight conditions. 4% w/v pilocarpine nitrate was studied to demonstrate the suitability of the model. Pilocarpine induced marked miosis for >3 h which was accompanied by a decrement in task performance. The method obviates the need for invasive surgery and, as the position of point of gaze can be approximately defined, the approach may have utility in other areas of research involving non-human primates.

Probabilistic Modeling and Visualization of the Flexibility in Morphable Models

NASA Astrophysics Data System (ADS)

Lüthi, M.; Albrecht, T.; Vetter, T.

Statistical shape models, and in particular morphable models, have gained widespread use in computer vision, computer graphics and medical imaging. Researchers have started to build models of almost any anatomical structure in the human body. While these models provide a useful prior for many image analysis task, relatively little information about the shape represented by the morphable model is exploited. We propose a method for computing and visualizing the remaining flexibility, when a part of the shape is fixed. Our method, which is based on Probabilistic PCA, not only leads to an approach for reconstructing the full shape from partial information, but also allows us to investigate and visualize the uncertainty of a reconstruction. To show the feasibility of our approach we performed experiments on a statistical model of the human face and the femur bone. The visualization of the remaining flexibility allows for greater insight into the statistical properties of the shape.

Visual Perspective and Feedback Guidance for VR Free-Throw Training.

PubMed

Covaci, Alexandra; Olivier, Anne-Hélène; Multon, Franck

2015-01-01

Accurate distance perception and natural interactions are mandatory conditions when training precision aiming tasks in VR. However, many factors specific to virtual environments (VEs) lead to differences in the way users execute a motor task in VR versus the real world. To investigate these differences, the authors performed a study on basketball beginners' free-throw performance in VEs under different visual conditions. Although the success rate is not statistically different, some adaptations occurred in the way the users performed the task, depending on the visual conditions. In the third-person perspective visual condition, the release parameters indicate that the users more accurately estimated distance to target. Adding visual guidance information (gradual depth information showing the ideal ball trajectory) also led to more natural motor behavior. The final aim of this study was to develop a reliable basketball free-throw training system in VEs, so the authors compared beginners' performances in VR with experts' models of performance. Their results show that most of the performance variables tended to evolve closer to the experts' performance during the training in the VE.

A Unified Air-Sea Visualization System: Survey on Gridding Structures

NASA Technical Reports Server (NTRS)

Anand, Harsh; Moorhead, Robert

1995-01-01

The goal is to develop a Unified Air-Sea Visualization System (UASVS) to enable the rapid fusion of observational, archival, and model data for verification and analysis. To design and develop UASVS, modelers were polled to determine the gridding structures and visualization systems used, and their needs with respect to visual analysis. A basic UASVS requirement is to allow a modeler to explore multiple data sets within a single environment, or to interpolate multiple datasets onto one unified grid. From this survey, the UASVS should be able to visualize 3D scalar/vector fields; render isosurfaces; visualize arbitrary slices of the 3D data; visualize data defined on spectral element grids with the minimum number of interpolation stages; render contours; produce 3D vector plots and streamlines; provide unified visualization of satellite images, observations and model output overlays; display the visualization on a projection of the users choice; implement functions so the user can derive diagnostic values; animate the data to see the time-evolution; animate ocean and atmosphere at different rates; store the record of cursor movement, smooth the path, and animate a window around the moving path; repeatedly start and stop the visual time-stepping; generate VHS tape animations; work on a variety of workstations; and allow visualization across clusters of workstations and scalable high performance computer systems.

Foveated model observers to predict human performance in 3D images

NASA Astrophysics Data System (ADS)

Lago, Miguel A.; Abbey, Craig K.; Eckstein, Miguel P.

2017-03-01

We evaluate 3D search requires model observers that take into account the peripheral human visual processing (foveated models) to predict human observer performance. We show that two different 3D tasks, free search and location-known detection, influence the relative human visual detectability of two signals of different sizes in synthetic backgrounds mimicking the noise found in 3D digital breast tomosynthesis. One of the signals resembled a microcalcification (a small and bright sphere), while the other one was designed to look like a mass (a larger Gaussian blob). We evaluated current standard models observers (Hotelling; Channelized Hotelling; non-prewhitening matched filter with eye filter, NPWE; and non-prewhitening matched filter model, NPW) and showed that they incorrectly predict the relative detectability of the two signals in 3D search. We propose a new model observer (3D Foveated Channelized Hotelling Observer) that incorporates the properties of the visual system over a large visual field (fovea and periphery). We show that the foveated model observer can accurately predict the rank order of detectability of the signals in 3D images for each task. Together, these results motivate the use of a new generation of foveated model observers for predicting image quality for search tasks in 3D imaging modalities such as digital breast tomosynthesis or computed tomography.

Analytic Guided-Search Model of Human Performance Accuracy in Target- Localization Search Tasks

NASA Technical Reports Server (NTRS)

Eckstein, Miguel P.; Beutter, Brent R.; Stone, Leland S.

2000-01-01

Current models of human visual search have extended the traditional serial/parallel search dichotomy. Two successful models for predicting human visual search are the Guided Search model and the Signal Detection Theory model. Although these models are inherently different, it has been difficult to compare them because the Guided Search model is designed to predict response time, while Signal Detection Theory models are designed to predict performance accuracy. Moreover, current implementations of the Guided Search model require the use of Monte-Carlo simulations, a method that makes fitting the model's performance quantitatively to human data more computationally time consuming. We have extended the Guided Search model to predict human accuracy in target-localization search tasks. We have also developed analytic expressions that simplify simulation of the model to the evaluation of a small set of equations using only three free parameters. This new implementation and extension of the Guided Search model will enable direct quantitative comparisons with human performance in target-localization search experiments and with the predictions of Signal Detection Theory and other search accuracy models.

The influence of anaesthetists' experience on workload, performance and visual attention during simulated critical incidents.

PubMed

Schulz, Christian M; Schneider, Erich; Kohlbecher, Stefan; Hapfelmeier, Alexander; Heuser, Fabian; Wagner, Klaus J; Kochs, Eberhard F; Schneider, Gerhard

2014-10-01

Development of accurate Situation Awareness (SA) depends on experience and may be impaired during excessive workload. In order to gain adequate SA for decision making and performance, anaesthetists need to distribute visual attention effectively. Therefore, we hypothesized that in more experienced anaesthetists performance is better and increase of physiological workload is less during critical incidents. Additionally, we investigated the relation between physiological workload indicators and distribution of visual attention. In fifteen anaesthetists, the increase of pupil size and heart rate was assessed in course of a simulated critical incident. Simulator log files were used for performance assessment. An eye-tracking device (EyeSeeCam) provided data about the anaesthetists' distribution of visual attention. Performance was assessed as time until definitive treatment. T tests and multivariate generalized linear models (MANOVA) were used for retrospective statistical analysis. Mean pupil diameter increase was 8.1% (SD ± 4.3) in the less experienced and 15.8% (±10.4) in the more experienced subjects (p = 0.191). Mean heart rate increase was 10.2% (±6.7) and 10.5% (±8.3, p = 0.956), respectively. Performance did not depend on experience. Pupil diameter and heart rate increases were associated with a shift of visual attention from monitoring towards manual tasks (not significant). For the first time, the following four variables were assessed simultaneously: physiological workload indicators, performance, experience, and distribution of visual attention between "monitoring" and "manual" tasks. However, we were unable to detect significant interactions between these variables. This experimental model could prove valuable in the investigation of gaining and maintaining SA in the operation theatre.

Visualization Improves Supraclavicular Access to the Subclavian Vein in a Mixed Reality Simulator.

PubMed

Sappenfield, Joshua Warren; Smith, William Brit; Cooper, Lou Ann; Lizdas, David; Gonsalves, Drew B; Gravenstein, Nikolaus; Lampotang, Samsun; Robinson, Albert R

2018-07-01

We investigated whether visual augmentation (3D, real-time, color visualization) of a procedural simulator improved performance during training in the supraclavicular approach to the subclavian vein, not as widely known or used as its infraclavicular counterpart. To train anesthesiology residents to access a central vein, a mixed reality simulator with emulated ultrasound imaging was created using an anatomically authentic, 3D-printed, physical mannequin based on a computed tomographic scan of an actual human. The simulator has a corresponding 3D virtual model of the neck and upper chest anatomy. Hand-held instruments such as a needle, an ultrasound probe, and a virtual camera controller are directly manipulated by the trainee and tracked and recorded with submillimeter resolution via miniature, 6 degrees of freedom magnetic sensors. After Institutional Review Board approval, 69 anesthesiology residents and faculty were enrolled and received scripted instructions on how to perform subclavian venous access using the supraclavicular approach based on anatomic landmarks. The volunteers were randomized into 2 cohorts. The first used real-time 3D visualization concurrently with trial 1, but not during trial 2. The second did not use real-time 3D visualization concurrently with trial 1 or 2. However, after trial 2, they observed a 3D visualization playback of trial 2 before performing trial 3 without visualization. An automated scoring system based on time, success, and errors/complications generated objective performance scores. Nonparametric statistical methods were used to compare the scores between subsequent trials, differences between groups (real-time visualization versus no visualization versus delayed visualization), and improvement in scores between trials within groups. Although the real-time visualization group demonstrated significantly better performance than the delayed visualization group on trial 1 (P = .01), there was no difference in gain scores, between performance on the first trial and performance on the final trial, that were dependent on group (P = .13). In the delayed visualization group, the difference in performance between trial 1 and trial 2 was not significant (P = .09); reviewing performance on trial 2 before trial 3 resulted in improved performance when compared to trial 1 (P < .0001). There was no significant difference in median scores (P = .13) between the real-time visualization and delayed visualization groups for the last trial after both groups had received visualization. Participants reported a significant improvement in confidence in performing supraclavicular access to the subclavian vein. Standard deviations of scores, a measure of performance variability, decreased in the delayed visualization group after viewing the visualization. Real-time visual augmentation (3D visualization) in the mixed reality simulator improved performance during supraclavicular access to the subclavian vein. No difference was seen in the final trial of the group that received real-time visualization compared to the group that had delayed visualization playback of their prior attempt. Training with the mixed reality simulator improved participant confidence in performing an unfamiliar technique.

Comparison of Congruence Judgment and Auditory Localization Tasks for Assessing the Spatial Limits of Visual Capture

PubMed Central

Bosen, Adam K.; Fleming, Justin T.; Brown, Sarah E.; Allen, Paul D.; O'Neill, William E.; Paige, Gary D.

2016-01-01

Vision typically has better spatial accuracy and precision than audition, and as a result often captures auditory spatial perception when visual and auditory cues are presented together. One determinant of visual capture is the amount of spatial disparity between auditory and visual cues: when disparity is small visual capture is likely to occur, and when disparity is large visual capture is unlikely. Previous experiments have used two methods to probe how visual capture varies with spatial disparity. First, congruence judgment assesses perceived unity between cues by having subjects report whether or not auditory and visual targets came from the same location. Second, auditory localization assesses the graded influence of vision on auditory spatial perception by having subjects point to the remembered location of an auditory target presented with a visual target. Previous research has shown that when both tasks are performed concurrently they produce similar measures of visual capture, but this may not hold when tasks are performed independently. Here, subjects alternated between tasks independently across three sessions. A Bayesian inference model of visual capture was used to estimate perceptual parameters for each session, which were compared across tasks. Results demonstrated that the range of audio-visual disparities over which visual capture was likely to occur were narrower in auditory localization than in congruence judgment, which the model indicates was caused by subjects adjusting their prior expectation that targets originated from the same location in a task-dependent manner. PMID:27815630

The Effect of Modeling and Visualization Resources on Student Understanding of Physical Hydrology

ERIC Educational Resources Information Center

Marshall, Jilll A.; Castillo, Adam J.; Cardenas, M. Bayani

2015-01-01

We investigated the effect of modeling and visualization resources on upper-division, undergraduate and graduate students' performance on an open-ended assessment of their understanding of physical hydrology. The students were enrolled in one of five sections of a physical hydrology course. In two of the sections, students completed homework…

Pilot/vehicle model analysis of visual and motion cue requirements in flight simulation. [helicopter hovering

NASA Technical Reports Server (NTRS)

Baron, S.; Lancraft, R.; Zacharias, G.

1980-01-01

The optimal control model (OCM) of the human operator is used to predict the effect of simulator characteristics on pilot performance and workload. The piloting task studied is helicopter hover. Among the simulator characteristics considered were (computer generated) visual display resolution, field of view and time delay.

Sex differences in motor and cognitive abilities predicted from human evolutionary history with some implications for models of the visual system.

PubMed

Sanders, Geoff

2013-01-01

This article expands the knowledge base available to sex researchers by reviewing recent evidence for sex differences in coincidence-anticipation timing (CAT), motor control with the hand and arm, and visual processing of stimuli in near and far space. In CAT, the differences are between sex and, therefore, typical of other widely reported sex differences. Men perform CAT tasks with greater accuracy and precision than women, who tend to underestimate time to arrival. Null findings arise because significant sex differences are found with easy but not with difficult tasks. The differences in motor control and visual processing are within sex, and they underlie reciprocal patterns of performance in women and men. Motor control is exerted better by women with the hand than the arm. In contrast, men showed the reverse pattern. Visual processing is performed better by women with stimuli within hand reach (near space) as opposed to beyond hand reach (far space); men showed the reverse pattern. The sex differences seen in each of these three abilities are consistent with the evolutionary selection of men for hunting-related skills and women for gathering-related skills. The implications of the sex differences in visual processing for two visual system models of human vision are discussed.

Should visual speech cues (speechreading) be considered when fitting hearing aids?

NASA Astrophysics Data System (ADS)

Grant, Ken

2002-05-01

When talker and listener are face-to-face, visual speech cues become an important part of the communication environment, and yet, these cues are seldom considered when designing hearing aids. Models of auditory-visual speech recognition highlight the importance of complementary versus redundant speech information for predicting auditory-visual recognition performance. Thus, for hearing aids to work optimally when visual speech cues are present, it is important to know whether the cues provided by amplification and the cues provided by speechreading complement each other. In this talk, data will be reviewed that show nonmonotonicity between auditory-alone speech recognition and auditory-visual speech recognition, suggesting that efforts designed solely to improve auditory-alone recognition may not always result in improved auditory-visual recognition. Data will also be presented showing that one of the most important speech cues for enhancing auditory-visual speech recognition performance, voicing, is often the cue that benefits least from amplification.

Visual fatigue modeling for stereoscopic video shot based on camera motion

NASA Astrophysics Data System (ADS)

Shi, Guozhong; Sang, Xinzhu; Yu, Xunbo; Liu, Yangdong; Liu, Jing

2014-11-01

As three-dimensional television (3-DTV) and 3-D movie become popular, the discomfort of visual feeling limits further applications of 3D display technology. The cause of visual discomfort from stereoscopic video conflicts between accommodation and convergence, excessive binocular parallax, fast motion of objects and so on. Here, a novel method for evaluating visual fatigue is demonstrated. Influence factors including spatial structure, motion scale and comfortable zone are analyzed. According to the human visual system (HVS), people only need to converge their eyes to the specific objects for static cameras and background. Relative motion should be considered for different camera conditions determining different factor coefficients and weights. Compared with the traditional visual fatigue prediction model, a novel visual fatigue predicting model is presented. Visual fatigue degree is predicted using multiple linear regression method combining with the subjective evaluation. Consequently, each factor can reflect the characteristics of the scene, and the total visual fatigue score can be indicated according to the proposed algorithm. Compared with conventional algorithms which ignored the status of the camera, our approach exhibits reliable performance in terms of correlation with subjective test results.

Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma.

PubMed

Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E; Bollinger, Kathryn; Devos, Hannes

2017-01-01

Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal-Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups ( p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1-Q3) 3 (2-6.50) vs. 2 (0.50-2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2-6) vs. 1 (0.50-2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls ( p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma.

International Space Station Configuration Analysis and Integration

NASA Technical Reports Server (NTRS)

Anchondo, Rebekah

2016-01-01

Ambitious engineering projects, such as NASA's International Space Station (ISS), require dependable modeling, analysis, visualization, and robotics to ensure that complex mission strategies are carried out cost effectively, sustainably, and safely. Learn how Booz Allen Hamilton's Modeling, Analysis, Visualization, and Robotics Integration Center (MAVRIC) team performs engineering analysis of the ISS Configuration based primarily on the use of 3D CAD models. To support mission planning and execution, the team tracks the configuration of ISS and maintains configuration requirements to ensure operational goals are met. The MAVRIC team performs multi-disciplinary integration and trade studies to ensure future configurations meet stakeholder needs.

The Perspective Structure of Visual Space

PubMed Central

2015-01-01

Luneburg’s model has been the reference for experimental studies of visual space for almost seventy years. His claim for a curved visual space has been a source of inspiration for visual scientists as well as philosophers. The conclusion of many experimental studies has been that Luneburg’s model does not describe visual space in various tasks and conditions. Remarkably, no alternative model has been suggested. The current study explores perspective transformations of Euclidean space as a model for visual space. Computations show that the geometry of perspective spaces is considerably different from that of Euclidean space. Collinearity but not parallelism is preserved in perspective space and angles are not invariant under translation and rotation. Similar relationships have shown to be properties of visual space. Alley experiments performed early in the nineteenth century have been instrumental in hypothesizing curved visual spaces. Alleys were computed in perspective space and compared with reconstructed alleys of Blumenfeld. Parallel alleys were accurately described by perspective geometry. Accurate distance alleys were derived from parallel alleys by adjusting the interstimulus distances according to the size-distance invariance hypothesis. Agreement between computed and experimental alleys and accommodation of experimental results that rejected Luneburg’s model show that perspective space is an appropriate model for how we perceive orientations and angles. The model is also appropriate for perceived distance ratios between stimuli but fails to predict perceived distances. PMID:27648222

Memory-guided saccade processing in visual form agnosia (patient DF).

PubMed

Rossit, Stéphanie; Szymanek, Larissa; Butler, Stephen H; Harvey, Monika

2010-01-01

According to Milner and Goodale's model (The visual brain in action, Oxford University Press, Oxford, 2006) areas in the ventral visual stream mediate visual perception and oV-line actions, whilst regions in the dorsal visual stream mediate the on-line visual control of action. Strong evidence for this model comes from a patient (DF), who suffers from visual form agnosia after bilateral damage to the ventro-lateral occipital region, sparing V1. It has been reported that she is normal in immediate reaching and grasping, yet severely impaired when asked to perform delayed actions. Here we investigated whether this dissociation would extend to saccade execution. Neurophysiological studies and TMS work in humans have shown that the posterior parietal cortex (PPC), on the right in particular (supposedly spared in DF), is involved in the control of memory-guided saccades. Surprisingly though, we found that, just as reported for reaching and grasping, DF's saccadic accuracy was much reduced in the memory compared to the stimulus-guided condition. These data support the idea of a tight coupling of eye and hand movements and further suggest that dorsal stream structures may not be sufficient to drive memory-guided saccadic performance.

Effects of simulator motion and visual characteristics on rotorcraft handling qualities evaluations

NASA Technical Reports Server (NTRS)

Mitchell, David G.; Hart, Daniel C.

1993-01-01

The pilot's perceptions of aircraft handling qualities are influenced by a combination of the aircraft dynamics, the task, and the environment under which the evaluation is performed. When the evaluation is performed in a groundbased simulator, the characteristics of the simulation facility also come into play. Two studies were conducted on NASA Ames Research Center's Vertical Motion Simulator to determine the effects of simulator characteristics on perceived handling qualities. Most evaluations were conducted with a baseline set of rotorcraft dynamics, using a simple transfer-function model of an uncoupled helicopter, under different conditions of visual time delays and motion command washout filters. Differences in pilot opinion were found as the visual and motion parameters were changed, reflecting a change in the pilots' perceptions of handling qualities, rather than changes in the aircraft model itself. The results indicate a need for tailoring the motion washout dynamics to suit the task. Visual-delay data are inconclusive but suggest that it may be better to allow some time delay in the visual path to minimize the mismatch between visual and motion, rather than eliminate the visual delay entirely through lead compensation.

Dynamic visual attention: motion direction versus motion magnitude

NASA Astrophysics Data System (ADS)

Bur, A.; Wurtz, P.; Müri, R. M.; Hügli, H.

2008-02-01

Defined as an attentive process in the context of visual sequences, dynamic visual attention refers to the selection of the most informative parts of video sequence. This paper investigates the contribution of motion in dynamic visual attention, and specifically compares computer models designed with the motion component expressed either as the speed magnitude or as the speed vector. Several computer models, including static features (color, intensity and orientation) and motion features (magnitude and vector) are considered. Qualitative and quantitative evaluations are performed by comparing the computer model output with human saliency maps obtained experimentally from eye movement recordings. The model suitability is evaluated in various situations (synthetic and real sequences, acquired with fixed and moving camera perspective), showing advantages and inconveniences of each method as well as preferred domain of application.

Dissociations of the number and precision of visual short-term memory representations in change detection.

PubMed

Xie, Weizhen; Zhang, Weiwei

2017-11-01

The present study dissociated the number (i.e., quantity) and precision (i.e., quality) of visual short-term memory (STM) representations in change detection using receiver operating characteristic (ROC) and experimental manipulations. Across three experiments, participants performed both recognition and recall tests of visual STM using the change-detection task and the continuous color-wheel recall task, respectively. Experiment 1 demonstrated that the estimates of the number and precision of visual STM representations based on the ROC model of change-detection performance were robustly correlated with the corresponding estimates based on the mixture model of continuous-recall performance. Experiments 2 and 3 showed that the experimental manipulation of mnemonic precision using white-noise masking and the experimental manipulation of the number of encoded STM representations using consolidation masking produced selective effects on the corresponding measures of mnemonic precision and the number of encoded STM representations, respectively, in both change-detection and continuous-recall tasks. Altogether, using the individual-differences (Experiment 1) and experimental dissociation (Experiment 2 and 3) approaches, the present study demonstrated the some-or-none nature of visual STM representations across recall and recognition.

Performance Measurement, Visualization and Modeling of Parallel and Distributed Programs

NASA Technical Reports Server (NTRS)

Yan, Jerry C.; Sarukkai, Sekhar R.; Mehra, Pankaj; Lum, Henry, Jr. (Technical Monitor)

1994-01-01

This paper presents a methodology for debugging the performance of message-passing programs on both tightly coupled and loosely coupled distributed-memory machines. The AIMS (Automated Instrumentation and Monitoring System) toolkit, a suite of software tools for measurement and analysis of performance, is introduced and its application illustrated using several benchmark programs drawn from the field of computational fluid dynamics. AIMS includes (i) Xinstrument, a powerful source-code instrumentor, which supports both Fortran77 and C as well as a number of different message-passing libraries including Intel's NX Thinking Machines' CMMD, and PVM; (ii) Monitor, a library of timestamping and trace -collection routines that run on supercomputers (such as Intel's iPSC/860, Delta, and Paragon and Thinking Machines' CM5) as well as on networks of workstations (including Convex Cluster and SparcStations connected by a LAN); (iii) Visualization Kernel, a trace-animation facility that supports source-code clickback, simultaneous visualization of computation and communication patterns, as well as analysis of data movements; (iv) Statistics Kernel, an advanced profiling facility, that associates a variety of performance data with various syntactic components of a parallel program; (v) Index Kernel, a diagnostic tool that helps pinpoint performance bottlenecks through the use of abstract indices; (vi) Modeling Kernel, a facility for automated modeling of message-passing programs that supports both simulation -based and analytical approaches to performance prediction and scalability analysis; (vii) Intrusion Compensator, a utility for recovering true performance from observed performance by removing the overheads of monitoring and their effects on the communication pattern of the program; and (viii) Compatibility Tools, that convert AIMS-generated traces into formats used by other performance-visualization tools, such as ParaGraph, Pablo, and certain AVS/Explorer modules.

The Effect of Covert Modeling on Communication Apprehension, Communication Confidence, and Performance.

ERIC Educational Resources Information Center

Nimocks, Mittie J.; Bromley, Patricia L.; Parsons, Theron E.; Enright, Corinne S.; Gates, Elizabeth A.

This study examined the effect of covert modeling on communication apprehension, public speaking anxiety, and communication competence. Students identified as highly communication apprehensive received covert modeling, a technique in which one first observes a model doing a behavior, then visualizes oneself performing the behavior and obtaining a…

Advances and limitations of visual conditioning protocols in harnessed bees.

PubMed

Avarguès-Weber, Aurore; Mota, Theo

2016-10-01

Bees are excellent invertebrate models for studying visual learning and memory mechanisms, because of their sophisticated visual system and impressive cognitive capacities associated with a relatively simple brain. Visual learning in free-flying bees has been traditionally studied using an operant conditioning paradigm. This well-established protocol, however, can hardly be combined with invasive procedures for studying the neurobiological basis of visual learning. Different efforts have been made to develop protocols in which harnessed honey bees could associate visual cues with reinforcement, though learning performances remain poorer than those obtained with free-flying animals. Especially in the last decade, the intention of improving visual learning performances of harnessed bees led many authors to adopt distinct visual conditioning protocols, altering parameters like harnessing method, nature and duration of visual stimulation, number of trials, inter-trial intervals, among others. As a result, the literature provides data hardly comparable and sometimes contradictory. In the present review, we provide an extensive analysis of the literature available on visual conditioning of harnessed bees, with special emphasis on the comparison of diverse conditioning parameters adopted by different authors. Together with this comparative overview, we discuss how these diverse conditioning parameters could modulate visual learning performances of harnessed bees. Copyright © 2016 Elsevier Ltd. All rights reserved.

Visually induced analgesia in a deep tissue experimental pain model: A randomised crossover experiment.

PubMed

van Selm, M J; Gibson, W I; Travers, M J; Moseley, G L; Hince, D; Wand, B M

2018-04-20

Visualizing one's own painful body part appears to have an effect on reported pain intensity. Furthermore, it seems that manipulating the size of the viewed image can determine the direction and extent of this phenomenon. When visual distortion has been applied to clinical populations, the analgesic effects have been in opposition to those observed in some experimental pain models. To help resolve this problem, we explored the effect of visualisation and magnification of the visual image on reported pain using a delayed onset muscle soreness (DOMS) pain model. We induced DOMS in the quadriceps of 20 healthy volunteers. Forty-eight hours later, participants performed a series of painful contractions of the DOMS-affected muscle under four randomised conditions: (1) Viewing the injured thigh; (2) Viewing the contralateral thigh; (3) Viewing a neutral object; and (4) Viewing the injured thigh through magnifying glasses. For each condition, participants rated their pain intensity during a series of painful contractions. We observed that direct visualisation of the injured thigh had no effect on pain intensity when compared to viewing the contralateral thigh or neutral object. However, magnification of the DOMS-affected leg during the performance of painful contractions caused participants to report more pain than when viewing the injured thigh normally. These results further demonstrate that the effect of visualisation varies between different pain conditions. These results may have implications for the integration of visual feedback into clinical practice. We present delayed onset muscle soreness as a model for exploring visually induced analgesia. Our findings suggest that this phenomenon is expressed differently in exogenous and endogenous experimental pain models. Further exploration may offer a potential pathway for the integration of visual analgesia into the management of clinical pain. © 2018 European Pain Federation - EFIC®.

Cue Integration in Categorical Tasks: Insights from Audio-Visual Speech Perception

PubMed Central

Bejjanki, Vikranth Rao; Clayards, Meghan; Knill, David C.; Aslin, Richard N.

2011-01-01

Previous cue integration studies have examined continuous perceptual dimensions (e.g., size) and have shown that human cue integration is well described by a normative model in which cues are weighted in proportion to their sensory reliability, as estimated from single-cue performance. However, this normative model may not be applicable to categorical perceptual dimensions (e.g., phonemes). In tasks defined over categorical perceptual dimensions, optimal cue weights should depend not only on the sensory variance affecting the perception of each cue but also on the environmental variance inherent in each task-relevant category. Here, we present a computational and experimental investigation of cue integration in a categorical audio-visual (articulatory) speech perception task. Our results show that human performance during audio-visual phonemic labeling is qualitatively consistent with the behavior of a Bayes-optimal observer. Specifically, we show that the participants in our task are sensitive, on a trial-by-trial basis, to the sensory uncertainty associated with the auditory and visual cues, during phonemic categorization. In addition, we show that while sensory uncertainty is a significant factor in determining cue weights, it is not the only one and participants' performance is consistent with an optimal model in which environmental, within category variability also plays a role in determining cue weights. Furthermore, we show that in our task, the sensory variability affecting the visual modality during cue-combination is not well estimated from single-cue performance, but can be estimated from multi-cue performance. The findings and computational principles described here represent a principled first step towards characterizing the mechanisms underlying human cue integration in categorical tasks. PMID:21637344

Stimulus Dependence of Correlated Variability across Cortical Areas

PubMed Central

Cohen, Marlene R.

2016-01-01

The way that correlated trial-to-trial variability between pairs of neurons in the same brain area (termed spike count or noise correlation, rSC) depends on stimulus or task conditions can constrain models of cortical circuits and of the computations performed by networks of neurons (Cohen and Kohn, 2011). In visual cortex, rSC tends not to depend on stimulus properties (Kohn and Smith, 2005; Huang and Lisberger, 2009) but does depend on cognitive factors like visual attention (Cohen and Maunsell, 2009; Mitchell et al., 2009). However, neurons across visual areas respond to any visual stimulus or contribute to any perceptual decision, and the way that information from multiple areas is combined to guide perception is unknown. To gain insight into these issues, we recorded simultaneously from neurons in two areas of visual cortex (primary visual cortex, V1, and the middle temporal area, MT) while rhesus monkeys viewed different visual stimuli in different attention conditions. We found that correlations between neurons in different areas depend on stimulus and attention conditions in very different ways than do correlations within an area. Correlations across, but not within, areas depend on stimulus direction and the presence of a second stimulus, and attention has opposite effects on correlations within and across areas. This observed pattern of cross-area correlations is predicted by a normalization model where MT units sum V1 inputs that are passed through a divisive nonlinearity. Together, our results provide insight into how neurons in different areas interact and constrain models of the neural computations performed across cortical areas. SIGNIFICANCE STATEMENT Correlations in the responses of pairs of neurons within the same cortical area have been a subject of growing interest in systems neuroscience. However, correlated variability between different cortical areas is likely just as important. We recorded simultaneously from neurons in primary visual cortex and the middle temporal area while rhesus monkeys viewed different visual stimuli in different attention conditions. We found that correlations between neurons in different areas depend on stimulus and attention conditions in very different ways than do correlations within an area. The observed pattern of cross-area correlations was predicted by a simple normalization model. Our results provide insight into how neurons in different areas interact and constrain models of the neural computations performed across cortical areas. PMID:27413163

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences

PubMed Central

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns. PMID:26147887

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

PubMed

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Computational Model of Primary Visual Cortex Combining Visual Attention for Action Recognition

PubMed Central

Shu, Na; Gao, Zhiyong; Chen, Xiangan; Liu, Haihua

2015-01-01

Humans can easily understand other people’s actions through visual systems, while computers cannot. Therefore, a new bio-inspired computational model is proposed in this paper aiming for automatic action recognition. The model focuses on dynamic properties of neurons and neural networks in the primary visual cortex (V1), and simulates the procedure of information processing in V1, which consists of visual perception, visual attention and representation of human action. In our model, a family of the three-dimensional spatial-temporal correlative Gabor filters is used to model the dynamic properties of the classical receptive field of V1 simple cell tuned to different speeds and orientations in time for detection of spatiotemporal information from video sequences. Based on the inhibitory effect of stimuli outside the classical receptive field caused by lateral connections of spiking neuron networks in V1, we propose surround suppressive operator to further process spatiotemporal information. Visual attention model based on perceptual grouping is integrated into our model to filter and group different regions. Moreover, in order to represent the human action, we consider the characteristic of the neural code: mean motion map based on analysis of spike trains generated by spiking neurons. The experimental evaluation on some publicly available action datasets and comparison with the state-of-the-art approaches demonstrate the superior performance of the proposed model. PMID:26132270

On the Integration of Medium Wave Infrared Cameras for Vision-Based Navigation

DTIC Science & Technology

2015-03-01

SWIR Short Wave Infrared VisualSFM Visual Structure from Motion WPAFB Wright Patterson Air Force Base xi ON THE INTEGRATION OF MEDIUM WAVE INFRARED...Structure from Motion Visual Structure from Motion ( VisualSFM ) is an application that performs incremental SfM using images fed into it of a scene [20...too drastically in between frames. When this happens, VisualSFM will begin creating a new model with images that do not fit to the old one. These new

The role of visual imagery in the retention of information from sentences.

PubMed

Drose, G S; Allen, G L

1994-01-01

We conducted two experiments to evaluate a multiple-code model for sentence memory that posits both propositional and visual representational systems. Both sentences involved recognition memory. The results of Experiment 1 indicated that subjects' recognition memory for concrete sentences was superior to their recognition memory for abstract sentences. Instructions to use visual imagery to enhance recognition performance yielded no effects. Experiment 2 tested the prediction that interference by a visual task would differentially affect recognition memory for concrete sentences. Results showed the interference task to have had a detrimental effect on recognition memory for both concrete and abstract sentences. Overall, the evidence provided partial support for both a multiple-code model and a semantic integration model of sentence memory.

A Model for the Detection of Moving Targets in Visual Clutter Inspired by Insect Physiology

DTIC Science & Technology

2008-07-01

paper: SDW PS DCO. References 1. Wagner H (1986) Flight performance and visual control of flight of the free- flying housefly (Musca domestica L) 3...differences in the chasing behaviour of houseflies (musca). Biol Cybern 32: 239–241. 3. Land MF (1997) Visual acuity in insects. Annu Rev Entomol 42: 147

Pupil Influence on the Visual Outcomes of a New-Generation Multifocal Toric Intraocular Lens With a Surface-Embedded Near Segment.

PubMed

Wang, Mengmeng; Corpuz, Christine Carole C; Huseynova, Tukezban; Tomita, Minoru

2016-02-01

To evaluate the influences of preoperative pupil parameters on the visual outcomes of a new-generation multifocal toric intraocular lens (IOL) model with a surface-embedded near segment. In this prospective study, patients with cataract had phacoemulsification and implantation of Lentis Mplus toric LU-313 30TY IOLs (Oculentis GmbH, Berlin, Germany). The visual and optical outcomes were measured and compared preoperatively and postoperatively. The correlations between preoperative pupil parameters (diameter and decentration) and 3-month postoperative visual outcomes were evaluated using the Spearman's rank-order correlation coefficient (Rs) for the nonparametric data. A total of 27 eyes (16 patients) were enrolled into the current study. Statistically significant improvements in visual and refractive performances were found after the implantation of Lentis Mplus toric LU-313 30TY IOLs (P < .05). Statistically significant correlations were present between preoperative pupil diameters and postoperative visual acuities (Rs > 0; P < .05). Patients with a larger pupil always have better postoperative visual acuities. Meanwhile, there was no statistically significant correlation between pupil decentration and visual acuities (P > .05). Lentis Mplus toric LU-313 30TY IOLs provided excellent visual and optical performances during the 3-month follow-up. The preoperative pupil size is an important parameter when this toric multifocal IOL model is contemplated for surgery. Copyright 2016, SLACK Incorporated.

A qualitative inquiry into the effects of visualization on high school chemistry students' learning process of molecular structure

NASA Astrophysics Data System (ADS)

Deratzou, Susan

This research studies the process of high school chemistry students visualizing chemical structures and its role in learning chemical bonding and molecular structure. Minimal research exists with high school chemistry students and more research is necessary (Gabel & Sherwood, 1980; Seddon & Moore, 1986; Seddon, Tariq, & Dos Santos Veiga, 1984). Using visualization tests (Ekstrom, French, Harman, & Dermen, 1990a), a learning style inventory (Brown & Cooper, 1999), and observations through a case study design, this study found visual learners performed better, but needed more practice and training. Statistically, all five pre- and post-test visualization test comparisons were highly significant in the two-tailed t-test (p > .01). The research findings are: (1) Students who tested high in the Visual (Language and/or Numerical) and Tactile Learning Styles (and Social Learning) had an advantage. Students who learned the chemistry concepts more effectively were better at visualizing structures and using molecular models to enhance their knowledge. (2) Students showed improvement in learning after visualization practice. Training in visualization would improve students' visualization abilities and provide them with a way to think about these concepts. (3) Conceptualization of concepts indicated that visualizing ability was critical and that it could be acquired. Support for this finding was provided by pre- and post-Visualization Test data with a highly significant t-test. (4) Various molecular animation programs and websites were found to be effective. (5) Visualization and modeling of structures encompassed both two- and three-dimensional space. The Visualization Test findings suggested that the students performed better with basic rotation of structures as compared to two- and three-dimensional objects. (6) Data from observations suggest that teaching style was an important factor in student learning of molecular structure. (7) Students did learn the chemistry concepts. Based on the Visualization Test results, which showed that most of the students performed better on the post-test, the visualization experience and the abstract nature of the content allowed them to transfer some of their chemical understanding and practice to non-chemical structures. Finally, implications for teaching of chemistry, students learning chemistry, curriculum, and research for the field of chemical education were discussed.

Psychophysical and perceptual performance in a simulated-scotoma model of human eye injury

NASA Astrophysics Data System (ADS)

Brandeis, R.; Egoz, I.; Peri, D.; Sapiens, N.; Turetz, J.

2008-02-01

Macular scotomas, affecting visual functioning, characterize many eye and neurological diseases like AMD, diabetes mellitus, multiple sclerosis, and macular hole. In this work, foveal visual field defects were modeled, and their effects were evaluated on spatial contrast sensitivity and a task of stimulus detection and aiming. The modeled occluding scotomas, of different size, were superimposed on the stimuli presented on the computer display, and were stabilized on the retina using a mono Purkinje Eye-Tracker. Spatial contrast sensitivity was evaluated using square-wave grating stimuli, whose contrast thresholds were measured using the method of constant stimuli with "catch trials". The detection task consisted of a triple conjunctive visual search display of: size (in visual angle), contrast and background (simple, low-level features vs. complex, high-level features). Search/aiming accuracy as well as R.T. measures used for performance evaluation. Artificially generated scotomas suppressed spatial contrast sensitivity in a size dependent manner, similar to previous studies. Deprivation effect was dependent on spatial frequency, consistent with retinal inhomogeneity models. Stimulus detection time was slowed in complex background search situation more than in simple background. Detection speed was dependent on scotoma size and size of stimulus. In contrast, visually guided aiming was more sensitive to scotoma effect in simple background search situation than in complex background. Both stimulus aiming R.T. and accuracy (precision targeting) were impaired, as a function of scotoma size and size of stimulus. The data can be explained by models distinguishing between saliency-based, parallel and serial search processes, guiding visual attention, which are supported by underlying retinal as well as neural mechanisms.

Effect of Cognitive Demand on Functional Visual Field Performance in Senior Drivers with Glaucoma

PubMed Central

Gangeddula, Viswa; Ranchet, Maud; Akinwuntan, Abiodun E.; Bollinger, Kathryn; Devos, Hannes

2017-01-01

Purpose: To investigate the effect of cognitive demand on functional visual field performance in drivers with glaucoma. Method: This study included 20 drivers with open-angle glaucoma and 13 age- and sex-matched controls. Visual field performance was evaluated under different degrees of cognitive demand: a static visual field condition (C1), dynamic visual field condition (C2), and dynamic visual field condition with active driving (C3) using an interactive, desktop driving simulator. The number of correct responses (accuracy) and response times on the visual field task were compared between groups and between conditions using Kruskal–Wallis tests. General linear models were employed to compare cognitive workload, recorded in real-time through pupillometry, between groups and conditions. Results: Adding cognitive demand (C2 and C3) to the static visual field test (C1) adversely affected accuracy and response times, in both groups (p < 0.05). However, drivers with glaucoma performed worse than did control drivers when the static condition changed to a dynamic condition [C2 vs. C1 accuracy; glaucoma: median difference (Q1–Q3) 3 (2–6.50) vs. controls: 2 (0.50–2.50); p = 0.05] and to a dynamic condition with active driving [C3 vs. C1 accuracy; glaucoma: 2 (2–6) vs. controls: 1 (0.50–2); p = 0.02]. Overall, drivers with glaucoma exhibited greater cognitive workload than controls (p = 0.02). Conclusion: Cognitive demand disproportionately affects functional visual field performance in drivers with glaucoma. Our results may inform the development of a performance-based visual field test for drivers with glaucoma. PMID:28912712

The Role of Teamwork in the Analysis of Big Data: A Study of Visual Analytics and Box Office Prediction.

PubMed

Buchanan, Verica; Lu, Yafeng; McNeese, Nathan; Steptoe, Michael; Maciejewski, Ross; Cooke, Nancy

2017-03-01

Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models. Although studies have explored the role of single analysts in the visual analytics pipeline, little work has explored the role of teamwork and visual analytics in the analysis of big data. In this article, we present an experiment integrating statistical models, visual analytics techniques, and user experiments to study the role of teamwork in predictive analytics. We frame our experiment around the analysis of social media data for box office prediction problems and compare the prediction performance of teams, groups, and individuals. Our results indicate that a team's performance is mediated by the team's characteristics such as openness of individual members to others' positions and the type of planning that goes into the team's analysis. These findings have important implications for how organizations should create teams in order to make effective use of information from their analytic models.

The development and discussion of computerized visual perception assessment tool for Chinese characters structures - Concurrent estimation of the overall ability and the domain ability in item response theory approach.

PubMed

Wu, Huey-Min; Lin, Chin-Kai; Yang, Yu-Mao; Kuo, Bor-Chen

2014-11-12

Visual perception is the fundamental skill required for a child to recognize words, and to read and write. There was no visual perception assessment tool developed for preschool children based on Chinese characters in Taiwan. The purposes were to develop the computerized visual perception assessment tool for Chinese Characters Structures and to explore the psychometrical characteristic of assessment tool. This study adopted purposive sampling. The study evaluated 551 kindergarten-age children (293 boys, 258 girls) ranging from 46 to 81 months of age. The test instrument used in this study consisted of three subtests and 58 items, including tests of basic strokes, single-component characters, and compound characters. Based on the results of model fit analysis, the higher-order item response theory was used to estimate the performance in visual perception, basic strokes, single-component characters, and compound characters simultaneously. Analyses of variance were used to detect significant difference in age groups and gender groups. The difficulty of identifying items in a visual perception test ranged from -2 to 1. The visual perception ability of 4- to 6-year-old children ranged from -1.66 to 2.19. Gender did not have significant effects on performance. However, there were significant differences among the different age groups. The performance of 6-year-olds was better than that of 5-year-olds, which was better than that of 4-year-olds. This study obtained detailed diagnostic scores by using a higher-order item response theory model to understand the visual perception of basic strokes, single-component characters, and compound characters. Further statistical analysis showed that, for basic strokes and compound characters, girls performed better than did boys; there also were differences within each age group. For single-component characters, there was no difference in performance between boys and girls. However, again the performance of 6-year-olds was better than that of 4-year-olds, but there were no statistical differences between the performance of 5-year-olds and 6-year-olds. Results of tests with basic strokes, single-component characters and compound characters tests had good reliability and validity. Therefore, it can be apply to diagnose the problem of visual perception at preschool. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cardinal rules: Visual orientation perception reflects knowledge of environmental statistics

PubMed Central

Girshick, Ahna R.; Landy, Michael S.; Simoncelli, Eero P.

2011-01-01

Humans are remarkably good at performing visual tasks, but experimental measurements reveal substantial biases in the perception of basic visual attributes. An appealing hypothesis is that these biases arise through a process of statistical inference, in which information from noisy measurements is fused with a probabilistic model of the environment. But such inference is optimal only if the observer’s internal model matches the environment. Here, we provide evidence that this is the case. We measured performance in an orientation-estimation task, demonstrating the well-known fact that orientation judgements are more accurate at cardinal (horizontal and vertical) orientations, along with a new observation that judgements made under conditions of uncertainty are strongly biased toward cardinal orientations. We estimate observers’ internal models for orientation and find that they match the local orientation distribution measured in photographs. We also show how a neural population could embed probabilistic information responsible for such biases. PMID:21642976

A Neurobehavioral Model of Flexible Spatial Language Behaviors

PubMed Central

Lipinski, John; Schneegans, Sebastian; Sandamirskaya, Yulia; Spencer, John P.; Schöner, Gregor

2012-01-01

We propose a neural dynamic model that specifies how low-level visual processes can be integrated with higher level cognition to achieve flexible spatial language behaviors. This model uses real-word visual input that is linked to relational spatial descriptions through a neural mechanism for reference frame transformations. We demonstrate that the system can extract spatial relations from visual scenes, select items based on relational spatial descriptions, and perform reference object selection in a single unified architecture. We further show that the performance of the system is consistent with behavioral data in humans by simulating results from 2 independent empirical studies, 1 spatial term rating task and 1 study of reference object selection behavior. The architecture we present thereby achieves a high degree of task flexibility under realistic stimulus conditions. At the same time, it also provides a detailed neural grounding for complex behavioral and cognitive processes. PMID:21517224

The Impact of Semantic Relevance and Heterogeneity of Pictorial Stimuli on Individual Brainstorming: An Extension of the SIAM Model

ERIC Educational Resources Information Center

Guo, Jing; McLeod, Poppy Lauretta

2014-01-01

Drawing upon the Search for Ideas in Associative Memory (SIAM) model as the theoretical framework, the impact of heterogeneity and topic relevance of visual stimuli on ideation performance was examined. Results from a laboratory experiment showed that visual stimuli increased productivity and diversity of idea generation, that relevance to the…

The marmoset monkey as a model for visual neuroscience

PubMed Central

Mitchell, Jude F.; Leopold, David A.

2015-01-01

The common marmoset (Callithrix jacchus) has been valuable as a primate model in biomedical research. Interest in this species has grown recently, in part due to the successful demonstration of transgenic marmosets. Here we examine the prospects of the marmoset model for visual neuroscience research, adopting a comparative framework to place the marmoset within a broader evolutionary context. The marmoset’s small brain bears most of the organizational features of other primates, and its smooth surface offers practical advantages over the macaque for areal mapping, laminar electrode penetration, and two-photon and optical imaging. Behaviorally, marmosets are more limited at performing regimented psychophysical tasks, but do readily accept the head restraint that is necessary for accurate eye tracking and neurophysiology, and can perform simple discriminations. Their natural gaze behavior closely resembles that of other primates, with a tendency to focus on objects of social interest including faces. Their immaturity at birth and routine twinning also makes them ideal for the study of postnatal visual development. These experimental factors, together with the theoretical advantages inherent in comparing anatomy, physiology, and behavior across related species, make the marmoset an excellent model for visual neuroscience. PMID:25683292

Integrating visual learning within a model-based ATR system

NASA Astrophysics Data System (ADS)

Carlotto, Mark; Nebrich, Mark

2017-05-01

Automatic target recognition (ATR) systems, like human photo-interpreters, rely on a variety of visual information for detecting, classifying, and identifying manmade objects in aerial imagery. We describe the integration of a visual learning component into the Image Data Conditioner (IDC) for target/clutter and other visual classification tasks. The component is based on an implementation of a model of the visual cortex developed by Serre, Wolf, and Poggio. Visual learning in an ATR context requires the ability to recognize objects independent of location, scale, and rotation. Our method uses IDC to extract, rotate, and scale image chips at candidate target locations. A bootstrap learning method effectively extends the operation of the classifier beyond the training set and provides a measure of confidence. We show how the classifier can be used to learn other features that are difficult to compute from imagery such as target direction, and to assess the performance of the visual learning process itself.

Improved Discrimination of Visual Stimuli Following Repetitive Transcranial Magnetic Stimulation

PubMed Central

Waterston, Michael L.; Pack, Christopher C.

2010-01-01

Background Repetitive transcranial magnetic stimulation (rTMS) at certain frequencies increases thresholds for motor-evoked potentials and phosphenes following stimulation of cortex. Consequently rTMS is often assumed to introduce a “virtual lesion” in stimulated brain regions, with correspondingly diminished behavioral performance. Methodology/Principal Findings Here we investigated the effects of rTMS to visual cortex on subjects' ability to perform visual psychophysical tasks. Contrary to expectations of a visual deficit, we find that rTMS often improves the discrimination of visual features. For coarse orientation tasks, discrimination of a static stimulus improved consistently following theta-burst stimulation of the occipital lobe. Using a reaction-time task, we found that these improvements occurred throughout the visual field and lasted beyond one hour post-rTMS. Low-frequency (1 Hz) stimulation yielded similar improvements. In contrast, we did not find consistent effects of rTMS on performance in a fine orientation discrimination task. Conclusions/Significance Overall our results suggest that rTMS generally improves or has no effect on visual acuity, with the nature of the effect depending on the type of stimulation and the task. We interpret our results in the context of an ideal-observer model of visual perception. PMID:20442776

A Pervasive Parallel Processing Framework for Data Visualization and Analysis at Extreme Scale

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ma, Kwan-Liu

Most of today’s visualization libraries and applications are based off of what is known today as the visualization pipeline. In the visualization pipeline model, algorithms are encapsulated as “filtering” components with inputs and outputs. These components can be combined by connecting the outputs of one filter to the inputs of another filter. The visualization pipeline model is popular because it provides a convenient abstraction that allows users to combine algorithms in powerful ways. Unfortunately, the visualization pipeline cannot run effectively on exascale computers. Experts agree that the exascale machine will comprise processors that contain many cores. Furthermore, physical limitations willmore » prevent data movement in and out of the chip (that is, between main memory and the processing cores) from keeping pace with improvements in overall compute performance. To use these processors to their fullest capability, it is essential to carefully consider memory access. This is where the visualization pipeline fails. Each filtering component in the visualization library is expected to take a data set in its entirety, perform some computation across all of the elements, and output the complete results. The process of iterating over all elements must be repeated in each filter, which is one of the worst possible ways to traverse memory when trying to maximize the number of executions per memory access. This project investigates a new type of visualization framework that exhibits a pervasive parallelism necessary to run on exascale machines. Our framework achieves this by defining algorithms in terms of functors, which are localized, stateless operations. Functors can be composited in much the same way as filters in the visualization pipeline. But, functors’ design allows them to be concurrently running on massive amounts of lightweight threads. Only with such fine-grained parallelism can we hope to fill the billions of threads we expect will be necessary for efficient computation on an exascale computer. This project concludes with a functional prototype containing pervasively parallel algorithms that perform demonstratively well on many-core processors. These algorithms are fundamental for performing data analysis and visualization at extreme scale.« less

Motor-cognitive dual-task performance: effects of a concurrent motor task on distinct components of visual processing capacity.

PubMed

Künstler, E C S; Finke, K; Günther, A; Klingner, C; Witte, O; Bublak, P

2018-01-01

Dual tasking, or the simultaneous execution of two continuous tasks, is frequently associated with a performance decline that can be explained within a capacity sharing framework. In this study, we assessed the effects of a concurrent motor task on the efficiency of visual information uptake based on the 'theory of visual attention' (TVA). TVA provides parameter estimates reflecting distinct components of visual processing capacity: perceptual threshold, visual processing speed, and visual short-term memory (VSTM) storage capacity. Moreover, goodness-of-fit values and bootstrapping estimates were derived to test whether the TVA-model is validly applicable also under dual task conditions, and whether the robustness of parameter estimates is comparable in single- and dual-task conditions. 24 subjects of middle to higher age performed a continuous tapping task, and a visual processing task (whole report of briefly presented letter arrays) under both single- and dual-task conditions. Results suggest a decline of both visual processing capacity and VSTM storage capacity under dual-task conditions, while the perceptual threshold remained unaffected by a concurrent motor task. In addition, goodness-of-fit values and bootstrapping estimates support the notion that participants processed the visual task in a qualitatively comparable, although quantitatively less efficient way under dual-task conditions. The results support a capacity sharing account of motor-cognitive dual tasking and suggest that even performing a relatively simple motor task relies on central attentional capacity that is necessary for efficient visual information uptake.

Use of Linear Perspective Scene Cues in a Simulated Height Regulation Task

NASA Technical Reports Server (NTRS)

Levison, W. H.; Warren, R.

1984-01-01

As part of a long-term effort to quantify the effects of visual scene cuing and non-visual motion cuing in flight simulators, an experimental study of the pilot's use of linear perspective cues in a simulated height-regulation task was conducted. Six test subjects performed a fixed-base tracking task with a visual display consisting of a simulated horizon and a perspective view of a straight, infinitely-long roadway of constant width. Experimental parameters were (1) the central angle formed by the roadway perspective and (2) the display gain. The subject controlled only the pitch/height axis; airspeed, bank angle, and lateral track were fixed in the simulation. The average RMS height error score for the least effective display configuration was about 25% greater than the score for the most effective configuration. Overall, larger and more highly significant effects were observed for the pitch and control scores. Model analysis was performed with the optimal control pilot model to characterize the pilot's use of visual scene cues, with the goal of obtaining a consistent set of independent model parameters to account for display effects.

Global motion compensated visual attention-based video watermarking

NASA Astrophysics Data System (ADS)

Oakes, Matthew; Bhowmik, Deepayan; Abhayaratne, Charith

2016-11-01

Imperceptibility and robustness are two key but complementary requirements of any watermarking algorithm. Low-strength watermarking yields high imperceptibility but exhibits poor robustness. High-strength watermarking schemes achieve good robustness but often suffer from embedding distortions resulting in poor visual quality in host media. This paper proposes a unique video watermarking algorithm that offers a fine balance between imperceptibility and robustness using motion compensated wavelet-based visual attention model (VAM). The proposed VAM includes spatial cues for visual saliency as well as temporal cues. The spatial modeling uses the spatial wavelet coefficients while the temporal modeling accounts for both local and global motion to arrive at the spatiotemporal VAM for video. The model is then used to develop a video watermarking algorithm, where a two-level watermarking weighting parameter map is generated from the VAM saliency maps using the saliency model and data are embedded into the host image according to the visual attentiveness of each region. By avoiding higher strength watermarking in the visually attentive region, the resulting watermarked video achieves high perceived visual quality while preserving high robustness. The proposed VAM outperforms the state-of-the-art video visual attention methods in joint saliency detection and low computational complexity performance. For the same embedding distortion, the proposed visual attention-based watermarking achieves up to 39% (nonblind) and 22% (blind) improvement in robustness against H.264/AVC compression, compared to existing watermarking methodology that does not use the VAM. The proposed visual attention-based video watermarking results in visual quality similar to that of low-strength watermarking and a robustness similar to those of high-strength watermarking.

Effect of verbal instructions and image size on visual search strategies in basketball free throw shooting.

PubMed

Al-Abood, Saleh A; Bennett, Simon J; Hernandez, Francisco Moreno; Ashford, Derek; Davids, Keith

2002-03-01

We assessed the effects on basketball free throw performance of two types of verbal directions with an external attentional focus. Novices (n = 16) were pre-tested on free throw performance and assigned to two groups of similar ability (n = 8 in each). Both groups received verbal instructions with an external focus on either movement dynamics (movement form) or movement effects (e.g. ball trajectory relative to basket). The participants also observed a skilled model performing the task on either a small or large screen monitor, to ascertain the effects of visual presentation mode on task performance. After observation of six videotaped trials, all participants were given a post-test. Visual search patterns were monitored during observation and cross-referenced with performance on the pre- and post-test. Group effects were noted for verbal instructions and image size on visual search strategies and free throw performance. The 'movement effects' group saw a significant improvement in outcome scores between the pre-test and post-test. These results supported evidence that this group spent more viewing time on information outside the body than the 'movement dynamics' group. Image size affected both groups equally with more fixations of shorter duration when viewing the small screen. The results support the benefits of instructions when observing a model with an external focus on movement effects, not dynamics.

The effect of observational learning on students' performance, processes, and motivation in two creative domains.

PubMed

Groenendijk, Talita; Janssen, Tanja; Rijlaarsdam, Gert; van den Bergh, Huub

2013-03-01

Previous research has shown that observation can be effective for learning in various domains, for example, argumentative writing and mathematics. The question in this paper is whether observational learning can also be beneficial when learning to perform creative tasks in visual and verbal arts. We hypothesized that observation has a positive effect on performance, process, and motivation. We expected similarity in competence between the model and the observer to influence the effectiveness of observation. Sample.  A total of 131 Dutch students (10(th) grade, 15 years old) participated. Two experiments were carried out (one for visual and one for verbal arts). Participants were randomly assigned to one of three conditions; two observational learning conditions and a control condition (learning by practising). The observational learning conditions differed in instructional focus (on the weaker or the more competent model of a pair to be observed). We found positive effects of observation on creative products, creative processes, and motivation in the visual domain. In the verbal domain, observation seemed to affect the creative process, but not the other variables. The model similarity hypothesis was not confirmed. Results suggest that observation may foster learning in creative domains, especially in the visual arts. © 2011 The British Psychological Society.

An ideal observer analysis of visual working memory.

PubMed

Sims, Chris R; Jacobs, Robert A; Knill, David C

2012-10-01

Limits in visual working memory (VWM) strongly constrain human performance across many tasks. However, the nature of these limits is not well understood. In this article we develop an ideal observer analysis of human VWM by deriving the expected behavior of an optimally performing but limited-capacity memory system. This analysis is framed around rate-distortion theory, a branch of information theory that provides optimal bounds on the accuracy of information transmission subject to a fixed information capacity. The result of the ideal observer analysis is a theoretical framework that provides a task-independent and quantitative definition of visual memory capacity and yields novel predictions regarding human performance. These predictions are subsequently evaluated and confirmed in 2 empirical studies. Further, the framework is general enough to allow the specification and testing of alternative models of visual memory (e.g., how capacity is distributed across multiple items). We demonstrate that a simple model developed on the basis of the ideal observer analysis-one that allows variability in the number of stored memory representations but does not assume the presence of a fixed item limit-provides an excellent account of the empirical data and further offers a principled reinterpretation of existing models of VWM. PsycINFO Database Record (c) 2012 APA, all rights reserved.

Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow.

PubMed

Wongsuphasawat, Kanit; Smilkov, Daniel; Wexler, James; Wilson, Jimbo; Mane, Dandelion; Fritz, Doug; Krishnan, Dilip; Viegas, Fernanda B; Wattenberg, Martin

2018-01-01

We present a design study of the TensorFlow Graph Visualizer, part of the TensorFlow machine intelligence platform. This tool helps users understand complex machine learning architectures by visualizing their underlying dataflow graphs. The tool works by applying a series of graph transformations that enable standard layout techniques to produce a legible interactive diagram. To declutter the graph, we decouple non-critical nodes from the layout. To provide an overview, we build a clustered graph using the hierarchical structure annotated in the source code. To support exploration of nested structure on demand, we perform edge bundling to enable stable and responsive cluster expansion. Finally, we detect and highlight repeated structures to emphasize a model's modular composition. To demonstrate the utility of the visualizer, we describe example usage scenarios and report user feedback. Overall, users find the visualizer useful for understanding, debugging, and sharing the structures of their models.

The effect of amblyopia on fine motor skills in children.

PubMed

Webber, Ann L; Wood, Joanne M; Gole, Glen A; Brown, Brian

2008-02-01

In an investigation of the functional impact of amblyopia in children, the fine motor skills of amblyopes and age-matched control subjects were compared. The influence of visual factors that might predict any decrement in fine motor skills was also explored. Vision and fine motor skills were tested in a group of children (n = 82; mean age, 8.2 +/- 1.7 [SD] years) with amblyopia of different causes (infantile esotropia, n = 17; acquired strabismus, n = 28; anisometropia, n = 15; mixed, n = 13; and deprivation n = 9), and age-matched control children (n = 37; age 8.3 +/- 1.3 years). Visual motor control (VMC) and upper limb speed and dexterity (ULSD) items of the Bruininks-Oseretsky Test of Motor Proficiency were assessed, and logMAR visual acuity (VA) and Randot stereopsis were measured. Multiple regression models were used to identify the visual determinants of fine motor skills performance. Amblyopes performed significantly poorer than control subjects on 9 of 16 fine motor skills subitems and for the overall age-standardized scores for both VMC and ULSD items (P < 0.05). The effects were most evident on timed tasks. The etiology of amblyopia and level of binocular function significantly affected fine motor skill performance on both items; however, when examined in a multiple regression model that took into account the intercorrelation between visual characteristics, poorer fine motor skills performance was associated with strabismus (F(1,75) = 5.428; P = 0.022), but not with the level of binocular function, refractive error, or visual acuity in either eye. Fine motor skills were reduced in children with amblyopia, particularly those with strabismus, compared with control subjects. The deficits in motor performance were greatest on manual dexterity tasks requiring speed and accuracy.

A web platform for integrated surface water - groundwater modeling and data management

NASA Astrophysics Data System (ADS)

Fatkhutdinov, Aybulat; Stefan, Catalin; Junghanns, Ralf

2016-04-01

Model-based decision support systems are considered to be reliable and time-efficient tools for resources management in various hydrology related fields. However, searching and acquisition of the required data, preparation of the data sets for simulations as well as post-processing, visualization and publishing of the simulations results often requires significantly more work and time than performing the modeling itself. The purpose of the developed software is to combine data storage facilities, data processing instruments and modeling tools in a single platform which potentially can reduce time required for performing simulations, hence decision making. The system is developed within the INOWAS (Innovative Web Based Decision Support System for Water Sustainability under a Changing Climate) project. The platform integrates spatially distributed catchment scale rainfall - runoff, infiltration and groundwater flow models with data storage, processing and visualization tools. The concept is implemented in a form of a web-GIS application and is build based on free and open source components, including the PostgreSQL database management system, Python programming language for modeling purposes, Mapserver for visualization and publishing the data, Openlayers for building the user interface and others. Configuration of the system allows performing data input, storage, pre- and post-processing and visualization in a single not disturbed workflow. In addition, realization of the decision support system in the form of a web service provides an opportunity to easily retrieve and share data sets as well as results of simulations over the internet, which gives significant advantages for collaborative work on the projects and is able to significantly increase usability of the decision support system.

More is still not better: testing the perturbation model of temporal reference memory across different modalities and tasks.

PubMed

Ogden, Ruth S; Jones, Luke A

2009-05-01

The ability of the perturbation model (Jones & Wearden, 2003) to account for reference memory function in a visual temporal generalization task and auditory and visual reproduction tasks was examined. In all tasks the number of presentations of the standard was manipulated (1, 3, or 5), and its effect on performance was compared. In visual temporal generalization the number of presentations of the standard did not affect the number of times the standard was correctly identified, nor did it affect the overall temporal generalization gradient. In auditory reproduction there was no effect of the number of times the standard was presented on mean reproductions. In visual reproduction mean reproductions were shorter when the standard was only presented once; however, this effect was reduced when a visual cue was provided before the first presentation of the standard. Whilst the results of all experiments are best accounted for by the perturbation model there appears to be some attentional benefit to multiple presentations of the standard in visual reproduction.

Encoding color information for visual tracking: Algorithms and benchmark.

PubMed

Liang, Pengpeng; Blasch, Erik; Ling, Haibin

2015-12-01

While color information is known to provide rich discriminative clues for visual inference, most modern visual trackers limit themselves to the grayscale realm. Despite recent efforts to integrate color in tracking, there is a lack of comprehensive understanding of the role color information can play. In this paper, we attack this problem by conducting a systematic study from both the algorithm and benchmark perspectives. On the algorithm side, we comprehensively encode 10 chromatic models into 16 carefully selected state-of-the-art visual trackers. On the benchmark side, we compile a large set of 128 color sequences with ground truth and challenge factor annotations (e.g., occlusion). A thorough evaluation is conducted by running all the color-encoded trackers, together with two recently proposed color trackers. A further validation is conducted on an RGBD tracking benchmark. The results clearly show the benefit of encoding color information for tracking. We also perform detailed analysis on several issues, including the behavior of various combinations between color model and visual tracker, the degree of difficulty of each sequence for tracking, and how different challenge factors affect the tracking performance. We expect the study to provide the guidance, motivation, and benchmark for future work on encoding color in visual tracking.

Hydrograph matching method for measuring model performance

NASA Astrophysics Data System (ADS)

Ewen, John

2011-09-01

SummaryDespite all the progress made over the years on developing automatic methods for analysing hydrographs and measuring the performance of rainfall-runoff models, automatic methods cannot yet match the power and flexibility of the human eye and brain. Very simple approaches are therefore being developed that mimic the way hydrologists inspect and interpret hydrographs, including the way that patterns are recognised, links are made by eye, and hydrological responses and errors are studied and remembered. In this paper, a dynamic programming algorithm originally designed for use in data mining is customised for use with hydrographs. It generates sets of "rays" that are analogous to the visual links made by the hydrologist's eye when linking features or times in one hydrograph to the corresponding features or times in another hydrograph. One outcome from this work is a new family of performance measures called "visual" performance measures. These can measure differences in amplitude and timing, including the timing errors between simulated and observed hydrographs in model calibration. To demonstrate this, two visual performance measures, one based on the Nash-Sutcliffe Efficiency and the other on the mean absolute error, are used in a total of 34 split-sample calibration-validation tests for two rainfall-runoff models applied to the Hodder catchment, northwest England. The customised algorithm, called the Hydrograph Matching Algorithm, is very simple to apply; it is given in a few lines of pseudocode.

Evidence that primary visual cortex is required for image, orientation, and motion discrimination by rats.

PubMed

Petruno, Sarah K; Clark, Robert E; Reinagel, Pamela

2013-01-01

The pigmented Long-Evans rat has proven to be an excellent subject for studying visually guided behavior including quantitative visual psychophysics. This observation, together with its experimental accessibility and its close homology to the mouse, has made it an attractive model system in which to dissect the thalamic and cortical circuits underlying visual perception. Given that visually guided behavior in the absence of primary visual cortex has been described in the literature, however, it is an empirical question whether specific visual behaviors will depend on primary visual cortex in the rat. Here we tested the effects of cortical lesions on performance of two-alternative forced-choice visual discriminations by Long-Evans rats. We present data from one highly informative subject that learned several visual tasks and then received a bilateral lesion ablating >90% of primary visual cortex. After the lesion, this subject had a profound and persistent deficit in complex image discrimination, orientation discrimination, and full-field optic flow motion discrimination, compared with both pre-lesion performance and sham-lesion controls. Performance was intact, however, on another visual two-alternative forced-choice task that required approaching a salient visual target. A second highly informative subject learned several visual tasks prior to receiving a lesion ablating >90% of medial extrastriate cortex. This subject showed no impairment on any of the four task categories. Taken together, our data provide evidence that these image, orientation, and motion discrimination tasks require primary visual cortex in the Long-Evans rat, whereas approaching a salient visual target does not.

FastDart : a fast, accurate and friendly version of DART code.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rest, J.; Taboada, H.

2000-11-08

A new enhanced, visual version of DART code is presented. DART is a mechanistic model based code, developed for the performance calculation and assessment of aluminum dispersion fuel. Major issues of this new version are the development of a new, time saving calculation routine, able to be run on PC, a friendly visual input interface and a plotting facility. This version, available for silicide and U-Mo fuels,adds to the classical accuracy of DART models for fuel performance prediction, a faster execution and visual interfaces. It is part of a collaboration agreement between ANL and CNEA in the area of Lowmore » Enriched Uranium Advanced Fuels, held by the Implementation Arrangement for Technical Exchange and Cooperation in the Area of Peaceful Uses of Nuclear Energy.« less

Local Homing Navigation Based on the Moment Model for Landmark Distribution and Features

PubMed Central

Lee, Changmin; Kim, DaeEun

2017-01-01

For local homing navigation, an agent is supposed to return home based on the surrounding environmental information. According to the snapshot model, the home snapshot and the current view are compared to determine the homing direction. In this paper, we propose a novel homing navigation method using the moment model. The suggested moment model also follows the snapshot theory to compare the home snapshot and the current view, but the moment model defines a moment of landmark inertia as the sum of the product of the feature of the landmark particle with the square of its distance. The method thus uses range values of landmarks in the surrounding view and the visual features. The center of the moment can be estimated as the reference point, which is the unique convergence point in the moment potential from any view. The homing vector can easily be extracted from the centers of the moment measured at the current position and the home location. The method effectively guides homing direction in real environments, as well as in the simulation environment. In this paper, we take a holistic approach to use all pixels in the panoramic image as landmarks and use the RGB color intensity for the visual features in the moment model in which a set of three moment functions is encoded to determine the homing vector. We also tested visual homing or the moment model with only visual features, but the suggested moment model with both the visual feature and the landmark distance shows superior performance. We demonstrate homing performance with various methods classified by the status of the feature, the distance and the coordinate alignment. PMID:29149043

Theory of Visual Attention (TVA) applied to mice in the 5-choice serial reaction time task.

PubMed

Fitzpatrick, C M; Caballero-Puntiverio, M; Gether, U; Habekost, T; Bundesen, C; Vangkilde, S; Woldbye, D P D; Andreasen, J T; Petersen, A

2017-03-01

The 5-choice serial reaction time task (5-CSRTT) is widely used to measure rodent attentional functions. In humans, many attention studies in healthy and clinical populations have used testing based on Bundesen's Theory of Visual Attention (TVA) to estimate visual processing speeds and other parameters of attentional capacity. We aimed to bridge these research fields by modifying the 5-CSRTT's design and by mathematically modelling data to derive attentional parameters analogous to human TVA-based measures. C57BL/6 mice were tested in two 1-h sessions on consecutive days with a version of the 5-CSRTT where stimulus duration (SD) probe length was varied based on information from previous TVA studies. Thereafter, a scopolamine hydrobromide (HBr; 0.125 or 0.25 mg/kg) pharmacological challenge was undertaken, using a Latin square design. Mean score values were modelled using a new three-parameter version of TVA to obtain estimates of visual processing speeds, visual thresholds and motor response baselines in each mouse. The parameter estimates for each animal were reliable across sessions, showing that the data were stable enough to support analysis on an individual level. Scopolamine HBr dose-dependently reduced 5-CSRTT attentional performance while also increasing reward collection latency at the highest dose. Upon TVA modelling, scopolamine HBr significantly reduced visual processing speed at both doses, while having less pronounced effects on visual thresholds and motor response baselines. This study shows for the first time how 5-CSRTT performance in mice can be mathematically modelled to yield estimates of attentional capacity that are directly comparable to estimates from human studies.

A localized model of spatial cognition in chemistry

NASA Astrophysics Data System (ADS)

Stieff, Mike

This dissertation challenges the assumption that spatial cognition, particularly visualization, is the key component to problem solving in chemistry. In contrast to this assumption, I posit a localized, or task-specific, model of spatial cognition in chemistry problem solving to locate the exact tasks in a traditional organic chemistry curriculum that require students to use visualization strategies to problem solve. Instead of assuming that visualization is required for most chemistry tasks simply because chemistry concerns invisible three-dimensional entities, I instead use the framework of the localized model to identify how students do and do not make use of visualization strategies on a wide variety of assessment tasks regardless of each task's explicit demand for spatial cognition. I establish the dimensions of the localized model with five studies. First, I designed two novel psychometrics to reveal how students selectively use visualization strategies to interpret and analyze molecular structures. The third study comprised a document analysis of the organic chemistry assessments that empirically determined only 12% of these tasks explicitly require visualization. The fourth study concerned a series of correlation analyses between measures of visuo-spatial ability and chemistry performance to clarify the impact of individual differences. Finally, I performed a series of micro-genetic analyses of student problem solving that confirmed the earlier findings and revealed students prefer to visualize molecules from alternative perspectives without using mental rotation. The results of each study reveal that occurrences of sophisticated spatial cognition are relatively infrequent in chemistry, despite instructors' ostensible emphasis on the visualization of three-dimensional structures. To the contrary, students eschew visualization strategies and instead rely on the use of molecular diagrams to scaffold spatial cognition. Visualization does play a key role, however, in problem solving on a select group of chemistry tasks that require students to translate molecular representations or fundamentally alter the morphology of a molecule. Ultimately, this dissertation calls into question the assumption that individual differences in visuo-spatial ability play a critical role in determining who succeeds in chemistry. The results of this work establish a foundation for defining the precise manner in which visualization tools can best support problem solving.

An analysis of mathematical connection ability based on student learning style on visualization auditory kinesthetic (VAK) learning model with self-assessment

NASA Astrophysics Data System (ADS)

Apipah, S.; Kartono; Isnarto

2018-03-01

This research aims to analyze the quality of VAK learning with self-assessment toward the ability of mathematical connection performed by students and to analyze students’ mathematical connection ability based on learning styles in VAK learning model with self-assessment. This research applies mixed method type with concurrent embedded design. The subject of this research consists of VIII grade students from State Junior High School 9 Semarang who apply visual learning style, auditory learning style, and kinesthetic learning style. The data of learning style is collected by using questionnaires, the data of mathematical connection ability is collected by performing tests, and the data of self-assessment is collected by using assessment sheets. The quality of learning is qualitatively valued from planning stage, realization stage, and valuation stage. The result of mathematical connection ability test is analyzed quantitatively by mean test, conducting completeness test, mean differentiation test, and mean proportional differentiation test. The result of the research shows that VAK learning model results in well-qualified learning regarded from qualitative and quantitative sides. Students with visual learning style perform the highest mathematical connection ability, students with kinesthetic learning style perform average mathematical connection ability, and students with auditory learning style perform the lowest mathematical connection ability.

Power spectrum model of visual masking: simulations and empirical data.

PubMed

Serrano-Pedraza, Ignacio; Sierra-Vázquez, Vicente; Derrington, Andrew M

2013-06-01

In the study of the spatial characteristics of the visual channels, the power spectrum model of visual masking is one of the most widely used. When the task is to detect a signal masked by visual noise, this classical model assumes that the signal and the noise are previously processed by a bank of linear channels and that the power of the signal at threshold is proportional to the power of the noise passing through the visual channel that mediates detection. The model also assumes that this visual channel will have the highest ratio of signal power to noise power at its output. According to this, there are masking conditions where the highest signal-to-noise ratio (SNR) occurs in a channel centered in a spatial frequency different from the spatial frequency of the signal (off-frequency looking). Under these conditions the channel mediating detection could vary with the type of noise used in the masking experiment and this could affect the estimation of the shape and the bandwidth of the visual channels. It is generally believed that notched noise, white noise and double bandpass noise prevent off-frequency looking, and high-pass, low-pass and bandpass noises can promote it independently of the channel's shape. In this study, by means of a procedure that finds the channel that maximizes the SNR at its output, we performed numerical simulations using the power spectrum model to study the characteristics of masking caused by six types of one-dimensional noise (white, high-pass, low-pass, bandpass, notched, and double bandpass) for two types of channel's shape (symmetric and asymmetric). Our simulations confirm that (1) high-pass, low-pass, and bandpass noises do not prevent the off-frequency looking, (2) white noise satisfactorily prevents the off-frequency looking independently of the shape and bandwidth of the visual channel, and interestingly we proved for the first time that (3) notched and double bandpass noises prevent off-frequency looking only when the noise cutoffs around the spatial frequency of the signal match the shape of the visual channel (symmetric or asymmetric) involved in the detection. In order to test the explanatory power of the model with empirical data, we performed six visual masking experiments. We show that this model, with only two free parameters, fits the empirical masking data with high precision. Finally, we provide equations of the power spectrum model for six masking noises used in the simulations and in the experiments.

A signal detection model predicts the effects of set size on visual search accuracy for feature, conjunction, triple conjunction, and disjunction displays

NASA Technical Reports Server (NTRS)

Eckstein, M. P.; Thomas, J. P.; Palmer, J.; Shimozaki, S. S.

2000-01-01

Recently, quantitative models based on signal detection theory have been successfully applied to the prediction of human accuracy in visual search for a target that differs from distractors along a single attribute (feature search). The present paper extends these models for visual search accuracy to multidimensional search displays in which the target differs from the distractors along more than one feature dimension (conjunction, disjunction, and triple conjunction displays). The model assumes that each element in the display elicits a noisy representation for each of the relevant feature dimensions. The observer combines the representations across feature dimensions to obtain a single decision variable, and the stimulus with the maximum value determines the response. The model accurately predicts human experimental data on visual search accuracy in conjunctions and disjunctions of contrast and orientation. The model accounts for performance degradation without resorting to a limited-capacity spatially localized and temporally serial mechanism by which to bind information across feature dimensions.

A Hyperbolic Ontology Visualization Tool for Model Application Programming Interface Documentation

NASA Technical Reports Server (NTRS)

Hyman, Cody

2011-01-01

Spacecraft modeling, a critically important portion in validating planned spacecraft activities, is currently carried out using a time consuming method of mission to mission model implementations and integration. A current project in early development, Integrated Spacecraft Analysis (ISCA), aims to remedy this hindrance by providing reusable architectures and reducing time spent integrating models with planning and sequencing tools. The principle objective of this internship was to develop a user interface for an experimental ontology-based structure visualization of navigation and attitude control system modeling software. To satisfy this, a number of tree and graph visualization tools were researched and a Java based hyperbolic graph viewer was selected for experimental adaptation. Early results show promise in the ability to organize and display large amounts of spacecraft model documentation efficiently and effectively through a web browser. This viewer serves as a conceptual implementation for future development but trials with both ISCA developers and end users should be performed to truly evaluate the effectiveness of continued development of such visualizations.

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory

PubMed Central

Pratte, Michael S.; Park, Young Eun; Rademaker, Rosanne L.; Tong, Frank

2016-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced “oblique effect”, with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. PMID:28004957

Accounting for stimulus-specific variation in precision reveals a discrete capacity limit in visual working memory.

PubMed

Pratte, Michael S; Park, Young Eun; Rademaker, Rosanne L; Tong, Frank

2017-01-01

If we view a visual scene that contains many objects, then momentarily close our eyes, some details persist while others seem to fade. Discrete models of visual working memory (VWM) assume that only a few items can be actively maintained in memory, beyond which pure guessing will emerge. Alternatively, continuous resource models assume that all items in a visual scene can be stored with some precision. Distinguishing between these competing models is challenging, however, as resource models that allow for stochastically variable precision (across items and trials) can produce error distributions that resemble random guessing behavior. Here, we evaluated the hypothesis that a major source of variability in VWM performance arises from systematic variation in precision across the stimuli themselves; such stimulus-specific variability can be incorporated into both discrete-capacity and variable-precision resource models. Participants viewed multiple oriented gratings, and then reported the orientation of a cued grating from memory. When modeling the overall distribution of VWM errors, we found that the variable-precision resource model outperformed the discrete model. However, VWM errors revealed a pronounced "oblique effect," with larger errors for oblique than cardinal orientations. After this source of variability was incorporated into both models, we found that the discrete model provided a better account of VWM errors. Our results demonstrate that variable precision across the stimulus space can lead to an unwarranted advantage for resource models that assume stochastically variable precision. When these deterministic sources are adequately modeled, human working memory performance reveals evidence of a discrete capacity limit. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Grohar: Automated Visualization of Genome-Scale Metabolic Models and Their Pathways.

PubMed

Moškon, Miha; Zimic, Nikolaj; Mraz, Miha

2018-05-01

Genome-scale metabolic models (GEMs) have become a powerful tool for the investigation of the entire metabolism of the organism in silico. These models are, however, often extremely hard to reconstruct and also difficult to apply to the selected problem. Visualization of the GEM allows us to easier comprehend the model, to perform its graphical analysis, to find and correct the faulty relations, to identify the parts of the system with a designated function, etc. Even though several approaches for the automatic visualization of GEMs have been proposed, metabolic maps are still manually drawn or at least require large amount of manual curation. We present Grohar, a computational tool for automatic identification and visualization of GEM (sub)networks and their metabolic fluxes. These (sub)networks can be specified directly by listing the metabolites of interest or indirectly by providing reference metabolic pathways from different sources, such as KEGG, SBML, or Matlab file. These pathways are identified within the GEM using three different pathway alignment algorithms. Grohar also supports the visualization of the model adjustments (e.g., activation or inhibition of metabolic reactions) after perturbations are induced.

Declarative language design for interactive visualization.

PubMed

Heer, Jeffrey; Bostock, Michael

2010-01-01

We investigate the design of declarative, domain-specific languages for constructing interactive visualizations. By separating specification from execution, declarative languages can simplify development, enable unobtrusive optimization, and support retargeting across platforms. We describe the design of the Protovis specification language and its implementation within an object-oriented, statically-typed programming language (Java). We demonstrate how to support rich visualizations without requiring a toolkit-specific data model and extend Protovis to enable declarative specification of animated transitions. To support cross-platform deployment, we introduce rendering and event-handling infrastructures decoupled from the runtime platform, letting designers retarget visualization specifications (e.g., from desktop to mobile phone) with reduced effort. We also explore optimizations such as runtime compilation of visualization specifications, parallelized execution, and hardware-accelerated rendering. We present benchmark studies measuring the performance gains provided by these optimizations and compare performance to existing Java-based visualization tools, demonstrating scalability improvements exceeding an order of magnitude.

Visual Predictive Check in Models with Time-Varying Input Function.

PubMed

Largajolli, Anna; Bertoldo, Alessandra; Campioni, Marco; Cobelli, Claudio

2015-11-01

The nonlinear mixed effects models are commonly used modeling techniques in the pharmaceutical research as they enable the characterization of the individual profiles together with the population to which the individuals belong. To ensure a correct use of them is fundamental to provide powerful diagnostic tools that are able to evaluate the predictive performance of the models. The visual predictive check (VPC) is a commonly used tool that helps the user to check by visual inspection if the model is able to reproduce the variability and the main trend of the observed data. However, the simulation from the model is not always trivial, for example, when using models with time-varying input function (IF). In this class of models, there is a potential mismatch between each set of simulated parameters and the associated individual IF which can cause an incorrect profile simulation. We introduce a refinement of the VPC by taking in consideration a correlation term (the Mahalanobis or normalized Euclidean distance) that helps the association of the correct IF with the individual set of simulated parameters. We investigate and compare its performance with the standard VPC in models of the glucose and insulin system applied on real and simulated data and in a simulated pharmacokinetic/pharmacodynamic (PK/PD) example. The newly proposed VPC performance appears to be better with respect to the standard VPC especially for the models with big variability in the IF where the probability of simulating incorrect profiles is higher.

The Influence of Visual Experience on the Ability to Form Spatial Mental Models Based on Route and Survey Descriptions

ERIC Educational Resources Information Center

Noordzij, Matthijs L.; Zuidhoek, Sander; Postma, Albert

2006-01-01

The purpose of the present study is twofold: the first objective is to evaluate the importance of visual experience for the ability to form a spatial representation (spatial mental model) of fairly elaborate spatial descriptions. Secondly, we examine whether blind people exhibit the same preferences (i.e. level of performance on spatial tasks) as…

Good Features to Correlate for Visual Tracking

NASA Astrophysics Data System (ADS)

Gundogdu, Erhan; Alatan, A. Aydin

2018-05-01

During the recent years, correlation filters have shown dominant and spectacular results for visual object tracking. The types of the features that are employed in these family of trackers significantly affect the performance of visual tracking. The ultimate goal is to utilize robust features invariant to any kind of appearance change of the object, while predicting the object location as properly as in the case of no appearance change. As the deep learning based methods have emerged, the study of learning features for specific tasks has accelerated. For instance, discriminative visual tracking methods based on deep architectures have been studied with promising performance. Nevertheless, correlation filter based (CFB) trackers confine themselves to use the pre-trained networks which are trained for object classification problem. To this end, in this manuscript the problem of learning deep fully convolutional features for the CFB visual tracking is formulated. In order to learn the proposed model, a novel and efficient backpropagation algorithm is presented based on the loss function of the network. The proposed learning framework enables the network model to be flexible for a custom design. Moreover, it alleviates the dependency on the network trained for classification. Extensive performance analysis shows the efficacy of the proposed custom design in the CFB tracking framework. By fine-tuning the convolutional parts of a state-of-the-art network and integrating this model to a CFB tracker, which is the top performing one of VOT2016, 18% increase is achieved in terms of expected average overlap, and tracking failures are decreased by 25%, while maintaining the superiority over the state-of-the-art methods in OTB-2013 and OTB-2015 tracking datasets.

Corneal changes induced by laser ablation: study of the visual-quality evolution by a customized eye model

NASA Astrophysics Data System (ADS)

Ortiz, D.; Anera, R. G.; Saiz, J. M.; Jiménez, J. R.; Moreno, F.; Jiménez Del Barco, L.; González, F.

2006-11-01

This study focuses on the changes induced in both the asphericity and homogeneity of the cornea for a group of myopic eyes undergoing LASIK surgery. Eyes were characterized by a Kooijman-based customized eye model in which changes were introduced in the form of Gaussian-distributed refractive-index variations of given correlation length for the inhomogeneities and in the form of an expression, based on the modified Munnerlyn's paraxial formula, for the post-LASIK asphericity. Visual quality was evaluated in terms of the Modulation Transfer Function and the Point-Spread Function. The results show that, on average, the evolution of visual acuity is consistent with the change in corneal asphericity, while the evolution of contrast sensitivity requires a loss in corneal homogeneity in order to be explained. By including both effects in the model, the overall model performance in predicting visual quality is improved.

Desktop chaotic systems: Intuition and visualization

NASA Technical Reports Server (NTRS)

Bright, Michelle M.; Melcher, Kevin J.; Qammar, Helen K.; Hartley, Tom T.

1993-01-01

This paper presents a dynamic study of the Wildwood Pendulum, a commercially available desktop system which exhibits a strange attractor. The purpose of studying this chaotic pendulum is twofold: to gain insight in the paradigmatic approach of modeling, simulating, and determining chaos in nonlinear systems; and to provide a desktop model of chaos as a visual tool. For this study, the nonlinear behavior of this chaotic pendulum is modeled, a computer simulation is performed, and an experimental performance is measured. An assessment of the pendulum in the phase plane shows the strange attractor. Through the use of a box-assisted correlation dimension methodology, the attractor dimension is determined for both the model and the experimental pendulum systems. Correlation dimension results indicate that the pendulum and the model are chaotic and their fractal dimensions are similar.

Treatment of amblyopia in the adult: insights from a new rodent model of visual perceptual learning.

PubMed

Bonaccorsi, Joyce; Berardi, Nicoletta; Sale, Alessandro

2014-01-01

Amblyopia is the most common form of impairment of visual function affecting one eye, with a prevalence of about 1-5% of the total world population. Amblyopia usually derives from conditions of early functional imbalance between the two eyes, owing to anisometropia, strabismus, or congenital cataract, and results in a pronounced reduction of visual acuity and severe deficits in contrast sensitivity and stereopsis. It is widely accepted that, due to a lack of sufficient plasticity in the adult brain, amblyopia becomes untreatable after the closure of the critical period in the primary visual cortex. However, recent results obtained both in animal models and in clinical trials have challenged this view, unmasking a previously unsuspected potential for promoting recovery even in adulthood. In this context, non invasive procedures based on visual perceptual learning, i.e., the improvement in visual performance on a variety of simple visual tasks following practice, emerge as particularly promising to rescue discrimination abilities in adult amblyopic subjects. This review will survey recent work regarding the impact of visual perceptual learning on amblyopia, with a special focus on a new experimental model of perceptual learning in the amblyopic rat.

Treatment of amblyopia in the adult: insights from a new rodent model of visual perceptual learning

PubMed Central

Bonaccorsi, Joyce; Berardi, Nicoletta; Sale, Alessandro

2014-01-01

Amblyopia is the most common form of impairment of visual function affecting one eye, with a prevalence of about 1–5% of the total world population. Amblyopia usually derives from conditions of early functional imbalance between the two eyes, owing to anisometropia, strabismus, or congenital cataract, and results in a pronounced reduction of visual acuity and severe deficits in contrast sensitivity and stereopsis. It is widely accepted that, due to a lack of sufficient plasticity in the adult brain, amblyopia becomes untreatable after the closure of the critical period in the primary visual cortex. However, recent results obtained both in animal models and in clinical trials have challenged this view, unmasking a previously unsuspected potential for promoting recovery even in adulthood. In this context, non invasive procedures based on visual perceptual learning, i.e., the improvement in visual performance on a variety of simple visual tasks following practice, emerge as particularly promising to rescue discrimination abilities in adult amblyopic subjects. This review will survey recent work regarding the impact of visual perceptual learning on amblyopia, with a special focus on a new experimental model of perceptual learning in the amblyopic rat. PMID:25076874

A GUI visualization system for airborne lidar image data to reconstruct 3D city model

NASA Astrophysics Data System (ADS)

Kawata, Yoshiyuki; Koizumi, Kohei

2015-10-01

A visualization toolbox system with graphical user interfaces (GUIs) was developed for the analysis of LiDAR point cloud data, as a compound object oriented widget application in IDL (Interractive Data Language). The main features in our system include file input and output abilities, data conversion capability from ascii formatted LiDAR point cloud data to LiDAR image data whose pixel value corresponds the altitude measured by LiDAR, visualization of 2D/3D images in various processing steps and automatic reconstruction ability of 3D city model. The performance and advantages of our graphical user interface (GUI) visualization system for LiDAR data are demonstrated.

Visual search for object categories is predicted by the representational architecture of high-level visual cortex

PubMed Central

Alvarez, George A.; Nakayama, Ken; Konkle, Talia

2016-01-01

Visual search is a ubiquitous visual behavior, and efficient search is essential for survival. Different cognitive models have explained the speed and accuracy of search based either on the dynamics of attention or on similarity of item representations. Here, we examined the extent to which performance on a visual search task can be predicted from the stable representational architecture of the visual system, independent of attentional dynamics. Participants performed a visual search task with 28 conditions reflecting different pairs of categories (e.g., searching for a face among cars, body among hammers, etc.). The time it took participants to find the target item varied as a function of category combination. In a separate group of participants, we measured the neural responses to these object categories when items were presented in isolation. Using representational similarity analysis, we then examined whether the similarity of neural responses across different subdivisions of the visual system had the requisite structure needed to predict visual search performance. Overall, we found strong brain/behavior correlations across most of the higher-level visual system, including both the ventral and dorsal pathways when considering both macroscale sectors as well as smaller mesoscale regions. These results suggest that visual search for real-world object categories is well predicted by the stable, task-independent architecture of the visual system. NEW & NOTEWORTHY Here, we ask which neural regions have neural response patterns that correlate with behavioral performance in a visual processing task. We found that the representational structure across all of high-level visual cortex has the requisite structure to predict behavior. Furthermore, when directly comparing different neural regions, we found that they all had highly similar category-level representational structures. These results point to a ubiquitous and uniform representational structure in high-level visual cortex underlying visual object processing. PMID:27832600

Measured Visual Motion Sensitivity at Fixed Contrast in the Periphery and Far Periphery

DTIC Science & Technology

2017-08-01

group Soldier performance. Soldier performance depends on visual detection of enemy personnel and materiel. Vision modeling in IWARS is neither...a highly time-critical and order- dependent activity, these unrealistic characterizations of target detection time and order severely limit the...recognize that MVTs should depend on target contrast, so we selected a target design different from that used in the Monaco et al. (2007) study. Based

Enhancing Soldier Performance: A Nonlinear Model of Performance to Improve Selection Testing and Training

DTIC Science & Technology

1994-07-01

psychological refractory period 15. Two-flash threshold 16. Critical flicker fusion (CFF) 17. Steady state visually evoked response 18. Auditory brain stem...States of awareness I: Subliminal erceoption relationships to situational awareness (AL-TR-1992-0085). Brooks Air Force BaSe, TX: Armstrong...the signals required different inputs (e.g., visual versus auditory ) (Colley & Beech, 1989). Despite support of this theory from such experiments

Is Posner's "beam" the same as Treisman's "glue"?: On the relation between visual orienting and feature integration theory.

PubMed

Briand, K A; Klein, R M

1987-05-01

In the present study we investigated whether the visually allocated "beam" studied by Posner and others is the same visual attentional resource that performs the role of feature integration in Treisman's model. Subjects were cued to attend to a certain spatial location by a visual cue, and performance at expected and unexpected stimulus locations was compared. Subjects searched for a target letter (R) with distractor letters that either could give rise to illusory conjunctions (PQ) or could not (PB). Results from three separate experiments showed that orienting attention in response to central cues (endogenous orienting) showed similar effects for both conjunction and feature search. However, when attention was oriented with peripheral visual cues (exogenous orienting), conjunction search showed larger effects of attention than did feature search. It is suggested that the attentional systems that are oriented in response to central and peripheral cues may not be the same and that only the latter performs a role in feature integration. Possibilities for future research are discussed.

The visual system’s internal model of the world

PubMed Central

Lee, Tai Sing

2015-01-01

The Bayesian paradigm has provided a useful conceptual theory for understanding perceptual computation in the brain. While the detailed neural mechanisms of Bayesian inference are not fully understood, recent computational and neurophysiological works have illuminated the underlying computational principles and representational architecture. The fundamental insights are that the visual system is organized as a modular hierarchy to encode an internal model of the world, and that perception is realized by statistical inference based on such internal model. In this paper, I will discuss and analyze the varieties of representational schemes of these internal models and how they might be used to perform learning and inference. I will argue for a unified theoretical framework for relating the internal models to the observed neural phenomena and mechanisms in the visual cortex. PMID:26566294

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed.

High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

PubMed Central

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y. K.

2018-01-01

Fast and accurate computational biology models offer the prospect of accelerating the development of personalized medicine. A tool capable of estimating treatment success can help prevent unnecessary and costly treatments and potential harmful side effects. A novel high-performance Agent-Based Model (ABM) was adopted to simulate and visualize multi-scale complex biological processes arising in vocal fold inflammation and repair. The computational scheme was designed to organize the 3D ABM sub-tasks to fully utilize the resources available on current heterogeneous platforms consisting of multi-core CPUs and many-core GPUs. Subtasks are further parallelized and convolution-based diffusion is used to enhance the performance of the ABM simulation. The scheme was implemented using a client-server protocol allowing the results of each iteration to be analyzed and visualized on the server (i.e., in-situ) while the simulation is running on the same server. The resulting simulation and visualization software enables users to interact with and steer the course of the simulation in real-time as needed. This high-resolution 3D ABM framework was used for a case study of surgical vocal fold injury and repair. The new framework is capable of completing the simulation, visualization and remote result delivery in under 7 s per iteration, where each iteration of the simulation represents 30 min in the real world. The case study model was simulated at the physiological scale of a human vocal fold. This simulation tracks 17 million biological cells as well as a total of 1.7 billion signaling chemical and structural protein data points. The visualization component processes and renders all simulated biological cells and 154 million signaling chemical data points. The proposed high-performance 3D ABM was verified through comparisons with empirical vocal fold data. Representative trends of biomarker predictions in surgically injured vocal folds were observed. PMID:29706894

Intelligent Entity Behavior Within Synthetic Environments. Chapter 3

NASA Technical Reports Server (NTRS)

Kruk, R. V.; Howells, P. B.; Siksik, D. N.

2007-01-01

This paper describes some elements in the development of realistic performance and behavior in the synthetic entities (players) which support Modeling and Simulation (M&S) applications, particularly military training. Modern human-in-the-loop (virtual) training systems incorporate sophisticated synthetic environments, which provide: 1. The operational environment, including, for example, terrain databases; 2. Physical entity parameters which define performance in engineered systems, such as aircraft aerodynamics; 3. Platform/system characteristics such as acoustic, IR and radar signatures; 4. Behavioral entity parameters which define interactive performance, including knowledge/reasoning about terrain, tactics; and, 5. Doctrine, which combines knowledge and tactics into behavior rule sets. The resolution and fidelity of these model/database elements can vary substantially, but as synthetic environments are designed to be compose able, attributes may easily be added (e.g., adding a new radar to an aircraft) or enhanced (e.g. Amending or replacing missile seeker head/ Electronic Counter Measures (ECM) models to improve the realism of their interaction). To a human in the loop with synthetic entities, their observed veridicality is assessed via engagement responses (e.g. effect of countermeasures upon a closing missile), as seen on systems displays, and visual (image) behavior. The realism of visual models in a simulation (level of detail as well as motion fidelity) remains a challenge in realistic articulation of elements such as vehicle antennae and turrets, or, with human figures; posture, joint articulation, response to uneven ground. Currently the adequacy of visual representation is more dependant upon the quality and resolution of the physical models driving those entities than graphics processing power per Se. Synthetic entities in M&S applications traditionally have represented engineered systems (e.g. aircraft) with human-in-the-loop performance characteristics (e.g. visual acuity) included in the system behavioral specification. As well, performance affecting human parameters such as experience level, fatigue and stress are coming into wider use (via AI approaches) to incorporate more uncertainty as to response type as well as performance (e.g. Where an opposing entity might go and what it might do, as well as how well it might perform).

Revel8or: Model Driven Capacity Planning Tool Suite

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhu, Liming; Liu, Yan; Bui, Ngoc B.

2007-05-31

Designing complex multi-tier applications that must meet strict performance requirements is a challenging software engineering problem. Ideally, the application architect could derive accurate performance predictions early in the project life-cycle, leveraging initial application design-level models and a description of the target software and hardware platforms. To this end, we have developed a capacity planning tool suite for component-based applications, called Revel8tor. The tool adheres to the model driven development paradigm and supports benchmarking and performance prediction for J2EE, .Net and Web services platforms. The suite is composed of three different tools: MDAPerf, MDABench and DSLBench. MDAPerf allows annotation of designmore » diagrams and derives performance analysis models. MDABench allows a customized benchmark application to be modeled in the UML 2.0 Testing Profile and automatically generates a deployable application, with measurement automatically conducted. DSLBench allows the same benchmark modeling and generation to be conducted using a simple performance engineering Domain Specific Language (DSL) in Microsoft Visual Studio. DSLBench integrates with Visual Studio and reuses its load testing infrastructure. Together, the tool suite can assist capacity planning across platforms in an automated fashion.« less

A physiologically based nonhomogeneous Poisson counter model of visual identification.

PubMed

Christensen, Jeppe H; Markussen, Bo; Bundesen, Claus; Kyllingsbæk, Søren

2018-04-30

A physiologically based nonhomogeneous Poisson counter model of visual identification is presented. The model was developed in the framework of a Theory of Visual Attention (Bundesen, 1990; Kyllingsbæk, Markussen, & Bundesen, 2012) and meant for modeling visual identification of objects that are mutually confusable and hard to see. The model assumes that the visual system's initial sensory response consists in tentative visual categorizations, which are accumulated by leaky integration of both transient and sustained components comparable with those found in spike density patterns of early sensory neurons. The sensory response (tentative categorizations) feeds independent Poisson counters, each of which accumulates tentative object categorizations of a particular type to guide overt identification performance. We tested the model's ability to predict the effect of stimulus duration on observed distributions of responses in a nonspeeded (pure accuracy) identification task with eight response alternatives. The time courses of correct and erroneous categorizations were well accounted for when the event-rates of competing Poisson counters were allowed to vary independently over time in a way that mimicked the dynamics of receptive field selectivity as found in neurophysiological studies. Furthermore, the initial sensory response yielded theoretical hazard rate functions that closely resembled empirically estimated ones. Finally, supplied with a Naka-Rushton type contrast gain control, the model provided an explanation for Bloch's law. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Relationships between academic performance, SES school type and perceptual-motor skills in first grade South African learners: NW-CHILD study.

PubMed

Pienaar, A E; Barhorst, R; Twisk, J W R

2014-05-01

Perceptual-motor skills contribute to a variety of basic learning skills associated with normal academic success. This study aimed to determine the relationship between academic performance and perceptual-motor skills in first grade South African learners and whether low SES (socio-economic status) school type plays a role in such a relationship. This cross-sectional study of the baseline measurements of the NW-CHILD longitudinal study included a stratified random sample of first grade learners (n = 812; 418 boys and 394 boys), with a mean age of 6.78 years ± 0.49 living in the North West Province (NW) of South Africa. The Beery-Buktenica Developmental Test of Visual-Motor Integration-4 (VMI) was used to assess visual-motor integration, visual perception and hand control while the Bruininks Oseretsky Test of Motor Proficiency, short form (BOT2-SF) assessed overall motor proficiency. Academic performance in math, reading and writing was assessed with the Mastery of Basic Learning Areas Questionnaire. Linear mixed models analysis was performed with spss to determine possible differences between the different VMI and BOT2-SF standard scores in different math, reading and writing mastery categories ranging from no mastery to outstanding mastery. A multinomial multilevel logistic regression analysis was performed to assess the relationship between a clustered score of academic performance and the different determinants. A strong relationship was established between academic performance and VMI, visual perception, hand control and motor proficiency with a significant relationship between a clustered academic performance score, visual-motor integration and visual perception. A negative association was established between low SES school types on academic performance, with a common perceptual motor foundation shared by all basic learning areas. Visual-motor integration, visual perception, hand control and motor proficiency are closely related to basic academic skills required in the first formal school year, especially among learners in low SES type schools. © 2013 John Wiley & Sons Ltd.

Measuring and Predicting Tag Importance for Image Retrieval.

PubMed

Li, Shangwen; Purushotham, Sanjay; Chen, Chen; Ren, Yuzhuo; Kuo, C-C Jay

2017-12-01

Textual data such as tags, sentence descriptions are combined with visual cues to reduce the semantic gap for image retrieval applications in today's Multimodal Image Retrieval (MIR) systems. However, all tags are treated as equally important in these systems, which may result in misalignment between visual and textual modalities during MIR training. This will further lead to degenerated retrieval performance at query time. To address this issue, we investigate the problem of tag importance prediction, where the goal is to automatically predict the tag importance and use it in image retrieval. To achieve this, we first propose a method to measure the relative importance of object and scene tags from image sentence descriptions. Using this as the ground truth, we present a tag importance prediction model to jointly exploit visual, semantic and context cues. The Structural Support Vector Machine (SSVM) formulation is adopted to ensure efficient training of the prediction model. Then, the Canonical Correlation Analysis (CCA) is employed to learn the relation between the image visual feature and tag importance to obtain robust retrieval performance. Experimental results on three real-world datasets show a significant performance improvement of the proposed MIR with Tag Importance Prediction (MIR/TIP) system over other MIR systems.

A Model of the Superior Colliculus Predicts Fixation Locations during Scene Viewing and Visual Search.

PubMed

Adeli, Hossein; Vitu, Françoise; Zelinsky, Gregory J

2017-02-08

Modern computational models of attention predict fixations using saliency maps and target maps, which prioritize locations for fixation based on feature contrast and target goals, respectively. But whereas many such models are biologically plausible, none have looked to the oculomotor system for design constraints or parameter specification. Conversely, although most models of saccade programming are tightly coupled to underlying neurophysiology, none have been tested using real-world stimuli and tasks. We combined the strengths of these two approaches in MASC, a model of attention in the superior colliculus (SC) that captures known neurophysiological constraints on saccade programming. We show that MASC predicted the fixation locations of humans freely viewing naturalistic scenes and performing exemplar and categorical search tasks, a breadth achieved by no other existing model. Moreover, it did this as well or better than its more specialized state-of-the-art competitors. MASC's predictive success stems from its inclusion of high-level but core principles of SC organization: an over-representation of foveal information, size-invariant population codes, cascaded population averaging over distorted visual and motor maps, and competition between motor point images for saccade programming, all of which cause further modulation of priority (attention) after projection of saliency and target maps to the SC. Only by incorporating these organizing brain principles into our models can we fully understand the transformation of complex visual information into the saccade programs underlying movements of overt attention. With MASC, a theoretical footing now exists to generate and test computationally explicit predictions of behavioral and neural responses in visually complex real-world contexts. SIGNIFICANCE STATEMENT The superior colliculus (SC) performs a visual-to-motor transformation vital to overt attention, but existing SC models cannot predict saccades to visually complex real-world stimuli. We introduce a brain-inspired SC model that outperforms state-of-the-art image-based competitors in predicting the sequences of fixations made by humans performing a range of everyday tasks (scene viewing and exemplar and categorical search), making clear the value of looking to the brain for model design. This work is significant in that it will drive new research by making computationally explicit predictions of SC neural population activity in response to naturalistic stimuli and tasks. It will also serve as a blueprint for the construction of other brain-inspired models, helping to usher in the next generation of truly intelligent autonomous systems. Copyright © 2017 the authors 0270-6474/17/371453-15$15.00/0.

Computational and fMRI Studies of Visualization

DTIC Science & Technology

2009-03-31

spatial thinking in high level cognition, such as in problem-solving and reasoning. In conjunction with the experimental work, the project developed a...computational modeling system (4CAPS) as well as the development of 4CAPS models for particular tasks. The cognitive level of 4CAPS accounts for...neuroarchitecture to interpret and predict the brain activation in a network of cortical areas that underpin the performance of a visual thinking task. The

Different developmental trajectories across feature types support a dynamic field model of visual working memory development.

PubMed

Simmering, Vanessa R; Miller, Hilary E; Bohache, Kevin

2015-05-01

Research on visual working memory has focused on characterizing the nature of capacity limits as "slots" or "resources" based almost exclusively on adults' performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to "slot" or "resource" explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children's (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model-purportedly arising through experience-can capture differences across feature types.

Efficacy of Simulation-Based Learning of Electronics Using Visualization and Manipulation

ERIC Educational Resources Information Center

Chen, Yu-Lung; Hong, Yu-Ru; Sung, Yao-Ting; Chang, Kuo-En

2011-01-01

Software for simulation-based learning of electronics was implemented to help learners understand complex and abstract concepts through observing external representations and exploring concept models. The software comprises modules for visualization and simulative manipulation. Differences in learning performance of using the learning software…

Combining photorealistic immersive geovisualization and high-resolution geospatial data to enhance human-scale viewshed modelling

NASA Astrophysics Data System (ADS)

Tabrizian, P.; Petrasova, A.; Baran, P.; Petras, V.; Mitasova, H.; Meentemeyer, R. K.

2017-12-01

Viewshed modelling- a process of defining, parsing and analysis of landscape visual space's structure within GIS- has been commonly used in applications ranging from landscape planning and ecosystem services assessment to geography and archaeology. However, less effort has been made to understand whether and to what extent these objective analyses predict actual on-the-ground perception of human observer. Moreover, viewshed modelling at the human-scale level require incorporation of fine-grained landscape structure (eg., vegetation) and patterns (e.g, landcover) that are typically omitted from visibility calculations or unrealistically simulated leading to significant error in predicting visual attributes. This poster illustrates how photorealistic Immersive Virtual Environments and high-resolution geospatial data can be used to integrate objective and subjective assessments of visual characteristics at the human-scale level. We performed viewshed modelling for a systematically sampled set of viewpoints (N=340) across an urban park using open-source GIS (GRASS GIS). For each point a binary viewshed was computed on a 3D surface model derived from high-density leaf-off LIDAR (QL2) points. Viewshed map was combined with high-resolution landcover (.5m) derived through fusion of orthoimagery, lidar vegetation, and vector data. Geo-statistics and landscape structure analysis was performed to compute topological and compositional metrics for visual-scale (e.g., openness), complexity (pattern, shape and object diversity), and naturalness. Based on the viewshed model output, a sample of 24 viewpoints representing the variation of visual characteristics were selected and geolocated. For each location, 360o imagery were captured using a DSL camera mounted on a GIGA PAN robot. We programmed a virtual reality application through which human subjects (N=100) immersively experienced a random representation of selected environments via a head-mounted display (Oculus Rift CV1), and rated each location on perceived openness, naturalness and complexity. Regression models were performed to correlate model outputs with participants' responses. The results indicated strong, significant correlations for openness, and naturalness and moderate correlation for complexity estimations.

Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model

PubMed Central

Konstantinova, Jelizaveta; Xu, Guanghua; He, Bo; Aminzadeh, Vahid; Xie, Jun; Wurdemann, Helge; Althoefer, Kaspar

2017-01-01

Haptic information in robotic surgery can significantly improve clinical outcomes and help detect hard soft-tissue inclusions that indicate potential abnormalities. Visual representation of tissue stiffness information is a cost-effective technique. Meanwhile, direct force feedback, although considerably more expensive than visual representation, is an intuitive method of conveying information regarding tissue stiffness to surgeons. In this study, real-time visual stiffness feedback by sliding indentation palpation is proposed, validated, and compared with force feedback involving human subjects. In an experimental tele-manipulation environment, a dynamically updated color map depicting the stiffness of probed soft tissue is presented via a graphical interface. The force feedback is provided, aided by a master haptic device. The haptic device uses data acquired from an F/T sensor attached to the end-effector of a tele-manipulated robot. Hard nodule detection performance is evaluated for 2 modes (force feedback and visual stiffness feedback) of stiffness feedback on an artificial organ containing buried stiff nodules. From this artificial organ, a virtual-environment tissue model is generated based on sliding indentation measurements. Employing this virtual-environment tissue model, we compare the performance of human participants in distinguishing differently sized hard nodules by force feedback and visual stiffness feedback. Results indicate that the proposed distributed visual representation of tissue stiffness can be used effectively for hard nodule identification. The representation can also be used as a sufficient substitute for force feedback in tissue palpation. PMID:28248996

Evaluation of stiffness feedback for hard nodule identification on a phantom silicone model.

PubMed

Li, Min; Konstantinova, Jelizaveta; Xu, Guanghua; He, Bo; Aminzadeh, Vahid; Xie, Jun; Wurdemann, Helge; Althoefer, Kaspar

2017-01-01

Haptic information in robotic surgery can significantly improve clinical outcomes and help detect hard soft-tissue inclusions that indicate potential abnormalities. Visual representation of tissue stiffness information is a cost-effective technique. Meanwhile, direct force feedback, although considerably more expensive than visual representation, is an intuitive method of conveying information regarding tissue stiffness to surgeons. In this study, real-time visual stiffness feedback by sliding indentation palpation is proposed, validated, and compared with force feedback involving human subjects. In an experimental tele-manipulation environment, a dynamically updated color map depicting the stiffness of probed soft tissue is presented via a graphical interface. The force feedback is provided, aided by a master haptic device. The haptic device uses data acquired from an F/T sensor attached to the end-effector of a tele-manipulated robot. Hard nodule detection performance is evaluated for 2 modes (force feedback and visual stiffness feedback) of stiffness feedback on an artificial organ containing buried stiff nodules. From this artificial organ, a virtual-environment tissue model is generated based on sliding indentation measurements. Employing this virtual-environment tissue model, we compare the performance of human participants in distinguishing differently sized hard nodules by force feedback and visual stiffness feedback. Results indicate that the proposed distributed visual representation of tissue stiffness can be used effectively for hard nodule identification. The representation can also be used as a sufficient substitute for force feedback in tissue palpation.

Using Saliency-Weighted Disparity Statistics for Objective Visual Comfort Assessment of Stereoscopic Images

NASA Astrophysics Data System (ADS)

Zhang, Wenlan; Luo, Ting; Jiang, Gangyi; Jiang, Qiuping; Ying, Hongwei; Lu, Jing

2016-06-01

Visual comfort assessment (VCA) for stereoscopic images is a particularly significant yet challenging task in 3D quality of experience research field. Although the subjective assessment given by human observers is known as the most reliable way to evaluate the experienced visual discomfort, it is time-consuming and non-systematic. Therefore, it is of great importance to develop objective VCA approaches that can faithfully predict the degree of visual discomfort as human beings do. In this paper, a novel two-stage objective VCA framework is proposed. The main contribution of this study is that the important visual attention mechanism of human visual system is incorporated for visual comfort-aware feature extraction. Specifically, in the first stage, we first construct an adaptive 3D visual saliency detection model to derive saliency map of a stereoscopic image, and then a set of saliency-weighted disparity statistics are computed and combined to form a single feature vector to represent a stereoscopic image in terms of visual comfort. In the second stage, a high dimensional feature vector is fused into a single visual comfort score by performing random forest algorithm. Experimental results on two benchmark databases confirm the superior performance of the proposed approach.

Towards a Visual Quality Metric for Digital Video

NASA Technical Reports Server (NTRS)

Watson, Andrew B.

1998-01-01

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

Automated Assessment of Visual Quality of Digital Video

NASA Technical Reports Server (NTRS)

Watson, Andrew B.; Ellis, Stephen R. (Technical Monitor)

1997-01-01

The advent of widespread distribution of digital video creates a need for automated methods for evaluating visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics. In previous work, we have developed visual quality metrics for evaluating, controlling, and optimizing the quality of compressed still images[1-4]. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. The challenge of video quality metrics is to extend these simplified models to temporal signals as well. In this presentation I will discuss a number of the issues that must be resolved in the design of effective video quality metrics. Among these are spatial, temporal, and chromatic sensitivity and their interactions, visual masking, and implementation complexity. I will also touch on the question of how to evaluate the performance of these metrics.

Template construction grammar: from visual scene description to language comprehension and agrammatism.

PubMed

Barrès, Victor; Lee, Jinyong

2014-01-01

How does the language system coordinate with our visual system to yield flexible integration of linguistic, perceptual, and world-knowledge information when we communicate about the world we perceive? Schema theory is a computational framework that allows the simulation of perceptuo-motor coordination programs on the basis of known brain operating principles such as cooperative computation and distributed processing. We present first its application to a model of language production, SemRep/TCG, which combines a semantic representation of visual scenes (SemRep) with Template Construction Grammar (TCG) as a means to generate verbal descriptions of a scene from its associated SemRep graph. SemRep/TCG combines the neurocomputational framework of schema theory with the representational format of construction grammar in a model linking eye-tracking data to visual scene descriptions. We then offer a conceptual extension of TCG to include language comprehension and address data on the role of both world knowledge and grammatical semantics in the comprehension performances of agrammatic aphasic patients. This extension introduces a distinction between heavy and light semantics. The TCG model of language comprehension offers a computational framework to quantitatively analyze the distributed dynamics of language processes, focusing on the interactions between grammatical, world knowledge, and visual information. In particular, it reveals interesting implications for the understanding of the various patterns of comprehension performances of agrammatic aphasics measured using sentence-picture matching tasks. This new step in the life cycle of the model serves as a basis for exploring the specific challenges that neurolinguistic computational modeling poses to the neuroinformatics community.

Adapting the iSNOBAL model for improved visualization in a GIS environment

NASA Astrophysics Data System (ADS)

Johansen, W. J.; Delparte, D.

2014-12-01

Snowmelt is a primary means of crucial water resources in much of the western United States. Researchers are developing models that estimate snowmelt to aid in water resource management. One such model is the image snowcover energy and mass balance (iSNOBAL) model. It uses input climate grids to simulate the development and melting of snowpack in mountainous regions. This study looks at applying this model to the Reynolds Creek Experimental Watershed in southwestern Idaho, utilizing novel approaches incorporating geographic information systems (GIS). To improve visualization of the iSNOBAL model, we have adapted it to run in a GIS environment. This type of environment is suited to both the input grid creation and the visualization of results. The data used for input grid creation can be stored locally or on a web-server. Kriging interpolation embedded within Python scripts are used to create air temperature, soil temperature, humidity, and precipitation grids, while built-in GIS and existing tools are used to create solar radiation and wind grids. Additional Python scripting is then used to perform model calculations. The final product is a user-friendly and accessible version of the iSNOBAL model, including the ability to easily visualize and interact with model results, all within a web- or desktop-based GIS environment. This environment allows for interactive manipulation of model parameters and visualization of the resulting input grids for the model calculations. Future work is moving towards adapting the model further for use in a 3D gaming engine for improved visualization and interaction.

Brain processing of visual information during fast eye movements maintains motor performance.

PubMed

Panouillères, Muriel; Gaveau, Valérie; Socasau, Camille; Urquizar, Christian; Pélisson, Denis

2013-01-01

Movement accuracy depends crucially on the ability to detect errors while actions are being performed. When inaccuracies occur repeatedly, both an immediate motor correction and a progressive adaptation of the motor command can unfold. Of all the movements in the motor repertoire of humans, saccadic eye movements are the fastest. Due to the high speed of saccades, and to the impairment of visual perception during saccades, a phenomenon called "saccadic suppression", it is widely believed that the adaptive mechanisms maintaining saccadic performance depend critically on visual error signals acquired after saccade completion. Here, we demonstrate that, contrary to this widespread view, saccadic adaptation can be based entirely on visual information presented during saccades. Our results show that visual error signals introduced during saccade execution--by shifting a visual target at saccade onset and blanking it at saccade offset--induce the same level of adaptation as error signals, presented for the same duration, but after saccade completion. In addition, they reveal that this processing of intra-saccadic visual information for adaptation depends critically on visual information presented during the deceleration phase, but not the acceleration phase, of the saccade. These findings demonstrate that the human central nervous system can use short intra-saccadic glimpses of visual information for motor adaptation, and they call for a reappraisal of current models of saccadic adaptation.

A Grammar-based Approach for Modeling User Interactions and Generating Suggestions During the Data Exploration Process.

PubMed

Dabek, Filip; Caban, Jesus J

2017-01-01

Despite the recent popularity of visual analytics focusing on big data, little is known about how to support users that use visualization techniques to explore multi-dimensional datasets and accomplish specific tasks. Our lack of models that can assist end-users during the data exploration process has made it challenging to learn from the user's interactive and analytical process. The ability to model how a user interacts with a specific visualization technique and what difficulties they face are paramount in supporting individuals with discovering new patterns within their complex datasets. This paper introduces the notion of visualization systems understanding and modeling user interactions with the intent of guiding a user through a task thereby enhancing visual data exploration. The challenges faced and the necessary future steps to take are discussed; and to provide a working example, a grammar-based model is presented that can learn from user interactions, determine the common patterns among a number of subjects using a K-Reversible algorithm, build a set of rules, and apply those rules in the form of suggestions to new users with the goal of guiding them along their visual analytic process. A formal evaluation study with 300 subjects was performed showing that our grammar-based model is effective at capturing the interactive process followed by users and that further research in this area has the potential to positively impact how users interact with a visualization system.

Oscillatory network with self-organized dynamical connections for synchronization-based image segmentation.

PubMed

Kuzmina, Margarita; Manykin, Eduard; Surina, Irina

2004-01-01

An oscillatory network of columnar architecture located in 3D spatial lattice was recently designed by the authors as oscillatory model of the brain visual cortex. Single network oscillator is a relaxational neural oscillator with internal dynamics tunable by visual image characteristics - local brightness and elementary bar orientation. It is able to demonstrate either activity state (stable undamped oscillations) or "silence" (quickly damped oscillations). Self-organized nonlocal dynamical connections of oscillators depend on oscillator activity levels and orientations of cortical receptive fields. Network performance consists in transfer into a state of clusterized synchronization. At current stage grey-level image segmentation tasks are carried out by 2D oscillatory network, obtained as a limit version of the source model. Due to supplemented network coupling strength control the 2D reduced network provides synchronization-based image segmentation. New results on segmentation of brightness and texture images presented in the paper demonstrate accurate network performance and informative visualization of segmentation results, inherent in the model.

Information visualization of the minority game

NASA Astrophysics Data System (ADS)

Jiang, W.; Herbert, R. D.; Webber, R.

2008-02-01

Many dynamical systems produce large quantities of data. How can the system be understood from the output data? Often people are simply overwhelmed by the data. Traditional tools such as tables and plots are often not adequate, and new techniques are needed to help people to analyze the system. In this paper, we propose the use of two spacefilling visualization tools to examine the output from a complex agent-based financial model. We measure the effectiveness and performance of these tools through usability experiments. Based on the experimental results, we develop two new visualization techniques that combine the advantages and discard the disadvantages of the information visualization tools. The model we use is an evolutionary version of the Minority Game which simulates a financial market.

The visual accommodation response during concurrent mental activity

NASA Technical Reports Server (NTRS)

Malmstrom, F. V.; Randle, R. J.; Bendix, J. S.; Weber, R. J.

1980-01-01

The direction and magnitude of the human visual accommodation response during concurrent mental activity are investigated. Subject focusing responses to targets at distances of 0.0 D, 3.0 D and an indeterminate distance were monitored by means of an optometer during the performance of a backwards counting task and a visual imagery task (thinking near and thinking far). In both experiments a shift in accommodation towards the visual far point is observed particularly for the near target, which increases with the duration of the task. The results can be interpreted in terms of both the capacity model of Kahneman (1973) and the autonomic arousal model of Hess and Polt (1964), and are not inconsistent with the possibility of an intermediate resting position.

Similarity relations in visual search predict rapid visual categorization

PubMed Central

Mohan, Krithika; Arun, S. P.

2012-01-01

How do we perform rapid visual categorization?It is widely thought that categorization involves evaluating the similarity of an object to other category items, but the underlying features and similarity relations remain unknown. Here, we hypothesized that categorization performance is based on perceived similarity relations between items within and outside the category. To this end, we measured the categorization performance of human subjects on three diverse visual categories (animals, vehicles, and tools) and across three hierarchical levels (superordinate, basic, and subordinate levels among animals). For the same subjects, we measured their perceived pair-wise similarities between objects using a visual search task. Regardless of category and hierarchical level, we found that the time taken to categorize an object could be predicted using its similarity to members within and outside its category. We were able to account for several classic categorization phenomena, such as (a) the longer times required to reject category membership; (b) the longer times to categorize atypical objects; and (c) differences in performance across tasks and across hierarchical levels. These categorization times were also accounted for by a model that extracts coarse structure from an image. The striking agreement observed between categorization and visual search suggests that these two disparate tasks depend on a shared coarse object representation. PMID:23092947

DEEP MOTIF DASHBOARD: VISUALIZING AND UNDERSTANDING GENOMIC SEQUENCES USING DEEP NEURAL NETWORKS.

PubMed

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2017-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence's saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them.

Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks

PubMed Central

Lanchantin, Jack; Singh, Ritambhara; Wang, Beilun; Qi, Yanjun

2018-01-01

Deep neural network (DNN) models have recently obtained state-of-the-art prediction accuracy for the transcription factor binding (TFBS) site classification task. However, it remains unclear how these approaches identify meaningful DNA sequence signals and give insights as to why TFs bind to certain locations. In this paper, we propose a toolkit called the Deep Motif Dashboard (DeMo Dashboard) which provides a suite of visualization strategies to extract motifs, or sequence patterns from deep neural network models for TFBS classification. We demonstrate how to visualize and understand three important DNN models: convolutional, recurrent, and convolutional-recurrent networks. Our first visualization method is finding a test sequence’s saliency map which uses first-order derivatives to describe the importance of each nucleotide in making the final prediction. Second, considering recurrent models make predictions in a temporal manner (from one end of a TFBS sequence to the other), we introduce temporal output scores, indicating the prediction score of a model over time for a sequential input. Lastly, a class-specific visualization strategy finds the optimal input sequence for a given TFBS positive class via stochastic gradient optimization. Our experimental results indicate that a convolutional-recurrent architecture performs the best among the three architectures. The visualization techniques indicate that CNN-RNN makes predictions by modeling both motifs as well as dependencies among them. PMID:27896980

Deep Neural Networks: A New Framework for Modeling Biological Vision and Brain Information Processing.

PubMed

Kriegeskorte, Nikolaus

2015-11-24

Recent advances in neural network modeling have enabled major strides in computer vision and other artificial intelligence applications. Human-level visual recognition abilities are coming within reach of artificial systems. Artificial neural networks are inspired by the brain, and their computations could be implemented in biological neurons. Convolutional feedforward networks, which now dominate computer vision, take further inspiration from the architecture of the primate visual hierarchy. However, the current models are designed with engineering goals, not to model brain computations. Nevertheless, initial studies comparing internal representations between these models and primate brains find surprisingly similar representational spaces. With human-level performance no longer out of reach, we are entering an exciting new era, in which we will be able to build biologically faithful feedforward and recurrent computational models of how biological brains perform high-level feats of intelligence, including vision.

A novel visual saliency analysis model based on dynamic multiple feature combination strategy

NASA Astrophysics Data System (ADS)

Lv, Jing; Ye, Qi; Lv, Wen; Zhang, Libao

2017-06-01

The human visual system can quickly focus on a small number of salient objects. This process was known as visual saliency analysis and these salient objects are called focus of attention (FOA). The visual saliency analysis mechanism can be used to extract the salient regions and analyze saliency of object in an image, which is time-saving and can avoid unnecessary costs of computing resources. In this paper, a novel visual saliency analysis model based on dynamic multiple feature combination strategy is introduced. In the proposed model, we first generate multi-scale feature maps of intensity, color and orientation features using Gaussian pyramids and the center-surround difference. Then, we evaluate the contribution of all feature maps to the saliency map according to the area of salient regions and their average intensity, and attach different weights to different features according to their importance. Finally, we choose the largest salient region generated by the region growing method to perform the evaluation. Experimental results show that the proposed model cannot only achieve higher accuracy in saliency map computation compared with other traditional saliency analysis models, but also extract salient regions with arbitrary shapes, which is of great value for the image analysis and understanding.

Analysis of CAD Model-based Visual Tracking for Microassembly using a New Block Set for MATLAB/Simulink

NASA Astrophysics Data System (ADS)

Kudryavtsev, Andrey V.; Laurent, Guillaume J.; Clévy, Cédric; Tamadazte, Brahim; Lutz, Philippe

2015-10-01

Microassembly is an innovative alternative to the microfabrication process of MOEMS, which is quite complex. It usually implies the use of microrobots controlled by an operator. The reliability of this approach has been already confirmed for micro-optical technologies. However, the characterization of assemblies has shown that the operator is the main source of inaccuracies in the teleoperated microassembly. Therefore, there is great interest in automating the microassembly process. One of the constraints of automation in microscale is the lack of high precision sensors capable to provide the full information about the object position. Thus, the usage of visual-based feedback represents a very promising approach allowing to automate the microassembly process. The purpose of this article is to characterize the techniques of object position estimation based on the visual data, i.e., visual tracking techniques from the ViSP library. These algorithms enables a 3-D object pose using a single view of the scene and the CAD model of the object. The performance of three main types of model-based trackers is analyzed and quantified: edge-based, texture-based and hybrid tracker. The problems of visual tracking in microscale are discussed. The control of the micromanipulation station used in the framework of our project is performed using a new Simulink block set. Experimental results are shown and demonstrate the possibility to obtain the repeatability below 1 µm.

Predicting Visual Disability in Glaucoma With Combinations of Vision Measures.

PubMed

Lin, Stephanie; Mihailovic, Aleksandra; West, Sheila K; Johnson, Chris A; Friedman, David S; Kong, Xiangrong; Ramulu, Pradeep Y

2018-04-01

We characterized vision in glaucoma using seven visual measures, with the goals of determining the dimensionality of vision, and how many and which visual measures best model activity limitation. We analyzed cross-sectional data from 150 older adults with glaucoma, collecting seven visual measures: integrated visual field (VF) sensitivity, visual acuity, contrast sensitivity (CS), area under the log CS function, color vision, stereoacuity, and visual acuity with noise. Principal component analysis was used to examine the dimensionality of vision. Multivariable regression models using one, two, or three vision tests (and nonvisual predictors) were compared to determine which was best associated with Rasch-analyzed Glaucoma Quality of Life-15 (GQL-15) person measure scores. The participants had a mean age of 70.2 and IVF sensitivity of 26.6 dB, suggesting mild-to-moderate glaucoma. All seven vision measures loaded similarly onto the first principal component (eigenvectors, 0.220-0.442), which explained 56.9% of the variance in vision scores. In models for GQL scores, the maximum adjusted- R 2 values obtained were 0.263, 0.296, and 0.301 when using one, two, and three vision tests in the models, respectively, though several models in each category had similar adjusted- R 2 values. All three of the best-performing models contained CS. Vision in glaucoma is a multidimensional construct that can be described by several variably-correlated vision measures. Measuring more than two vision tests does not substantially improve models for activity limitation. A sufficient description of disability in glaucoma can be obtained using one to two vision tests, especially VF and CS.

Multiperson visual focus of attention from head pose and meeting contextual cues.

PubMed

Ba, Sileye O; Odobez, Jean-Marc

2011-01-01

This paper introduces a novel contextual model for the recognition of people's visual focus of attention (VFOA) in meetings from audio-visual perceptual cues. More specifically, instead of independently recognizing the VFOA of each meeting participant from his own head pose, we propose to jointly recognize the participants' visual attention in order to introduce context-dependent interaction models that relate to group activity and the social dynamics of communication. Meeting contextual information is represented by the location of people, conversational events identifying floor holding patterns, and a presentation activity variable. By modeling the interactions between the different contexts and their combined and sometimes contradictory impact on the gazing behavior, our model allows us to handle VFOA recognition in difficult task-based meetings involving artifacts, presentations, and moving people. We validated our model through rigorous evaluation on a publicly available and challenging data set of 12 real meetings (5 hours of data). The results demonstrated that the integration of the presentation and conversation dynamical context using our model can lead to significant performance improvements.

Automation for System Safety Analysis

NASA Technical Reports Server (NTRS)

Malin, Jane T.; Fleming, Land; Throop, David; Thronesbery, Carroll; Flores, Joshua; Bennett, Ted; Wennberg, Paul

2009-01-01

This presentation describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

Two-dimensional hidden semantic information model for target saliency detection and eyetracking identification

NASA Astrophysics Data System (ADS)

Wan, Weibing; Yuan, Lingfeng; Zhao, Qunfei; Fang, Tao

2018-01-01

Saliency detection has been applied to the target acquisition case. This paper proposes a two-dimensional hidden Markov model (2D-HMM) that exploits the hidden semantic information of an image to detect its salient regions. A spatial pyramid histogram of oriented gradient descriptors is used to extract features. After encoding the image by a learned dictionary, the 2D-Viterbi algorithm is applied to infer the saliency map. This model can predict fixation of the targets and further creates robust and effective depictions of the targets' change in posture and viewpoint. To validate the model with a human visual search mechanism, two eyetrack experiments are employed to train our model directly from eye movement data. The results show that our model achieves better performance than visual attention. Moreover, it indicates the plausibility of utilizing visual track data to identify targets.

Performance analysis and optimization of an advanced pharmaceutical wastewater treatment plant through a visual basic software tool (PWWT.VB).

PubMed

Pal, Parimal; Thakura, Ritwik; Chakrabortty, Sankha

2016-05-01

A user-friendly, menu-driven simulation software tool has been developed for the first time to optimize and analyze the system performance of an advanced continuous membrane-integrated pharmaceutical wastewater treatment plant. The software allows pre-analysis and manipulation of input data which helps in optimization and shows the software performance visually on a graphical platform. Moreover, the software helps the user to "visualize" the effects of the operating parameters through its model-predicted output profiles. The software is based on a dynamic mathematical model, developed for a systematically integrated forward osmosis-nanofiltration process for removal of toxic organic compounds from pharmaceutical wastewater. The model-predicted values have been observed to corroborate well with the extensive experimental investigations which were found to be consistent under varying operating conditions like operating pressure, operating flow rate, and draw solute concentration. Low values of the relative error (RE = 0.09) and high values of Willmott-d-index (d will = 0.981) reflected a high degree of accuracy and reliability of the software. This software is likely to be a very efficient tool for system design or simulation of an advanced membrane-integrated treatment plant for hazardous wastewater.

Lexical decision with pseudohomophones and reading in the semantic variant of primary progressive aphasia: A double dissociation.

PubMed

Boukadi, Mariem; Potvin, Karel; Macoir, Joël; Jr Laforce, Robert; Poulin, Stéphane; Brambati, Simona M; Wilson, Maximiliano A

2016-06-01

The co-occurrence of semantic impairment and surface dyslexia in the semantic variant of primary progressive aphasia (svPPA) has often been taken as supporting evidence for the central role of semantics in visual word processing. According to connectionist models, semantic access is needed to accurately read irregular words. They also postulate that reliance on semantics is necessary to perform the lexical decision task under certain circumstances (for example, when the stimulus list comprises pseudohomophones). In the present study, we report two svPPA cases: M.F. who presented with surface dyslexia but performed accurately on the lexical decision task with pseudohomophones, and R.L. who showed no surface dyslexia but performed below the normal range on the lexical decision task with pseudohomophones. This double dissociation between reading and lexical decision with pseudohomophones is in line with the dual-route cascaded (DRC) model of reading. According to this model, impairments in visual word processing in svPPA are not necessarily associated with the semantic deficits characterizing this disease. Our findings also call into question the central role given to semantics in visual word processing within the connectionist account. Copyright © 2016 Elsevier Ltd. All rights reserved.

A neural-visualization IDS for honeynet data.

PubMed

Herrero, Álvaro; Zurutuza, Urko; Corchado, Emilio

2012-04-01

Neural intelligent systems can provide a visualization of the network traffic for security staff, in order to reduce the widely known high false-positive rate associated with misuse-based Intrusion Detection Systems (IDSs). Unlike previous work, this study proposes an unsupervised neural models that generate an intuitive visualization of the captured traffic, rather than network statistics. These snapshots of network events are immensely useful for security personnel that monitor network behavior. The system is based on the use of different neural projection and unsupervised methods for the visual inspection of honeypot data, and may be seen as a complementary network security tool that sheds light on internal data structures through visual inspection of the traffic itself. Furthermore, it is intended to facilitate verification and assessment of Snort performance (a well-known and widely-used misuse-based IDS), through the visualization of attack patterns. Empirical verification and comparison of the proposed projection methods are performed in a real domain, where two different case studies are defined and analyzed.

An Architectural Model of Visual Motion Understanding

DTIC Science & Technology

1989-08-01

of the Center for Visual Sciences of the University of Rochester. Their courage in the face of the overwhelming com- plexity of the human visual...analysis should perform better than either approach by itself. Notice that the problems of the two approaches are non-overlapping. Continuous methods face no...success. This is not terribly surprising, as the problem is inherently very difficult. Consider the problems faced by a unit that is trying to compute the

Global Image Dissimilarity in Macaque Inferotemporal Cortex Predicts Human Visual Search Efficiency

PubMed Central

Sripati, Arun P.; Olson, Carl R.

2010-01-01

Finding a target in a visual scene can be easy or difficult depending on the nature of the distractors. Research in humans has suggested that search is more difficult the more similar the target and distractors are to each other. However, it has not yielded an objective definition of similarity. We hypothesized that visual search performance depends on similarity as determined by the degree to which two images elicit overlapping patterns of neuronal activity in visual cortex. To test this idea, we recorded from neurons in monkey inferotemporal cortex (IT) and assessed visual search performance in humans using pairs of images formed from the same local features in different global arrangements. The ability of IT neurons to discriminate between two images was strongly predictive of the ability of humans to discriminate between them during visual search, accounting overall for 90% of the variance in human performance. A simple physical measure of global similarity – the degree of overlap between the coarse footprints of a pair of images – largely explains both the neuronal and the behavioral results. To explain the relation between population activity and search behavior, we propose a model in which the efficiency of global oddball search depends on contrast-enhancing lateral interactions in high-order visual cortex. PMID:20107054

Decontaminate feature for tracking: adaptive tracking via evolutionary feature subset

NASA Astrophysics Data System (ADS)

Liu, Qiaoyuan; Wang, Yuru; Yin, Minghao; Ren, Jinchang; Li, Ruizhi

2017-11-01

Although various visual tracking algorithms have been proposed in the last 2-3 decades, it remains a challenging problem for effective tracking with fast motion, deformation, occlusion, etc. Under complex tracking conditions, most tracking models are not discriminative and adaptive enough. When the combined feature vectors are inputted to the visual models, this may lead to redundancy causing low efficiency and ambiguity causing poor performance. An effective tracking algorithm is proposed to decontaminate features for each video sequence adaptively, where the visual modeling is treated as an optimization problem from the perspective of evolution. Every feature vector is compared to a biological individual and then decontaminated via classical evolutionary algorithms. With the optimized subsets of features, the "curse of dimensionality" has been avoided while the accuracy of the visual model has been improved. The proposed algorithm has been tested on several publicly available datasets with various tracking challenges and benchmarked with a number of state-of-the-art approaches. The comprehensive experiments have demonstrated the efficacy of the proposed methodology.

Fused methods for visual saliency estimation

NASA Astrophysics Data System (ADS)

Danko, Amanda S.; Lyu, Siwei

2015-02-01

In this work, we present a new model of visual saliency by combing results from existing methods, improving upon their performance and accuracy. By fusing pre-attentive and context-aware methods, we highlight the abilities of state-of-the-art models while compensating for their deficiencies. We put this theory to the test in a series of experiments, comparatively evaluating the visual saliency maps and employing them for content-based image retrieval and thumbnail generation. We find that on average our model yields definitive improvements upon recall and f-measure metrics with comparable precisions. In addition, we find that all image searches using our fused method return more correct images and additionally rank them higher than the searches using the original methods alone.

Simulation and visualization of energy-related occupant behavior in office buildings

DOE PAGES

Chen, Yixing; Liang, Xin; Hong, Tianzhen; ...

2017-03-15

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each spacemore » as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. Furthermore, the presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.« less

Simulation and visualization of energy-related occupant behavior in office buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Yixing; Liang, Xin; Hong, Tianzhen

In current building performance simulation programs, occupant presence and interactions with building systems are over-simplified and less indicative of real world scenarios, contributing to the discrepancies between simulated and actual energy use in buildings. Simulation results are normally presented using various types of charts. However, using those charts, it is difficult to visualize and communicate the importance of occupants’ behavior to building energy performance. This study introduced a new approach to simulating and visualizing energy-related occupant behavior in office buildings. First, the Occupancy Simulator was used to simulate the occupant presence and movement and generate occupant schedules for each spacemore » as well as for each occupant. Then an occupant behavior functional mockup unit (obFMU) was used to model occupant behavior and analyze their impact on building energy use through co-simulation with EnergyPlus. Finally, an agent-based model built upon AnyLogic was applied to visualize the simulation results of the occupant movement and interactions with building systems, as well as the related energy performance. A case study using a small office building in Miami, FL was presented to demonstrate the process and application of the Occupancy Simulator, the obFMU and EnergyPlus, and the AnyLogic module in simulation and visualization of energy-related occupant behaviors in office buildings. Furthermore, the presented approach provides a new detailed and visual way for policy makers, architects, engineers and building operators to better understand occupant energy behavior and their impact on energy use in buildings, which can improve the design and operation of low energy buildings.« less

Hybrid simulated annealing and its application to optimization of hidden Markov models for visual speech recognition.

PubMed

Lee, Jong-Seok; Park, Cheol Hoon

2010-08-01

We propose a novel stochastic optimization algorithm, hybrid simulated annealing (SA), to train hidden Markov models (HMMs) for visual speech recognition. In our algorithm, SA is combined with a local optimization operator that substitutes a better solution for the current one to improve the convergence speed and the quality of solutions. We mathematically prove that the sequence of the objective values converges in probability to the global optimum in the algorithm. The algorithm is applied to train HMMs that are used as visual speech recognizers. While the popular training method of HMMs, the expectation-maximization algorithm, achieves only local optima in the parameter space, the proposed method can perform global optimization of the parameters of HMMs and thereby obtain solutions yielding improved recognition performance. The superiority of the proposed algorithm to the conventional ones is demonstrated via isolated word recognition experiments.

Real-Time Performance Feedback for the Manual Control of Spacecraft

NASA Astrophysics Data System (ADS)

Karasinski, John Austin

Real-time performance metrics were developed to quantify workload, situational awareness, and manual task performance for use as visual feedback to pilots of aerospace vehicles. Results from prior lunar lander experiments with variable levels of automation were replicated and extended to provide insights for the development of real-time metrics. Increased levels of automation resulted in increased flight performance, lower workload, and increased situational awareness. Automated Speech Recognition (ASR) was employed to detect verbal callouts as a limited measure of subjects' situational awareness. A one-dimensional manual tracking task and simple instructor-model visual feedback scheme was developed. This feedback was indicated to the operator by changing the color of a guidance element on the primary flight display, similar to how a flight instructor points out elements of a display to a student pilot. Experiments showed that for this low-complexity task, visual feedback did not change subject performance, but did increase the subjects' measured workload. Insights gained from these experiments were applied to a Simplified Aid for EVA Rescue (SAFER) inspection task. The effects of variations of an instructor-model performance-feedback strategy on human performance in a novel SAFER inspection task were investigated. Real-time feedback was found to have a statistically significant effect of improving subject performance and decreasing workload in this complicated four degree of freedom manual control task with two secondary tasks.

Remote Sensing of Martian Terrain Hazards via Visually Salient Feature Detection

NASA Astrophysics Data System (ADS)

Al-Milli, S.; Shaukat, A.; Spiteri, C.; Gao, Y.

2014-04-01

The main objective of the FASTER remote sensing system is the detection of rocks on planetary surfaces by employing models that can efficiently characterise rocks in terms of semantic descriptions. The proposed technique abates some of the algorithmic limitations of existing methods with no training requirements, lower computational complexity and greater robustness towards visual tracking applications over long-distance planetary terrains. Visual saliency models inspired from biological systems help to identify important regions (such as rocks) in the visual scene. Surface rocks are therefore completely described in terms of their local or global conspicuity pop-out characteristics. These local and global pop-out cues are (but not limited to); colour, depth, orientation, curvature, size, luminance intensity, shape, topology etc. The currently applied methods follow a purely bottom-up strategy of visual attention for selection of conspicuous regions in the visual scene without any topdown control. Furthermore the choice of models used (tested and evaluated) are relatively fast among the state-of-the-art and have very low computational load. Quantitative evaluation of these state-ofthe- art models was carried out using benchmark datasets including the Surrey Space Centre Lab Testbed, Pangu generated images, RAL Space SEEKER and CNES Mars Yard datasets. The analysis indicates that models based on visually salient information in the frequency domain (SRA, SDSR, PQFT) are the best performing ones for detecting rocks in an extra-terrestrial setting. In particular the SRA model seems to be the most optimum of the lot especially that it requires the least computational time while keeping errors competitively low. The salient objects extracted using these models can then be merged with the Digital Elevation Models (DEMs) generated from the same navigation cameras in order to be fused to the navigation map thus giving a clear indication of the rock locations.

VFMA: Topographic Analysis of Sensitivity Data From Full-Field Static Perimetry

PubMed Central

Weleber, Richard G.; Smith, Travis B.; Peters, Dawn; Chegarnov, Elvira N.; Gillespie, Scott P.; Francis, Peter J.; Gardiner, Stuart K.; Paetzold, Jens; Dietzsch, Janko; Schiefer, Ulrich; Johnson, Chris A.

2015-01-01

Purpose: To analyze static visual field sensitivity with topographic models of the hill of vision (HOV), and to characterize several visual function indices derived from the HOV volume. Methods: A software application, Visual Field Modeling and Analysis (VFMA), was developed for static perimetry data visualization and analysis. Three-dimensional HOV models were generated for 16 healthy subjects and 82 retinitis pigmentosa patients. Volumetric visual function indices, which are measures of quantity and comparable regardless of perimeter test pattern, were investigated. Cross-validation, reliability, and cross-sectional analyses were performed to assess this methodology and compare the volumetric indices to conventional mean sensitivity and mean deviation. Floor effects were evaluated by computer simulation. Results: Cross-validation yielded an overall R2 of 0.68 and index of agreement of 0.89, which were consistent among subject groups, indicating good accuracy. Volumetric and conventional indices were comparable in terms of test–retest variability and discriminability among subject groups. Simulated floor effects did not negatively impact the repeatability of any index, but large floor changes altered the discriminability for regional volumetric indices. Conclusions: VFMA is an effective tool for clinical and research analyses of static perimetry data. Topographic models of the HOV aid the visualization of field defects, and topographically derived indices quantify the magnitude and extent of visual field sensitivity. Translational Relevance: VFMA assists with the interpretation of visual field data from any perimetric device and any test location pattern. Topographic models and volumetric indices are suitable for diagnosis, monitoring of field loss, patient counseling, and endpoints in therapeutic trials. PMID:25938002

Introducing memory and association mechanism into a biologically inspired visual model.

PubMed

Qiao, Hong; Li, Yinlin; Tang, Tang; Wang, Peng

2014-09-01

A famous biologically inspired hierarchical model (HMAX model), which was proposed recently and corresponds to V1 to V4 of the ventral pathway in primate visual cortex, has been successfully applied to multiple visual recognition tasks. The model is able to achieve a set of position- and scale-tolerant recognition, which is a central problem in pattern recognition. In this paper, based on some other biological experimental evidence, we introduce the memory and association mechanism into the HMAX model. The main contributions of the work are: 1) mimicking the active memory and association mechanism and adding the top down adjustment to the HMAX model, which is the first try to add the active adjustment to this famous model and 2) from the perspective of information, algorithms based on the new model can reduce the computation storage and have a good recognition performance. The new model is also applied to object recognition processes. The primary experimental results show that our method is efficient with a much lower memory requirement.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

NASA Astrophysics Data System (ADS)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

A biologically inspired neural model for visual and proprioceptive integration including sensory training.

PubMed

Saidi, Maryam; Towhidkhah, Farzad; Gharibzadeh, Shahriar; Lari, Abdolaziz Azizi

2013-12-01

Humans perceive the surrounding world by integration of information through different sensory modalities. Earlier models of multisensory integration rely mainly on traditional Bayesian and causal Bayesian inferences for single causal (source) and two causal (for two senses such as visual and auditory systems), respectively. In this paper a new recurrent neural model is presented for integration of visual and proprioceptive information. This model is based on population coding which is able to mimic multisensory integration of neural centers in the human brain. The simulation results agree with those achieved by casual Bayesian inference. The model can also simulate the sensory training process of visual and proprioceptive information in human. Training process in multisensory integration is a point with less attention in the literature before. The effect of proprioceptive training on multisensory perception was investigated through a set of experiments in our previous study. The current study, evaluates the effect of both modalities, i.e., visual and proprioceptive training and compares them with each other through a set of new experiments. In these experiments, the subject was asked to move his/her hand in a circle and estimate its position. The experiments were performed on eight subjects with proprioception training and eight subjects with visual training. Results of the experiments show three important points: (1) visual learning rate is significantly more than that of proprioception; (2) means of visual and proprioceptive errors are decreased by training but statistical analysis shows that this decrement is significant for proprioceptive error and non-significant for visual error, and (3) visual errors in training phase even in the beginning of it, is much less than errors of the main test stage because in the main test, the subject has to focus on two senses. The results of the experiments in this paper is in agreement with the results of the neural model simulation.

Learning invariance from natural images inspired by observations in the primary visual cortex.

PubMed

Teichmann, Michael; Wiltschut, Jan; Hamker, Fred

2012-05-01

The human visual system has the remarkable ability to largely recognize objects invariant of their position, rotation, and scale. A good interpretation of neurobiological findings involves a computational model that simulates signal processing of the visual cortex. In part, this is likely achieved step by step from early to late areas of visual perception. While several algorithms have been proposed for learning feature detectors, only few studies at hand cover the issue of biologically plausible learning of such invariance. In this study, a set of Hebbian learning rules based on calcium dynamics and homeostatic regulations of single neurons is proposed. Their performance is verified within a simple model of the primary visual cortex to learn so-called complex cells, based on a sequence of static images. As a result, the learned complex-cell responses are largely invariant to phase and position.

Combined influence of visual scene and body tilt on arm pointing movements: gravity matters!

PubMed

Scotto Di Cesare, Cécile; Sarlegna, Fabrice R; Bourdin, Christophe; Mestre, Daniel R; Bringoux, Lionel

2014-01-01

Performing accurate actions such as goal-directed arm movements requires taking into account visual and body orientation cues to localize the target in space and produce appropriate reaching motor commands. We experimentally tilted the body and/or the visual scene to investigate how visual and body orientation cues are combined for the control of unseen arm movements. Subjects were asked to point toward a visual target using an upward movement during slow body and/or visual scene tilts. When the scene was tilted, final pointing errors varied as a function of the direction of the scene tilt (forward or backward). Actual forward body tilt resulted in systematic target undershoots, suggesting that the brain may have overcompensated for the biomechanical movement facilitation arising from body tilt. Combined body and visual scene tilts also affected final pointing errors according to the orientation of the visual scene. The data were further analysed using either a body-centered or a gravity-centered reference frame to encode visual scene orientation with simple additive models (i.e., 'combined' tilts equal to the sum of 'single' tilts). We found that the body-centered model could account only for some of the data regarding kinematic parameters and final errors. In contrast, the gravity-centered modeling in which the body and visual scene orientations were referred to vertical could explain all of these data. Therefore, our findings suggest that the brain uses gravity, thanks to its invariant properties, as a reference for the combination of visual and non-visual cues.

Combined Influence of Visual Scene and Body Tilt on Arm Pointing Movements: Gravity Matters!

PubMed Central

Scotto Di Cesare, Cécile; Sarlegna, Fabrice R.; Bourdin, Christophe; Mestre, Daniel R.; Bringoux, Lionel

2014-01-01

Performing accurate actions such as goal-directed arm movements requires taking into account visual and body orientation cues to localize the target in space and produce appropriate reaching motor commands. We experimentally tilted the body and/or the visual scene to investigate how visual and body orientation cues are combined for the control of unseen arm movements. Subjects were asked to point toward a visual target using an upward movement during slow body and/or visual scene tilts. When the scene was tilted, final pointing errors varied as a function of the direction of the scene tilt (forward or backward). Actual forward body tilt resulted in systematic target undershoots, suggesting that the brain may have overcompensated for the biomechanical movement facilitation arising from body tilt. Combined body and visual scene tilts also affected final pointing errors according to the orientation of the visual scene. The data were further analysed using either a body-centered or a gravity-centered reference frame to encode visual scene orientation with simple additive models (i.e., ‘combined’ tilts equal to the sum of ‘single’ tilts). We found that the body-centered model could account only for some of the data regarding kinematic parameters and final errors. In contrast, the gravity-centered modeling in which the body and visual scene orientations were referred to vertical could explain all of these data. Therefore, our findings suggest that the brain uses gravity, thanks to its invariant properties, as a reference for the combination of visual and non-visual cues. PMID:24925371

Development of a computational model on the neural activity patterns of a visual working memory in a hierarchical feedforward Network

NASA Astrophysics Data System (ADS)

An, Soyoung; Choi, Woochul; Paik, Se-Bum

2015-11-01

Understanding the mechanism of information processing in the human brain remains a unique challenge because the nonlinear interactions between the neurons in the network are extremely complex and because controlling every relevant parameter during an experiment is difficult. Therefore, a simulation using simplified computational models may be an effective approach. In the present study, we developed a general model of neural networks that can simulate nonlinear activity patterns in the hierarchical structure of a neural network system. To test our model, we first examined whether our simulation could match the previously-observed nonlinear features of neural activity patterns. Next, we performed a psychophysics experiment for a simple visual working memory task to evaluate whether the model could predict the performance of human subjects. Our studies show that the model is capable of reproducing the relationship between memory load and performance and may contribute, in part, to our understanding of how the structure of neural circuits can determine the nonlinear neural activity patterns in the human brain.

Detection and recognition of simple spatial forms

NASA Technical Reports Server (NTRS)

Watson, A. B.

1983-01-01

A model of human visual sensitivity to spatial patterns is constructed. The model predicts the visibility and discriminability of arbitrary two-dimensional monochrome images. The image is analyzed by a large array of linear feature sensors, which differ in spatial frequency, phase, orientation, and position in the visual field. All sensors have one octave frequency bandwidths, and increase in size linearly with eccentricity. Sensor responses are processed by an ideal Bayesian classifier, subject to uncertainty. The performance of the model is compared to that of the human observer in detecting and discriminating some simple images.

A visual tracking method based on deep learning without online model updating

NASA Astrophysics Data System (ADS)

Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

2018-02-01

The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

Visualizing Compound Rotations with Virtual Reality

ERIC Educational Resources Information Center

Flanders, Megan; Kavanagh, Richard C.

2013-01-01

Mental rotations are among the most difficult of all spatial tasks to perform, and even those with high levels of spatial ability can struggle to visualize the result of compound rotations. This pilot study investigates the use of the virtual reality-based Rotation Tool, created using the Virtual Reality Modeling Language (VRML) together with…

The Interplay between Methodologies, Tasks and Visualisation Formats in the Study of Visual Expertise

ERIC Educational Resources Information Center

Boucheix, Jean-Michel

2017-01-01

This article introduces this special issue of "Frontline Learning Research." The first paper offers a methodological guide using Ericsson & Smith's (1991) "expert performance approach." This is followed by three papers that analyze the use of eye tracking in visual expertise models, and a paper reviewing the use of methods…

ERP Evidence of Hemispheric Independence in Visual Word Recognition

ERIC Educational Resources Information Center

Nemrodov, Dan; Harpaz, Yuval; Javitt, Daniel C.; Lavidor, Michal

2011-01-01

This study examined the capability of the left hemisphere (LH) and the right hemisphere (RH) to perform a visual recognition task independently as formulated by the Direct Access Model (Fernandino, Iacoboni, & Zaidel, 2007). Healthy native Hebrew speakers were asked to categorize nouns and non-words (created from nouns by transposing two middle…

Technique for Measuring Speed and Visual Motion Sensitivity in Lizards

ERIC Educational Resources Information Center

Woo, Kevin L.; Burke, Darren

2008-01-01

Testing sensory characteristics on herpetological species has been difficult due to a range of properties related to physiology, responsiveness, performance ability, and the type of reinforcer used. Using the Jacky lizard as a model, we outline a successfully established procedure in which to test the visual sensitivity to motion characteristics.…

On-chip visual perception of motion: a bio-inspired connectionist model on FPGA.

PubMed

Torres-Huitzil, César; Girau, Bernard; Castellanos-Sánchez, Claudio

2005-01-01

Visual motion provides useful information to understand the dynamics of a scene to allow intelligent systems interact with their environment. Motion computation is usually restricted by real time requirements that need the design and implementation of specific hardware architectures. In this paper, the design of hardware architecture for a bio-inspired neural model for motion estimation is presented. The motion estimation is based on a strongly localized bio-inspired connectionist model with a particular adaptation of spatio-temporal Gabor-like filtering. The architecture is constituted by three main modules that perform spatial, temporal, and excitatory-inhibitory connectionist processing. The biomimetic architecture is modeled, simulated and validated in VHDL. The synthesis results on a Field Programmable Gate Array (FPGA) device show the potential achievement of real-time performance at an affordable silicon area.

Edge Detection Based On the Characteristic of Primary Visual Cortex Cells

NASA Astrophysics Data System (ADS)

Zhu, M. M.; Xu, Y. L.; Ma, H. Q.

2018-01-01

Aiming at the problem that it is difficult to balance the accuracy of edge detection and anti-noise performance, and referring to the dynamic and static perceptions of the primary visual cortex (V1) cells, a V1 cell model is established to perform edge detection. A spatiotemporal filter is adopted to simulate the receptive field of V1 simple cells, the model V1 cell is obtained after integrating the responses of simple cells by half-wave rectification and normalization, Then the natural image edge is detected by using static perception of V1 cells. The simulation results show that, the V1 model can basically fit the biological data and has the universality of biology. What’s more, compared with other edge detection operators, the proposed model is more effective and has better robustness

DspaceOgre 3D Graphics Visualization Tool

NASA Technical Reports Server (NTRS)

Jain, Abhinandan; Myin, Steven; Pomerantz, Marc I.

2011-01-01

This general-purpose 3D graphics visualization C++ tool is designed for visualization of simulation and analysis data for articulated mechanisms. Examples of such systems are vehicles, robotic arms, biomechanics models, and biomolecular structures. DspaceOgre builds upon the open-source Ogre3D graphics visualization library. It provides additional classes to support the management of complex scenes involving multiple viewpoints and different scene groups, and can be used as a remote graphics server. This software provides improved support for adding programs at the graphics processing unit (GPU) level for improved performance. It also improves upon the messaging interface it exposes for use as a visualization server.

Cross-Modal Retrieval With CNN Visual Features: A New Baseline.

PubMed

Wei, Yunchao; Zhao, Yao; Lu, Canyi; Wei, Shikui; Liu, Luoqi; Zhu, Zhenfeng; Yan, Shuicheng

2017-02-01

Recently, convolutional neural network (CNN) visual features have demonstrated their powerful ability as a universal representation for various recognition tasks. In this paper, cross-modal retrieval with CNN visual features is implemented with several classic methods. Specifically, off-the-shelf CNN visual features are extracted from the CNN model, which is pretrained on ImageNet with more than one million images from 1000 object categories, as a generic image representation to tackle cross-modal retrieval. To further enhance the representational ability of CNN visual features, based on the pretrained CNN model on ImageNet, a fine-tuning step is performed by using the open source Caffe CNN library for each target data set. Besides, we propose a deep semantic matching method to address the cross-modal retrieval problem with respect to samples which are annotated with one or multiple labels. Extensive experiments on five popular publicly available data sets well demonstrate the superiority of CNN visual features for cross-modal retrieval.

Performance of Single-Use FlexorVue vs Reusable BoaVision Ureteroscope for Visualization of Calices and Stone Extraction in an Artificial Kidney Model.

PubMed

Schlager, Daniel; Hein, Simon; Obaid, Moaaz Abdulghani; Wilhelm, Konrad; Miernik, Arkadiusz; Schoenthaler, Martin

2017-11-01

To evaluate and compare Flexor ® Vue™, a semidisposable endoscopic deflection system with disposable ureteral sheath and reusable visualization source, and a nondisposable fiber optic ureteroscope in a standard in vitro setting. FlexorVue and a reusable fiber optic flexible ureteroscope were each tested in an artificial kidney model. The experimental setup included the visualization of colored pearls and the extraction of calculi with two different extraction devices (NCircle ® and NGage ® ). The procedures were performed by six experienced surgeons. Visualization time, access to calices, successful stone retraction, and time required were recorded. In addition, the surgeons' workload and subjective performance were determined according to the National Aeronautics and Space Administration-task load index (NASA-TLX). We referred to the Likert scale to assess maneuverability, handling, and image quality. Nearly all calices (99%) were correctly identified using the reusable scope, indicating full kidney access, whereas 74% of the calices were visualized using FlexorVue, of which 81% were correctly identified. Access to the lower poles of the kidney model was significantly less likely with the disposable device, and time to completion was significantly longer (755 s vs 153 s, p < 0.001). The stone clearance success rate with the disposable device was 23% using the NGage and 13% using the NCircle basket. Overall NASA-TLX scores were significantly higher using FlexorVue. The conventional reusable device also demonstrated superior maneuverability, handling, and image quality. FlexorVue offers a semidisposable deflecting endoscopic system allowing basic ureteroscopic and cystoscopic procedures. For its use as an addition or replacement for current reusable scopes, it requires substantial technical improvements.

Extensions to the visual predictive check to facilitate model performance evaluation.

PubMed

Post, Teun M; Freijer, Jan I; Ploeger, Bart A; Danhof, Meindert

2008-04-01

The Visual Predictive Check (VPC) is a valuable and supportive instrument for evaluating model performance. However in its most commonly applied form, the method largely depends on a subjective comparison of the distribution of the simulated data with the observed data, without explicitly quantifying and relating the information in both. In recent adaptations to the VPC this drawback is taken into consideration by presenting the observed and predicted data as percentiles. In addition, in some of these adaptations the uncertainty in the predictions is represented visually. However, it is not assessed whether the expected random distribution of the observations around the predicted median trend is realised in relation to the number of observations. Moreover the influence of and the information residing in missing data at each time point is not taken into consideration. Therefore, in this investigation the VPC is extended with two methods to support a less subjective and thereby more adequate evaluation of model performance: (i) the Quantified Visual Predictive Check (QVPC) and (ii) the Bootstrap Visual Predictive Check (BVPC). The QVPC presents the distribution of the observations as a percentage, thus regardless the density of the data, above and below the predicted median at each time point, while also visualising the percentage of unavailable data. The BVPC weighs the predicted median against the 5th, 50th and 95th percentiles resulting from a bootstrap of the observed data median at each time point, while accounting for the number and the theoretical position of unavailable data. The proposed extensions to the VPC are illustrated by a pharmacokinetic simulation example and applied to a pharmacodynamic disease progression example.

Invariant recognition drives neural representations of action sequences

PubMed Central

Poggio, Tomaso

2017-01-01

Recognizing the actions of others from visual stimuli is a crucial aspect of human perception that allows individuals to respond to social cues. Humans are able to discriminate between similar actions despite transformations, like changes in viewpoint or actor, that substantially alter the visual appearance of a scene. This ability to generalize across complex transformations is a hallmark of human visual intelligence. Advances in understanding action recognition at the neural level have not always translated into precise accounts of the computational principles underlying what representations of action sequences are constructed by human visual cortex. Here we test the hypothesis that invariant action discrimination might fill this gap. Recently, the study of artificial systems for static object perception has produced models, Convolutional Neural Networks (CNNs), that achieve human level performance in complex discriminative tasks. Within this class, architectures that better support invariant object recognition also produce image representations that better match those implied by human and primate neural data. However, whether these models produce representations of action sequences that support recognition across complex transformations and closely follow neural representations of actions remains unknown. Here we show that spatiotemporal CNNs accurately categorize video stimuli into action classes, and that deliberate model modifications that improve performance on an invariant action recognition task lead to data representations that better match human neural recordings. Our results support our hypothesis that performance on invariant discrimination dictates the neural representations of actions computed in the brain. These results broaden the scope of the invariant recognition framework for understanding visual intelligence from perception of inanimate objects and faces in static images to the study of human perception of action sequences. PMID:29253864

A Causal Inference Model Explains Perception of the McGurk Effect and Other Incongruent Audiovisual Speech.

PubMed

Magnotti, John F; Beauchamp, Michael S

2017-02-01

Audiovisual speech integration combines information from auditory speech (talker's voice) and visual speech (talker's mouth movements) to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory "ba" + visual "ga" (AbaVga), that are integrated to produce a fused percept ("da"). This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated; and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba). We describe a simplified model of causal inference in multisensory speech perception (CIMS) that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.

Visual learning in drosophila: application on a roving robot and comparisons

NASA Astrophysics Data System (ADS)

Arena, P.; De Fiore, S.; Patané, L.; Termini, P. S.; Strauss, R.

2011-05-01

Visual learning is an important aspect of fly life. Flies are able to extract visual cues from objects, like colors, vertical and horizontal distributedness, and others, that can be used for learning to associate a meaning to specific features (i.e. a reward or a punishment). Interesting biological experiments show trained stationary flying flies avoiding flying towards specific visual objects, appearing on the surrounding environment. Wild-type flies effectively learn to avoid those objects but this is not the case for the learning mutant rutabaga defective in the cyclic AMP dependent pathway for plasticity. A bio-inspired architecture has been proposed to model the fly behavior and experiments on roving robots were performed. Statistical comparisons have been considered and mutant-like effect on the model has been also investigated.

CheS-Mapper 2.0 for visual validation of (Q)SAR models

PubMed Central

2014-01-01

Background Sound statistical validation is important to evaluate and compare the overall performance of (Q)SAR models. However, classical validation does not support the user in better understanding the properties of the model or the underlying data. Even though, a number of visualization tools for analyzing (Q)SAR information in small molecule datasets exist, integrated visualization methods that allow the investigation of model validation results are still lacking. Results We propose visual validation, as an approach for the graphical inspection of (Q)SAR model validation results. The approach applies the 3D viewer CheS-Mapper, an open-source application for the exploration of small molecules in virtual 3D space. The present work describes the new functionalities in CheS-Mapper 2.0, that facilitate the analysis of (Q)SAR information and allows the visual validation of (Q)SAR models. The tool enables the comparison of model predictions to the actual activity in feature space. The approach is generic: It is model-independent and can handle physico-chemical and structural input features as well as quantitative and qualitative endpoints. Conclusions Visual validation with CheS-Mapper enables analyzing (Q)SAR information in the data and indicates how this information is employed by the (Q)SAR model. It reveals, if the endpoint is modeled too specific or too generic and highlights common properties of misclassified compounds. Moreover, the researcher can use CheS-Mapper to inspect how the (Q)SAR model predicts activity cliffs. The CheS-Mapper software is freely available at http://ches-mapper.org. Graphical abstract Comparing actual and predicted activity values with CheS-Mapper.

Vision in laboratory rodents-Tools to measure it and implications for behavioral research.

PubMed

Leinonen, Henri; Tanila, Heikki

2017-07-29

Mice and rats are nocturnal mammals and their vision is specialized for detection of motion and contrast in dim light conditions. These species possess a large proportion of UV-sensitive cones in their retinas and the majority of their optic nerve axons target superior colliculus rather than visual cortex. Therefore, it was a widely held belief that laboratory rodents hardly utilize vision during day-time behavior. This dogma is being questioned as accumulating evidence suggests that laboratory rodents are able to perform complex visual functions, such as perceiving subjective contours, and that declined vision may affect their performance in many behavioral tasks. For instance, genetic engineering may have unexpected consequences on vision as mouse models of Alzheimer's and Huntington's diseases have declined visual function. Rodent vision can be tested in numerous ways using operant training or reflex-based behavioral tasks, or alternatively using electrophysiological recordings. In this article, we will first provide a summary of visual system and explain its characteristics unique to rodents. Then, we present well-established techniques to test rodent vision, with an emphasis on pattern vision: visual water test, optomotor reflex test, pattern electroretinography and pattern visual evoked potentials. Finally, we highlight the importance of visual phenotyping in rodents. As the number of genetically engineered rodent models and volume of behavioral testing increase simultaneously, the possibility of visual dysfunctions needs to be addressed. Neglect in this matter potentially leads to crude biases in the field of neuroscience and beyond. Copyright © 2017 Elsevier B.V. All rights reserved.

A model for the pilot's use of motion cues in roll-axis tracking tasks

NASA Technical Reports Server (NTRS)

Levison, W. H.; Junker, A. M.

1977-01-01

Simulated target-following and disturbance-regulation tasks were explored with subjects using visual-only and combined visual and motion cues. The effects of motion cues on task performance and pilot response behavior were appreciably different for the two task configurations and were consistent with data reported in earlier studies for similar task configurations. The optimal-control model for pilot/vehicle systems provided a task-independent framework for accounting for the pilot's use of motion cues. Specifically, the availability of motion cues was modeled by augmenting the set of perceptual variables to include position, rate, acceleration, and accleration-rate of the motion simulator, and results were consistent with the hypothesis of attention-sharing between visual and motion variables. This straightforward informational model allowed accurate model predictions of the effects of motion cues on a variety of response measures for both the target-following and disturbance-regulation tasks.

A neurophysiologically plausible population code model for feature integration explains visual crowding.

PubMed

van den Berg, Ronald; Roerdink, Jos B T M; Cornelissen, Frans W

2010-01-22

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called "crowding". Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, "compulsory averaging", and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality.

How spatial abilities and dynamic visualizations interplay when learning functional anatomy with 3D anatomical models.

PubMed

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material presentation formats, spatial abilities, and anatomical tasks. First, to understand the cognitive challenges a novice learner would be faced with when first exposed to 3D anatomical content, a six-step cognitive task analysis was developed. Following this, an experimental study was conducted to explore how presentation formats (dynamic vs. static visualizations) support learning of functional anatomy, and affect subsequent anatomical tasks derived from the cognitive task analysis. A second aim was to investigate the interplay between spatial abilities (spatial visualization and spatial relation) and presentation formats when the functional anatomy of a 3D scapula and the associated shoulder flexion movement are learned. Findings showed no main effect of the presentation formats on performances, but revealed the predictive influence of spatial visualization and spatial relation abilities on performance. However, an interesting interaction between presentation formats and spatial relation ability for a specific anatomical task was found. This result highlighted the influence of presentation formats when spatial abilities are involved as well as the differentiated influence of spatial abilities on anatomical tasks. © 2015 American Association of Anatomists.

Parmodel: a web server for automated comparative modeling of proteins.

PubMed

Uchôa, Hugo Brandão; Jorge, Guilherme Eberhart; Freitas Da Silveira, Nelson José; Camera, João Carlos; Canduri, Fernanda; De Azevedo, Walter Filgueira

2004-12-24

Parmodel is a web server for automated comparative modeling and evaluation of protein structures. The aim of this tool is to help inexperienced users to perform modeling, assessment, visualization, and optimization of protein models as well as crystallographers to evaluate structures solved experimentally. It is subdivided in four modules: Parmodel Modeling, Parmodel Assessment, Parmodel Visualization, and Parmodel Optimization. The main module is the Parmodel Modeling that allows the building of several models for a same protein in a reduced time, through the distribution of modeling processes on a Beowulf cluster. Parmodel automates and integrates the main softwares used in comparative modeling as MODELLER, Whatcheck, Procheck, Raster3D, Molscript, and Gromacs. This web server is freely accessible at .

A Visual Basic simulation software tool for performance analysis of a membrane-based advanced water treatment plant.

PubMed

Pal, P; Kumar, R; Srivastava, N; Chaudhuri, J

2014-02-01

A Visual Basic simulation software (WATTPPA) has been developed to analyse the performance of an advanced wastewater treatment plant. This user-friendly and menu-driven software is based on the dynamic mathematical model for an industrial wastewater treatment scheme that integrates chemical, biological and membrane-based unit operations. The software-predicted results corroborate very well with the experimental findings as indicated in the overall correlation coefficient of the order of 0.99. The software permits pre-analysis and manipulation of input data, helps in optimization and exhibits performance of an integrated plant visually on a graphical platform. It allows quick performance analysis of the whole system as well as the individual units. The software first of its kind in its domain and in the well-known Microsoft Excel environment is likely to be very useful in successful design, optimization and operation of an advanced hybrid treatment plant for hazardous wastewater.

Visual feature-tolerance in the reading network.

PubMed

Rauschecker, Andreas M; Bowen, Reno F; Perry, Lee M; Kevan, Alison M; Dougherty, Robert F; Wandell, Brian A

2011-09-08

A century of neurology and neuroscience shows that seeing words depends on ventral occipital-temporal (VOT) circuitry. Typically, reading is learned using high-contrast line-contour words. We explored whether a specific VOT region, the visual word form area (VWFA), learns to see only these words or recognizes words independent of the specific shape-defining visual features. Word forms were created using atypical features (motion-dots, luminance-dots) whose statistical properties control word-visibility. We measured fMRI responses as word form visibility varied, and we used TMS to interfere with neural processing in specific cortical circuits, while subjects performed a lexical decision task. For all features, VWFA responses increased with word-visibility and correlated with performance. TMS applied to motion-specialized area hMT+ disrupted reading performance for motion-dots, but not line-contours or luminance-dots. A quantitative model describes feature-convergence in the VWFA and relates VWFA responses to behavioral performance. These findings suggest how visual feature-tolerance in the reading network arises through signal convergence from feature-specialized cortical areas. Copyright © 2011 Elsevier Inc. All rights reserved.

Different developmental trajectories across feature types support a dynamic field model of visual working memory development

PubMed Central

Simmering, Vanessa R.; Miller, Hilary E.; Bohache, Kevin

2015-01-01

Research on visual working memory has focused on characterizing the nature of capacity limits as “slots” or “resources” based almost exclusively on adults’ performance with little consideration for developmental change. Here we argue that understanding how visual working memory develops can shed new light onto the nature of representations. We present an alternative model, the Dynamic Field Theory (DFT), which can capture effects that have been previously attributed either to “slot” or “resource” explanations. The DFT includes a specific developmental mechanism to account for improvements in both resolution and capacity of visual working memory throughout childhood. Here we show how development in the DFT can account for different capacity estimates across feature types (i.e., color and shape). The current paper tests this account by comparing children’s (3, 5, and 7 years of age) performance across different feature types. Results showed that capacity for colors increased faster over development than capacity for shapes. A second experiment confirmed this difference across feature types within subjects, but also showed that the difference can be attenuated by testing memory for less-familiar colors. Model simulations demonstrate how developmental changes in connectivity within the model—purportedly arising through experience—can capture differences across feature types. PMID:25737253

Decoding visual object categories from temporal correlations of ECoG signals.

PubMed

Majima, Kei; Matsuo, Takeshi; Kawasaki, Keisuke; Kawai, Kensuke; Saito, Nobuhito; Hasegawa, Isao; Kamitani, Yukiyasu

2014-04-15

How visual object categories are represented in the brain is one of the key questions in neuroscience. Studies on low-level visual features have shown that relative timings or phases of neural activity between multiple brain locations encode information. However, whether such temporal patterns of neural activity are used in the representation of visual objects is unknown. Here, we examined whether and how visual object categories could be predicted (or decoded) from temporal patterns of electrocorticographic (ECoG) signals from the temporal cortex in five patients with epilepsy. We used temporal correlations between electrodes as input features, and compared the decoding performance with features defined by spectral power and phase from individual electrodes. While using power or phase alone, the decoding accuracy was significantly better than chance, correlations alone or those combined with power outperformed other features. Decoding performance with correlations was degraded by shuffling the order of trials of the same category in each electrode, indicating that the relative time series between electrodes in each trial is critical. Analysis using a sliding time window revealed that decoding performance with correlations began to rise earlier than that with power. This earlier increase in performance was replicated by a model using phase differences to encode categories. These results suggest that activity patterns arising from interactions between multiple neuronal units carry additional information on visual object categories. Copyright © 2013 Elsevier Inc. All rights reserved.

Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation

PubMed Central

Liu, Qian; Pineda-García, Garibaldi; Stromatias, Evangelos; Serrano-Gotarredona, Teresa; Furber, Steve B.

2016-01-01

Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field. PMID:27853419

Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation.

PubMed

Liu, Qian; Pineda-García, Garibaldi; Stromatias, Evangelos; Serrano-Gotarredona, Teresa; Furber, Steve B

2016-01-01

Today, increasing attention is being paid to research into spike-based neural computation both to gain a better understanding of the brain and to explore biologically-inspired computation. Within this field, the primate visual pathway and its hierarchical organization have been extensively studied. Spiking Neural Networks (SNNs), inspired by the understanding of observed biological structure and function, have been successfully applied to visual recognition and classification tasks. In addition, implementations on neuromorphic hardware have enabled large-scale networks to run in (or even faster than) real time, making spike-based neural vision processing accessible on mobile robots. Neuromorphic sensors such as silicon retinas are able to feed such mobile systems with real-time visual stimuli. A new set of vision benchmarks for spike-based neural processing are now needed to measure progress quantitatively within this rapidly advancing field. We propose that a large dataset of spike-based visual stimuli is needed to provide meaningful comparisons between different systems, and a corresponding evaluation methodology is also required to measure the performance of SNN models and their hardware implementations. In this paper we first propose an initial NE (Neuromorphic Engineering) dataset based on standard computer vision benchmarksand that uses digits from the MNIST database. This dataset is compatible with the state of current research on spike-based image recognition. The corresponding spike trains are produced using a range of techniques: rate-based Poisson spike generation, rank order encoding, and recorded output from a silicon retina with both flashing and oscillating input stimuli. In addition, a complementary evaluation methodology is presented to assess both model-level and hardware-level performance. Finally, we demonstrate the use of the dataset and the evaluation methodology using two SNN models to validate the performance of the models and their hardware implementations. With this dataset we hope to (1) promote meaningful comparison between algorithms in the field of neural computation, (2) allow comparison with conventional image recognition methods, (3) provide an assessment of the state of the art in spike-based visual recognition, and (4) help researchers identify future directions and advance the field.

Comparison of Object Recognition Behavior in Human and Monkey

PubMed Central

Rajalingham, Rishi; Schmidt, Kailyn

2015-01-01

Although the rhesus monkey is used widely as an animal model of human visual processing, it is not known whether invariant visual object recognition behavior is quantitatively comparable across monkeys and humans. To address this question, we systematically compared the core object recognition behavior of two monkeys with that of human subjects. To test true object recognition behavior (rather than image matching), we generated several thousand naturalistic synthetic images of 24 basic-level objects with high variation in viewing parameters and image background. Monkeys were trained to perform binary object recognition tasks on a match-to-sample paradigm. Data from 605 human subjects performing the same tasks on Mechanical Turk were aggregated to characterize “pooled human” object recognition behavior, as well as 33 separate Mechanical Turk subjects to characterize individual human subject behavior. Our results show that monkeys learn each new object in a few days, after which they not only match mean human performance but show a pattern of object confusion that is highly correlated with pooled human confusion patterns and is statistically indistinguishable from individual human subjects. Importantly, this shared human and monkey pattern of 3D object confusion is not shared with low-level visual representations (pixels, V1+; models of the retina and primary visual cortex) but is shared with a state-of-the-art computer vision feature representation. Together, these results are consistent with the hypothesis that rhesus monkeys and humans share a common neural shape representation that directly supports object perception. SIGNIFICANCE STATEMENT To date, several mammalian species have shown promise as animal models for studying the neural mechanisms underlying high-level visual processing in humans. In light of this diversity, making tight comparisons between nonhuman and human primates is particularly critical in determining the best use of nonhuman primates to further the goal of the field of translating knowledge gained from animal models to humans. To the best of our knowledge, this study is the first systematic attempt at comparing a high-level visual behavior of humans and macaque monkeys. PMID:26338324

TopicLens: Efficient Multi-Level Visual Topic Exploration of Large-Scale Document Collections.

PubMed

Kim, Minjeong; Kang, Kyeongpil; Park, Deokgun; Choo, Jaegul; Elmqvist, Niklas

2017-01-01

Topic modeling, which reveals underlying topics of a document corpus, has been actively adopted in visual analytics for large-scale document collections. However, due to its significant processing time and non-interactive nature, topic modeling has so far not been tightly integrated into a visual analytics workflow. Instead, most such systems are limited to utilizing a fixed, initial set of topics. Motivated by this gap in the literature, we propose a novel interaction technique called TopicLens that allows a user to dynamically explore data through a lens interface where topic modeling and the corresponding 2D embedding are efficiently computed on the fly. To support this interaction in real time while maintaining view consistency, we propose a novel efficient topic modeling method and a semi-supervised 2D embedding algorithm. Our work is based on improving state-of-the-art methods such as nonnegative matrix factorization and t-distributed stochastic neighbor embedding. Furthermore, we have built a web-based visual analytics system integrated with TopicLens. We use this system to measure the performance and the visualization quality of our proposed methods. We provide several scenarios showcasing the capability of TopicLens using real-world datasets.

Computing Systems | High-Performance Computing | NREL

Science.gov Websites

investigate, build, and test models of complex phenomena or entire integrated systems-that cannot be directly observed or manipulated in the lab, or would be too expensive or time consuming. Models and visualizations

Visual acuity estimation from simulated images

NASA Astrophysics Data System (ADS)

Duncan, William J.

Simulated images can provide insight into the performance of optical systems, especially those with complicated features. Many modern solutions for presbyopia and cataracts feature sophisticated power geometries or diffractive elements. Some intraocular lenses (IOLs) arrive at multifocality through the use of a diffractive surface and multifocal contact lenses have a radially varying power profile. These type of elements induce simultaneous vision as well as affecting vision much differently than a monofocal ophthalmic appliance. With myriad multifocal ophthalmics available on the market it is difficult to compare or assess performance in ways that effect wearers of such appliances. Here we present software and algorithmic metrics that can be used to qualitatively and quantitatively compare ophthalmic element performance, with specific examples of bifocal intraocular lenses (IOLs) and multifocal contact lenses. We anticipate this study, methods, and results to serve as a starting point for more complex models of vision and visual acuity in a setting where modeling is advantageous. Generating simulated images of real- scene scenarios is useful for patients in assessing vision quality with a certain appliance. Visual acuity estimation can serve as an important tool for manufacturing and design of ophthalmic appliances.

Networks for image acquisition, processing and display

NASA Technical Reports Server (NTRS)

Ahumada, Albert J., Jr.

1990-01-01

The human visual system comprises layers of networks which sample, process, and code images. Understanding these networks is a valuable means of understanding human vision and of designing autonomous vision systems based on network processing. Ames Research Center has an ongoing program to develop computational models of such networks. The models predict human performance in detection of targets and in discrimination of displayed information. In addition, the models are artificial vision systems sharing properties with biological vision that has been tuned by evolution for high performance. Properties include variable density sampling, noise immunity, multi-resolution coding, and fault-tolerance. The research stresses analysis of noise in visual networks, including sampling, photon, and processing unit noises. Specific accomplishments include: models of sampling array growth with variable density and irregularity comparable to that of the retinal cone mosaic; noise models of networks with signal-dependent and independent noise; models of network connection development for preserving spatial registration and interpolation; multi-resolution encoding models based on hexagonal arrays (HOP transform); and mathematical procedures for simplifying analysis of large networks.

The Hyper-Envelope Modeling Interface (HEMI): A Novel Approach Illustrated Through Predicting Tamarisk (Tamarix spp.) Habitat in the Western USA

USGS Publications Warehouse

Graham, Jim; Young, Nick; Jarnevich, Catherine S.; Newman, Greg; Evangelista, Paul; Stohlgren, Thomas J.

2013-01-01

Habitat suitability maps are commonly created by modeling a species’ environmental niche from occurrences and environmental characteristics. Here, we introduce the hyper-envelope modeling interface (HEMI), providing a new method for creating habitat suitability models using Bezier surfaces to model a species niche in environmental space. HEMI allows modeled surfaces to be visualized and edited in environmental space based on expert knowledge and does not require absence points for model development. The modeled surfaces require relatively few parameters compared to similar modeling approaches and may produce models that better match ecological niche theory. As a case study, we modeled the invasive species tamarisk (Tamarix spp.) in the western USA. We compare results from HEMI with those from existing similar modeling approaches (including BioClim, BioMapper, and Maxent). We used synthetic surfaces to create visualizations of the various models in environmental space and used modified area under the curve (AUC) statistic and akaike information criterion (AIC) as measures of model performance. We show that HEMI produced slightly better AUC values, except for Maxent and better AIC values overall. HEMI created a model with only ten parameters while Maxent produced a model with over 100 and BioClim used only eight. Additionally, HEMI allowed visualization and editing of the model in environmental space to develop alternative potential habitat scenarios. The use of Bezier surfaces can provide simple models that match our expectations of biological niche models and, at least in some cases, out-perform more complex approaches.

Tools for 3D scientific visualization in computational aerodynamics at NASA Ames Research Center

NASA Technical Reports Server (NTRS)

Bancroft, Gordon; Plessel, Todd; Merritt, Fergus; Watson, Val

1989-01-01

Hardware, software, and techniques used by the Fluid Dynamics Division (NASA) for performing visualization of computational aerodynamics, which can be applied to the visualization of flow fields from computer simulations of fluid dynamics about the Space Shuttle, are discussed. Three visualization techniques applied, post-processing, tracking, and steering, are described, as well as the post-processing software packages used, PLOT3D, SURF (Surface Modeller), GAS (Graphical Animation System), and FAST (Flow Analysis software Toolkit). Using post-processing methods a flow simulation was executed on a supercomputer and, after the simulation was complete, the results were processed for viewing. It is shown that the high-resolution, high-performance three-dimensional workstation combined with specially developed display and animation software provides a good tool for analyzing flow field solutions obtained from supercomputers.

Analysis of visual quality improvements provided by known tools for HDR content

NASA Astrophysics Data System (ADS)

Kim, Jaehwan; Alshina, Elena; Lee, JongSeok; Park, Youngo; Choi, Kwang Pyo

2016-09-01

In this paper, the visual quality of different solutions for high dynamic range (HDR) compression using MPEG test contents is analyzed. We also simulate the method for an efficient HDR compression which is based on statistical property of the signal. The method is compliant with HEVC specification and also easily compatible with other alternative methods which might require HEVC specification changes. It was subjectively tested on commercial TVs and compared with alternative solutions for HDR coding. Subjective visual quality tests were performed using SUHD TVs model which is SAMSUNG JS9500 with maximum luminance up to 1000nit in test. The solution that is based on statistical property shows not only improvement of objective performance but improvement of visual quality compared to other HDR solutions, while it is compatible with HEVC specification.

The emergence of polychronization and feature binding in a spiking neural network model of the primate ventral visual system.

PubMed

Eguchi, Akihiro; Isbister, James B; Ahmad, Nasir; Stringer, Simon

2018-07-01

We present a hierarchical neural network model, in which subpopulations of neurons develop fixed and regularly repeating temporal chains of spikes (polychronization), which respond specifically to randomized Poisson spike trains representing the input training images. The performance is improved by including top-down and lateral synaptic connections, as well as introducing multiple synaptic contacts between each pair of pre- and postsynaptic neurons, with different synaptic contacts having different axonal delays. Spike-timing-dependent plasticity thus allows the model to select the most effective axonal transmission delay between neurons. Furthermore, neurons representing the binding relationship between low-level and high-level visual features emerge through visually guided learning. This begins to provide a way forward to solving the classic feature binding problem in visual neuroscience and leads to a new hypothesis concerning how information about visual features at every spatial scale may be projected upward through successive neuronal layers. We name this hypothetical upward projection of information the "holographic principle." (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning.

PubMed

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-06-29

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images' spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines.

Thinking about the weather: How display salience and knowledge affect performance in a graphic inference task.

PubMed

Hegarty, Mary; Canham, Matt S; Fabrikant, Sara I

2010-01-01

Three experiments examined how bottom-up and top-down processes interact when people view and make inferences from complex visual displays (weather maps). Bottom-up effects of display design were investigated by manipulating the relative visual salience of task-relevant and task-irrelevant information across different maps. Top-down effects of domain knowledge were investigated by examining performance and eye fixations before and after participants learned relevant meteorological principles. Map design and knowledge interacted such that salience had no effect on performance before participants learned the meteorological principles; however, after learning, participants were more accurate if they viewed maps that made task-relevant information more visually salient. Effects of display design on task performance were somewhat dissociated from effects of display design on eye fixations. The results support a model in which eye fixations are directed primarily by top-down factors (task and domain knowledge). They suggest that good display design facilitates performance not just by guiding where viewers look in a complex display but also by facilitating processing of the visual features that represent task-relevant information at a given display location. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Increased conspicuousness can explain the match between visual sensitivities and blue plumage colours in fairy-wrens.

PubMed

Delhey, Kaspar; Hall, Michelle; Kingma, Sjouke A; Peters, Anne

2013-01-07

Colour signals are expected to match visual sensitivities of intended receivers. In birds, evolutionary shifts from violet-sensitive (V-type) to ultraviolet-sensitive (U-type) vision have been linked to increased prevalence of colours rich in shortwave reflectance (ultraviolet/blue), presumably due to better perception of such colours by U-type vision. Here we provide the first test of this widespread idea using fairy-wrens and allies (Family Maluridae) as a model, a family where shifts in visual sensitivities from V- to U-type eyes are associated with male nuptial plumage rich in ultraviolet/blue colours. Using psychophysical visual models, we compared the performance of both types of visual systems at two tasks: (i) detecting contrast between male plumage colours and natural backgrounds, and (ii) perceiving intraspecific chromatic variation in male plumage. While U-type outperforms V-type vision at both tasks, the crucial test here is whether U-type vision performs better at detecting and discriminating ultraviolet/blue colours when compared with other colours. This was true for detecting contrast between plumage colours and natural backgrounds (i), but not for discriminating intraspecific variability (ii). Our data indicate that selection to maximize conspicuousness to conspecifics may have led to the correlation between ultraviolet/blue colours and U-type vision in this clade of birds.

Feature extraction inspired by V1 in visual cortex

NASA Astrophysics Data System (ADS)

Lv, Chao; Xu, Yuelei; Zhang, Xulei; Ma, Shiping; Li, Shuai; Xin, Peng; Zhu, Mingning; Ma, Hongqiang

2018-04-01

Target feature extraction plays an important role in pattern recognition. It is the most complicated activity in the brain mechanism of biological vision. Inspired by high properties of primary visual cortex (V1) in extracting dynamic and static features, a visual perception model was raised. Firstly, 28 spatial-temporal filters with different orientations, half-squaring operation and divisive normalization were adopted to obtain the responses of V1 simple cells; then, an adjustable parameter was added to the output weight so that the response of complex cells was got. Experimental results indicate that the proposed V1 model can perceive motion information well. Besides, it has a good edge detection capability. The model inspired by V1 has good performance in feature extraction and effectively combines brain-inspired intelligence with computer vision.

A computational feedforward model predicts categorization of masked emotional body language for longer, but not for shorter, latencies.

PubMed

Stienen, Bernard M C; Schindler, Konrad; de Gelder, Beatrice

2012-07-01

Given the presence of massive feedback loops in brain networks, it is difficult to disentangle the contribution of feedforward and feedback processing to the recognition of visual stimuli, in this case, of emotional body expressions. The aim of the work presented in this letter is to shed light on how well feedforward processing explains rapid categorization of this important class of stimuli. By means of parametric masking, it may be possible to control the contribution of feedback activity in human participants. A close comparison is presented between human recognition performance and the performance of a computational neural model that exclusively modeled feedforward processing and was engineered to fulfill the computational requirements of recognition. Results show that the longer the stimulus onset asynchrony (SOA), the closer the performance of the human participants was to the values predicted by the model, with an optimum at an SOA of 100 ms. At short SOA latencies, human performance deteriorated, but the categorization of the emotional expressions was still above baseline. The data suggest that, although theoretically, feedback arising from inferotemporal cortex is likely to be blocked when the SOA is 100 ms, human participants still seem to rely on more local visual feedback processing to equal the model's performance.

Is airport baggage inspection just another medical image?

NASA Astrophysics Data System (ADS)

Gale, Alastair G.; Mugglestone, Mark D.; Purdy, Kevin J.; McClumpha, A.

2000-04-01

A similar inspection situation to medical imaging appears to be that of the airport security screener who examines X-ray images of passenger baggage. There is, however, little research overlap between the two areas. Studies of observer performance in examining medical images have led to a conceptual model which has been used successfully to understand diagnostic errors and develop appropriate training strategies. The model stresses three processes of; visual search, detection of potential targets, and interpretation of these areas; with most errors being due to the latter two factors. An initial study is reported on baggage inspection, using several brief image presentations, to examine the applicability of such a medical model to this domain. The task selected was the identification of potential Improvised Explosive Devices (IEDs). Specifically investigated was the visual search behavior of inspectors. It was found that IEDs could be identified in a very brief image presentation, with increased presentation time this performance improved. Participants fixated on IEDs very early on and sometimes concentrated wholly on this part of the baggage display. When IEDs were missed this was mainly due to interpretative factors rather than visual search or IED detection. It is argued that the observer model can be applied successfully to this scenario.

Kameleon Live: An Interactive Cloud Based Analysis and Visualization Platform for Space Weather Researchers

NASA Astrophysics Data System (ADS)

Pembroke, A. D.; Colbert, J. A.

2015-12-01

The Community Coordinated Modeling Center (CCMC) provides hosting for many of the simulations used by the space weather community of scientists, educators, and forecasters. CCMC users may submit model runs through the Runs on Request system, which produces static visualizations of model output in the browser, while further analysis may be performed off-line via Kameleon, CCMC's cross-language access and interpolation library. Off-line analysis may be suitable for power-users, but storage and coding requirements present a barrier to entry for non-experts. Moreover, a lack of a consistent framework for analysis hinders reproducibility of scientific findings. To that end, we have developed Kameleon Live, a cloud based interactive analysis and visualization platform. Kameleon Live allows users to create scientific studies built around selected runs from the Runs on Request database, perform analysis on those runs, collaborate with other users, and disseminate their findings among the space weather community. In addition to showcasing these novel collaborative analysis features, we invite feedback from CCMC users as we seek to advance and improve on the new platform.

A crossmodal crossover: opposite effects of visual and auditory perceptual load on steady-state evoked potentials to irrelevant visual stimuli.

PubMed

Jacoby, Oscar; Hall, Sarah E; Mattingley, Jason B

2012-07-16

Mechanisms of attention are required to prioritise goal-relevant sensory events under conditions of stimulus competition. According to the perceptual load model of attention, the extent to which task-irrelevant inputs are processed is determined by the relative demands of discriminating the target: the more perceptually demanding the target task, the less unattended stimuli will be processed. Although much evidence supports the perceptual load model for competing stimuli within a single sensory modality, the effects of perceptual load in one modality on distractor processing in another is less clear. Here we used steady-state evoked potentials (SSEPs) to measure neural responses to irrelevant visual checkerboard stimuli while participants performed either a visual or auditory task that varied in perceptual load. Consistent with perceptual load theory, increasing visual task load suppressed SSEPs to the ignored visual checkerboards. In contrast, increasing auditory task load enhanced SSEPs to the ignored visual checkerboards. This enhanced neural response to irrelevant visual stimuli under auditory load suggests that exhausting capacity within one modality selectively compromises inhibitory processes required for filtering stimuli in another. Copyright © 2012 Elsevier Inc. All rights reserved.

Transformation of an uncertain video search pipeline to a sketch-based visual analytics loop.

PubMed

Legg, Philip A; Chung, David H S; Parry, Matthew L; Bown, Rhodri; Jones, Mark W; Griffiths, Iwan W; Chen, Min

2013-12-01

Traditional sketch-based image or video search systems rely on machine learning concepts as their core technology. However, in many applications, machine learning alone is impractical since videos may not be semantically annotated sufficiently, there may be a lack of suitable training data, and the search requirements of the user may frequently change for different tasks. In this work, we develop a visual analytics systems that overcomes the shortcomings of the traditional approach. We make use of a sketch-based interface to enable users to specify search requirement in a flexible manner without depending on semantic annotation. We employ active machine learning to train different analytical models for different types of search requirements. We use visualization to facilitate knowledge discovery at the different stages of visual analytics. This includes visualizing the parameter space of the trained model, visualizing the search space to support interactive browsing, visualizing candidature search results to support rapid interaction for active learning while minimizing watching videos, and visualizing aggregated information of the search results. We demonstrate the system for searching spatiotemporal attributes from sports video to identify key instances of the team and player performance.

Incidental Learning Speeds Visual Search by Lowering Response Thresholds, Not by Improving Efficiency: Evidence from Eye Movements

ERIC Educational Resources Information Center

Hout, Michael C.; Goldinger, Stephen D.

2012-01-01

When observers search for a target object, they incidentally learn the identities and locations of "background" objects in the same display. This learning can facilitate search performance, eliciting faster reaction times for repeated displays. Despite these findings, visual search has been successfully modeled using architectures that maintain no…

Examination of Test and Item Statistics from Visual and Verbal Mathematics Questions

ERIC Educational Resources Information Center

Alpayar, Cagla; Gulleroglu, H. Deniz

2017-01-01

The aim of this research is to determine whether students' test performance and approaches to test questions change based on the type of mathematics questions (visual or verbal) administered to them. This research is based on a mixed-design model. The quantitative data are gathered from 297 seventh grade students, attending seven different middle…

Atoms of recognition in human and computer vision.

PubMed

Ullman, Shimon; Assif, Liav; Fetaya, Ethan; Harari, Daniel

2016-03-08

Discovering the visual features and representations used by the brain to recognize objects is a central problem in the study of vision. Recently, neural network models of visual object recognition, including biological and deep network models, have shown remarkable progress and have begun to rival human performance in some challenging tasks. These models are trained on image examples and learn to extract features and representations and to use them for categorization. It remains unclear, however, whether the representations and learning processes discovered by current models are similar to those used by the human visual system. Here we show, by introducing and using minimal recognizable images, that the human visual system uses features and processes that are not used by current models and that are critical for recognition. We found by psychophysical studies that at the level of minimal recognizable images a minute change in the image can have a drastic effect on recognition, thus identifying features that are critical for the task. Simulations then showed that current models cannot explain this sensitivity to precise feature configurations and, more generally, do not learn to recognize minimal images at a human level. The role of the features shown here is revealed uniquely at the minimal level, where the contribution of each feature is essential. A full understanding of the learning and use of such features will extend our understanding of visual recognition and its cortical mechanisms and will enhance the capacity of computational models to learn from visual experience and to deal with recognition and detailed image interpretation.

Stimulus modality and working memory performance in Greek children with reading disabilities: additional evidence for the pictorial superiority hypothesis.

PubMed

Constantinidou, Fofi; Evripidou, Christiana

2012-01-01

This study investigated the effects of stimulus presentation modality on working memory performance in children with reading disabilities (RD) and in typically developing children (TDC), all native speakers of Greek. It was hypothesized that the visual presentation of common objects would result in improved learning and recall performance as compared to the auditory presentation of stimuli. Twenty children, ages 10-12, diagnosed with RD were matched to 20 TDC age peers. The experimental tasks implemented a multitrial verbal learning paradigm incorporating three modalities: auditory, visual, and auditory plus visual. Significant group differences were noted on language, verbal and nonverbal memory, and measures of executive abilities. A mixed-model MANOVA indicated that children with RD had a slower learning curve and recalled fewer words than TDC across experimental modalities. Both groups of participants benefited from the visual presentation of objects; however, children with RD showed the greatest gains during this condition. In conclusion, working memory for common verbal items is impaired in children with RD; however, performance can be facilitated, and learning efficiency maximized, when information is presented visually. The results provide further evidence for the pictorial superiority hypothesis and the theory that pictorial presentation of verbal stimuli is adequate for dual coding.

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model

PubMed Central

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques. PMID:29694429

An effective content-based image retrieval technique for image visuals representation based on the bag-of-visual-words model.

PubMed

Jabeen, Safia; Mehmood, Zahid; Mahmood, Toqeer; Saba, Tanzila; Rehman, Amjad; Mahmood, Muhammad Tariq

2018-01-01

For the last three decades, content-based image retrieval (CBIR) has been an active research area, representing a viable solution for retrieving similar images from an image repository. In this article, we propose a novel CBIR technique based on the visual words fusion of speeded-up robust features (SURF) and fast retina keypoint (FREAK) feature descriptors. SURF is a sparse descriptor whereas FREAK is a dense descriptor. Moreover, SURF is a scale and rotation-invariant descriptor that performs better in the case of repeatability, distinctiveness, and robustness. It is robust to noise, detection errors, geometric, and photometric deformations. It also performs better at low illumination within an image as compared to the FREAK descriptor. In contrast, FREAK is a retina-inspired speedy descriptor that performs better for classification-based problems as compared to the SURF descriptor. Experimental results show that the proposed technique based on the visual words fusion of SURF-FREAK descriptors combines the features of both descriptors and resolves the aforementioned issues. The qualitative and quantitative analysis performed on three image collections, namely Corel-1000, Corel-1500, and Caltech-256, shows that proposed technique based on visual words fusion significantly improved the performance of the CBIR as compared to the feature fusion of both descriptors and state-of-the-art image retrieval techniques.

Signal detection evidence for limited capacity in visual search

PubMed Central

Fencsik, David E.; Flusberg, Stephen J.; Horowitz, Todd S.; Wolfe, Jeremy M.

2014-01-01

The nature of capacity limits (if any) in visual search has been a topic of controversy for decades. In 30 years of work, researchers have attempted to distinguish between two broad classes of visual search models. Attention-limited models have proposed two stages of perceptual processing: an unlimited-capacity preattentive stage, and a limited-capacity selective attention stage. Conversely, noise-limited models have proposed a single, unlimited-capacity perceptual processing stage, with decision processes influenced only by stochastic noise. Here, we use signal detection methods to test a strong prediction of attention-limited models. In standard attention-limited models, performance of some searches (feature searches) should only be limited by a preattentive stage. Other search tasks (e.g., spatial configuration search for a “2” among “5”s) should be additionally limited by an attentional bottleneck. We equated average accuracies for a feature and a spatial configuration search over set sizes of 1–8 for briefly presented stimuli. The strong prediction of attention-limited models is that, given overall equivalence in performance, accuracy should be better on the spatial configuration search than on the feature search for set size 1, and worse for set size 8. We confirm this crossover interaction and show that it is problematic for at least one class of one-stage decision models. PMID:21901574

Modern Scientific Visualization is more than Just Pretty Pictures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bethel, E Wes; Rubel, Oliver; Wu, Kesheng

2008-12-05

While the primary product of scientific visualization is images and movies, its primary objective is really scientific insight. Too often, the focus of visualization research is on the product, not the mission. This paper presents two case studies, both that appear in previous publications, that focus on using visualization technology to produce insight. The first applies"Query-Driven Visualization" concepts to laser wakefield simulation data to help identify and analyze the process of beam formation. The second uses topological analysis to provide a quantitative basis for (i) understanding the mixing process in hydrodynamic simulations, and (ii) performing comparative analysis of data frommore » two different types of simulations that model hydrodynamic instability.« less

Information Extraction for System-Software Safety Analysis: Calendar Year 2008 Year-End Report

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2009-01-01

This annual report describes work to integrate a set of tools to support early model-based analysis of failures and hazards due to system-software interactions. The tools perform and assist analysts in the following tasks: 1) extract model parts from text for architecture and safety/hazard models; 2) combine the parts with library information to develop the models for visualization and analysis; 3) perform graph analysis and simulation to identify and evaluate possible paths from hazard sources to vulnerable entities and functions, in nominal and anomalous system-software configurations and scenarios; and 4) identify resulting candidate scenarios for software integration testing. There has been significant technical progress in model extraction from Orion program text sources, architecture model derivation (components and connections) and documentation of extraction sources. Models have been derived from Internal Interface Requirements Documents (IIRDs) and FMEA documents. Linguistic text processing is used to extract model parts and relationships, and the Aerospace Ontology also aids automated model development from the extracted information. Visualizations of these models assist analysts in requirements overview and in checking consistency and completeness.

GANViz: A Visual Analytics Approach to Understand the Adversarial Game.

PubMed

Wang, Junpeng; Gou, Liang; Yang, Hao; Shen, Han-Wei

2018-06-01

Generative models bear promising implications to learn data representations in an unsupervised fashion with deep learning. Generative Adversarial Nets (GAN) is one of the most popular frameworks in this arena. Despite the promising results from different types of GANs, in-depth understanding on the adversarial training process of the models remains a challenge to domain experts. The complexity and the potential long-time training process of the models make it hard to evaluate, interpret, and optimize them. In this work, guided by practical needs from domain experts, we design and develop a visual analytics system, GANViz, aiming to help experts understand the adversarial process of GANs in-depth. Specifically, GANViz evaluates the model performance of two subnetworks of GANs, provides evidence and interpretations of the models' performance, and empowers comparative analysis with the evidence. Through our case studies with two real-world datasets, we demonstrate that GANViz can provide useful insight into helping domain experts understand, interpret, evaluate, and potentially improve GAN models.

Models Extracted from Text for System-Software Safety Analyses

NASA Technical Reports Server (NTRS)

Malin, Jane T.

2010-01-01

This presentation describes extraction and integration of requirements information and safety information in visualizations to support early review of completeness, correctness, and consistency of lengthy and diverse system safety analyses. Software tools have been developed and extended to perform the following tasks: 1) extract model parts and safety information from text in interface requirements documents, failure modes and effects analyses and hazard reports; 2) map and integrate the information to develop system architecture models and visualizations for safety analysts; and 3) provide model output to support virtual system integration testing. This presentation illustrates the methods and products with a rocket motor initiation case.

Biologically Inspired Model for Visual Cognition Achieving Unsupervised Episodic and Semantic Feature Learning.

PubMed

Qiao, Hong; Li, Yinlin; Li, Fengfu; Xi, Xuanyang; Wu, Wei

2016-10-01

Recently, many biologically inspired visual computational models have been proposed. The design of these models follows the related biological mechanisms and structures, and these models provide new solutions for visual recognition tasks. In this paper, based on the recent biological evidence, we propose a framework to mimic the active and dynamic learning and recognition process of the primate visual cortex. From principle point of view, the main contributions are that the framework can achieve unsupervised learning of episodic features (including key components and their spatial relations) and semantic features (semantic descriptions of the key components), which support higher level cognition of an object. From performance point of view, the advantages of the framework are as follows: 1) learning episodic features without supervision-for a class of objects without a prior knowledge, the key components, their spatial relations and cover regions can be learned automatically through a deep neural network (DNN); 2) learning semantic features based on episodic features-within the cover regions of the key components, the semantic geometrical values of these components can be computed based on contour detection; 3) forming the general knowledge of a class of objects-the general knowledge of a class of objects can be formed, mainly including the key components, their spatial relations and average semantic values, which is a concise description of the class; and 4) achieving higher level cognition and dynamic updating-for a test image, the model can achieve classification and subclass semantic descriptions. And the test samples with high confidence are selected to dynamically update the whole model. Experiments are conducted on face images, and a good performance is achieved in each layer of the DNN and the semantic description learning process. Furthermore, the model can be generalized to recognition tasks of other objects with learning ability.

Influence of visual observational conditions on tongue motor learning.

PubMed

Kothari, Mohit; Liu, Xuemei; Baad-Hansen, Lene; Kumar, Abhishek; Bin, Guo; Svensson, Peter

2016-12-01

The aim of this study was to investigate the impact of visual observational conditions on performance during a standardized tongue-protrusion training (TPT) task and to evaluate subject-based reports of helpfulness, disturbance, pain, and fatigue, due to the observational conditions on 0-10 numerical rating scales. Forty-eight healthy participants performed a 1-h standard TPT task. Participants were randomly assigned to one of the following three groups with different observational conditions: group 1, model observation (participants watched a prerecorded video showing standard TPT before optimal TPT being performed); group 2, self-observation (participants watched live video feedback of their own TPT performance); and group 3, control group (participants performed the TPT with no conditioning). There was no overall difference between groups but TPT performance increased over time. A significant group×time interaction indicated that the self-observation group performed significantly better than the model-observation group in the last 20 min of TPT. The subject-based reports of video helpfulness showed that the model-observation group rated the prerecorded video as more helpful for TPT performance compared with the other groups but there was no significant difference between groups regarding the level of disturbance, pain, or fatigue. Self-observation of tongue-training facilitated behavioral aspects of tongue motor learning compared with model observation but not compared with control. © 2016 Eur J Oral Sci.

Non-conscious visual cues related to affect and action alter perception of effort and endurance performance

PubMed Central

Blanchfield, Anthony; Hardy, James; Marcora, Samuele

2014-01-01

The psychobiological model of endurance performance proposes that endurance performance is determined by a decision-making process based on perception of effort and potential motivation. Recent research has reported that effort-based decision-making during cognitive tasks can be altered by non-conscious visual cues relating to affect and action. The effects of these non-conscious visual cues on effort and performance during physical tasks are however unknown. We report two experiments investigating the effects of subliminal priming with visual cues related to affect and action on perception of effort and endurance performance. In Experiment 1 thirteen individuals were subliminally primed with happy or sad faces as they cycled to exhaustion in a counterbalanced and randomized crossover design. A paired t-test (happy vs. sad faces) revealed that individuals cycled significantly longer (178 s, p = 0.04) when subliminally primed with happy faces. A 2 × 5 (condition × iso-time) ANOVA also revealed a significant main effect of condition on rating of perceived exertion (RPE) during the time to exhaustion (TTE) test with lower RPE when subjects were subliminally primed with happy faces (p = 0.04). In Experiment 2, a single-subject randomization tests design found that subliminal priming with action words facilitated a significantly longer TTE (399 s, p = 0.04) in comparison to inaction words. Like Experiment 1, this greater TTE was accompanied by a significantly lower RPE (p = 0.03). These experiments are the first to show that subliminal visual cues relating to affect and action can alter perception of effort and endurance performance. Non-conscious visual cues may therefore influence the effort-based decision-making process that is proposed to determine endurance performance. Accordingly, the findings raise notable implications for individuals who may encounter such visual cues during endurance competitions, training, or health related exercise. PMID:25566014

VisFlow - Web-based Visualization Framework for Tabular Data with a Subset Flow Model.

PubMed

Yu, Bowen; Silva, Claudio T

2017-01-01

Data flow systems allow the user to design a flow diagram that specifies the relations between system components which process, filter or visually present the data. Visualization systems may benefit from user-defined data flows as an analysis typically consists of rendering multiple plots on demand and performing different types of interactive queries across coordinated views. In this paper, we propose VisFlow, a web-based visualization framework for tabular data that employs a specific type of data flow model called the subset flow model. VisFlow focuses on interactive queries within the data flow, overcoming the limitation of interactivity from past computational data flow systems. In particular, VisFlow applies embedded visualizations and supports interactive selections, brushing and linking within a visualization-oriented data flow. The model requires all data transmitted by the flow to be a data item subset (i.e. groups of table rows) of some original input table, so that rendering properties can be assigned to the subset unambiguously for tracking and comparison. VisFlow features the analysis flexibility of a flow diagram, and at the same time reduces the diagram complexity and improves usability. We demonstrate the capability of VisFlow on two case studies with domain experts on real-world datasets showing that VisFlow is capable of accomplishing a considerable set of visualization and analysis tasks. The VisFlow system is available as open source on GitHub.

Behavioural system identification of visual flight speed control in Drosophila melanogaster

PubMed Central

Rohrseitz, Nicola; Fry, Steven N.

2011-01-01

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles. PMID:20525744

Behavioural system identification of visual flight speed control in Drosophila melanogaster.

PubMed

Rohrseitz, Nicola; Fry, Steven N

2011-02-06

Behavioural control in many animals involves complex mechanisms with intricate sensory-motor feedback loops. Modelling allows functional aspects to be captured without relying on a description of the underlying complex, and often unknown, mechanisms. A wide range of engineering techniques are available for modelling, but their ability to describe time-continuous processes is rarely exploited to describe sensory-motor control mechanisms in biological systems. We performed a system identification of visual flight speed control in the fruitfly Drosophila, based on an extensive dataset of open-loop responses previously measured under free flight conditions. We identified a second-order under-damped control model with just six free parameters that well describes both the transient and steady-state characteristics of the open-loop data. We then used the identified control model to predict flight speed responses after a visual perturbation under closed-loop conditions and validated the model with behavioural measurements performed in free-flying flies under the same closed-loop conditions. Our system identification of the fruitfly's flight speed response uncovers the high-level control strategy of a fundamental flight control reflex without depending on assumptions about the underlying physiological mechanisms. The results are relevant for future investigations of the underlying neuromotor processing mechanisms, as well as for the design of biomimetic robots, such as micro-air vehicles.

Differential Effects of Music and Video Gaming During Breaks on Auditory and Visual Learning.

PubMed

Liu, Shuyan; Kuschpel, Maxim S; Schad, Daniel J; Heinz, Andreas; Rapp, Michael A

2015-11-01

The interruption of learning processes by breaks filled with diverse activities is common in everyday life. This study investigated the effects of active computer gaming and passive relaxation (rest and music) breaks on auditory versus visual memory performance. Young adults were exposed to breaks involving (a) open eyes resting, (b) listening to music, and (c) playing a video game, immediately after memorizing auditory versus visual stimuli. To assess learning performance, words were recalled directly after the break (an 8:30 minute delay) and were recalled and recognized again after 7 days. Based on linear mixed-effects modeling, it was found that playing the Angry Birds video game during a short learning break impaired long-term retrieval in auditory learning but enhanced long-term retrieval in visual learning compared with the music and rest conditions. These differential effects of video games on visual versus auditory learning suggest specific interference of common break activities on learning.

Comparing two types of engineering visualizations: task-related manipulations matter.

PubMed

Cölln, Martin C; Kusch, Kerstin; Helmert, Jens R; Kohler, Petra; Velichkovsky, Boris M; Pannasch, Sebastian

2012-01-01

This study focuses on the comparison of traditional engineering drawings with a CAD (computer aided design) visualization in terms of user performance and eye movements in an applied context. Twenty-five students of mechanical engineering completed search tasks for measures in two distinct depictions of a car engine component (engineering drawing vs. CAD model). Besides spatial dimensionality, the display types most notably differed in terms of information layout, access and interaction options. The CAD visualization yielded better performance, if users directly manipulated the object, but was inferior, if employed in a conventional static manner, i.e. inspecting only predefined views. An additional eye movement analysis revealed longer fixation durations and a stronger increase of task-relevant fixations over time when interacting with the CAD visualization. This suggests a more focused extraction and filtering of information. We conclude that the three-dimensional CAD visualization can be advantageous if its ability to manipulate is used. Copyright © 2011 Elsevier Ltd and The Ergonomics Society. All rights reserved.

A cross-sectional controlled developmental study of neuropsychological functions in patients with glutaric aciduria type I.

PubMed

Boy, Nikolas; Heringer, Jana; Haege, Gisela; Glahn, Esther M; Hoffmann, Georg F; Garbade, Sven F; Kölker, Stefan; Burgard, Peter

2015-12-22

Glutaric aciduria type I (GA-I) is an inherited metabolic disease due to deficiency of glutaryl-CoA dehydrogenase (GCDH). Cognitive functions are generally thought to be spared, but have not yet been studied in detail. Thirty patients detected by newborn screening (n = 13), high-risk screening (n = 3) or targeted metabolic testing (n = 14) were studied for simple reaction time (SRT), continuous performance (CP), visual working memory (VWM), visual-motor coordination (Tracking) and visual search (VS). Dystonia (n = 13 patients) was categorized using the Barry-Albright-Dystonia Scale (BADS). Patients were compared with 196 healthy controls. Developmental functions of cognitive performances were analysed using a negative exponential function model. BADS scores correlated with speed tests but not with tests measuring stability or higher cognitive functions without time constraints. Developmental functions of GA-I patients significantly differed from controls for SRT and VS but not for VWM and showed obvious trends for CP and Tracking. Dystonic patients were slower in SRT and CP but reached their asymptote of performance similar to asymptomatic patients and controls in all tests. Asymptomatic patients did not differ from controls, except showing significantly better results in Tracking and a trend for slower reactions in visual search. Data across all age groups of patients and controls fitted well to a model of negative exponential development. Dystonic patients predominantly showed motor speed impairment, whereas performance improved with higher cognitive load. Patients without motor symptoms did not differ from controls. Developmental functions of cognitive performances were similar in patients and controls. Performance in tests with higher cognitive demand might be preserved in GA-I, even in patients with striatal degeneration.

Can responses to basic non-numerical visual features explain neural numerosity responses?

PubMed

Harvey, Ben M; Dumoulin, Serge O

2017-04-01

Humans and many animals can distinguish between stimuli that differ in numerosity, the number of objects in a set. Human and macaque parietal lobes contain neurons that respond to changes in stimulus numerosity. However, basic non-numerical visual features can affect neural responses to and perception of numerosity, and visual features often co-vary with numerosity. Therefore, it is debated whether numerosity or co-varying low-level visual features underlie neural and behavioral responses to numerosity. To test the hypothesis that non-numerical visual features underlie neural numerosity responses in a human parietal numerosity map, we analyze responses to a group of numerosity stimulus configurations that have the same numerosity progression but vary considerably in their non-numerical visual features. Using ultra-high-field (7T) fMRI, we measure responses to these stimulus configurations in an area of posterior parietal cortex whose responses are believed to reflect numerosity-selective activity. We describe an fMRI analysis method to distinguish between alternative models of neural response functions, following a population receptive field (pRF) modeling approach. For each stimulus configuration, we first quantify the relationships between numerosity and several non-numerical visual features that have been proposed to underlie performance in numerosity discrimination tasks. We then determine how well responses to these non-numerical visual features predict the observed fMRI responses, and compare this to the predictions of responses to numerosity. We demonstrate that a numerosity response model predicts observed responses more accurately than models of responses to simple non-numerical visual features. As such, neural responses in cognitive processing need not reflect simpler properties of early sensory inputs. Copyright © 2017 Elsevier Inc. All rights reserved.

Judgment in crossing a road between objects coming in the opposite lane

NASA Astrophysics Data System (ADS)

Matsumiya, Kazumichi; Kaneko, Hirohiko

2008-05-01

When cars are oncoming in the opposite lane of a road, a driver is able to judge whether his/her car can cross the road at an intersection without a collision with the oncoming cars. We developed a model for the human judgment used to cross a road between oncoming objects. In the model, in order to make the judgment to cross the road, the human visual system compares the time interval it takes for an oncoming object to pass the observer with the time interval it takes for the observer to cross the road. We conducted a psychophysical experiment to test the model prediction. The result showed that human performance is in good agreement with the theoretical consequence provided by the model, suggesting that the human visual system uses not only the visually timed information of the approaching object but also the timed information of self-action for the judgment about crossing the road.

A Theoretical and Experimental Analysis of the Outside World Perception Process

NASA Technical Reports Server (NTRS)

Wewerinke, P. H.

1978-01-01

The outside scene is often an important source of information for manual control tasks. Important examples of these are car driving and aircraft control. This paper deals with modelling this visual scene perception process on the basis of linear perspective geometry and the relative motion cues. Model predictions utilizing psychophysical threshold data from base-line experiments and literature of a variety of visual approach tasks are compared with experimental data. Both the performance and workload results illustrate that the model provides a meaningful description of the outside world perception process, with a useful predictive capability.

SWATShare- A Platform for Collaborative Hydrology Research and Education with Cyber-enabled Sharing, Running and Visualization of SWAT Models

NASA Astrophysics Data System (ADS)

Rajib, M. A.; Merwade, V.; Song, C.; Zhao, L.; Kim, I. L.; Zhe, S.

2014-12-01

Setting up of any hydrologic model requires a large amount of efforts including compilation of all the data, creation of input files, calibration and validation. Given the amount of efforts involved, it is possible that models for a watershed get created multiple times by multiple groups or organizations to accomplish different research, educational or policy goals. To reduce the duplication of efforts and enable collaboration among different groups or organizations around an already existing hydrology model, a platform is needed where anyone can search for existing models, perform simple scenario analysis and visualize model results. The creator and users of a model on such a platform can then collaborate to accomplish new research or educational objectives. From this perspective, a prototype cyber-infrastructure (CI), called SWATShare, is developed for sharing, running and visualizing Soil Water Assessment Tool (SWAT) models in an interactive GIS-enabled web environment. Users can utilize SWATShare to publish or upload their own models, search and download existing SWAT models developed by others, run simulations including calibration using high performance resources provided by XSEDE and Cloud. Besides running and sharing, SWATShare hosts a novel spatio-temporal visualization system for SWAT model outputs. In temporal scale, the system creates time-series plots for all the hydrology and water quality variables available along the reach as well as in watershed-level. In spatial scale, the system can dynamically generate sub-basin level thematic maps for any variable at any user-defined date or date range; and thereby, allowing users to run animations or download the data for subsequent analyses. In addition to research, SWATShare can also be used within a classroom setting as an educational tool for modeling and comparing the hydrologic processes under different geographic and climatic settings. SWATShare is publicly available at https://www.water-hub.org/swatshare.

A dual-task investigation of automaticity in visual word processing

NASA Technical Reports Server (NTRS)

McCann, R. S.; Remington, R. W.; Van Selst, M.

2000-01-01

An analysis of activation models of visual word processing suggests that frequency-sensitive forms of lexical processing should proceed normally while unattended. This hypothesis was tested by having participants perform a speeded pitch discrimination task followed by lexical decisions or word naming. As the stimulus onset asynchrony between the tasks was reduced, lexical-decision and naming latencies increased dramatically. Word-frequency effects were additive with the increase, indicating that frequency-sensitive processing was subject to postponement while attention was devoted to the other task. Either (a) the same neural hardware shares responsibility for lexical processing and central stages of choice reaction time task processing and cannot perform both computations simultaneously, or (b) lexical processing is blocked in order to optimize performance on the pitch discrimination task. Either way, word processing is not as automatic as activation models suggest.

Real-Time Agent-Based Modeling Simulation with in-situ Visualization of Complex Biological Systems: A Case Study on Vocal Fold Inflammation and Healing.

PubMed

Seekhao, Nuttiiya; Shung, Caroline; JaJa, Joseph; Mongeau, Luc; Li-Jessen, Nicole Y K

2016-05-01

We present an efficient and scalable scheme for implementing agent-based modeling (ABM) simulation with In Situ visualization of large complex systems on heterogeneous computing platforms. The scheme is designed to make optimal use of the resources available on a heterogeneous platform consisting of a multicore CPU and a GPU, resulting in minimal to no resource idle time. Furthermore, the scheme was implemented under a client-server paradigm that enables remote users to visualize and analyze simulation data as it is being generated at each time step of the model. Performance of a simulation case study of vocal fold inflammation and wound healing with 3.8 million agents shows 35× and 7× speedup in execution time over single-core and multi-core CPU respectively. Each iteration of the model took less than 200 ms to simulate, visualize and send the results to the client. This enables users to monitor the simulation in real-time and modify its course as needed.

Modeling semantic aspects for cross-media image indexing.

PubMed

Monay, Florent; Gatica-Perez, Daniel

2007-10-01

To go beyond the query-by-example paradigm in image retrieval, there is a need for semantic indexing of large image collections for intuitive text-based image search. Different models have been proposed to learn the dependencies between the visual content of an image set and the associated text captions, then allowing for the automatic creation of semantic indices for unannotated images. The task, however, remains unsolved. In this paper, we present three alternatives to learn a Probabilistic Latent Semantic Analysis model (PLSA) for annotated images, and evaluate their respective performance for automatic image indexing. Under the PLSA assumptions, an image is modeled as a mixture of latent aspects that generates both image features and text captions, and we investigate three ways to learn the mixture of aspects. We also propose a more discriminative image representation than the traditional Blob histogram, concatenating quantized local color information and quantized local texture descriptors. The first learning procedure of a PLSA model for annotated images is a standard EM algorithm, which implicitly assumes that the visual and the textual modalities can be treated equivalently. The other two models are based on an asymmetric PLSA learning, allowing to constrain the definition of the latent space on the visual or on the textual modality. We demonstrate that the textual modality is more appropriate to learn a semantically meaningful latent space, which translates into improved annotation performance. A comparison of our learning algorithms with respect to recent methods on a standard dataset is presented, and a detailed evaluation of the performance shows the validity of our framework.

UV-blocking spectacle lens protects against UV-induced decline of visual performance.

PubMed

Liou, Jyh-Cheng; Teng, Mei-Ching; Tsai, Yun-Shan; Lin, En-Chieh; Chen, Bo-Yie

2015-01-01

Excessive exposure to sunlight may be a risk factor for ocular diseases and reduced visual performance. This study was designed to examine the ability of an ultraviolet (UV)-blocking spectacle lens to prevent visual acuity decline and ocular surface disorders in a mouse model of UVB-induced photokeratitis. Mice were divided into 4 groups (10 mice per group): (1) a blank control group (no exposure to UV radiation), (2) a UVB/no lens group (mice exposed to UVB rays, but without lens protection), (3) a UVB/UV400 group (mice exposed to UVB rays and protected using the CR-39™ spectacle lens [UV400 coating]), and (4) a UVB/photochromic group (mice exposed to UVB rays and protected using the CR-39™ spectacle lens [photochromic coating]). We investigated UVB-induced changes in visual acuity and in corneal smoothness, opacity, and lissamine green staining. We also evaluated the correlation between visual acuity decline and changes to the corneal surface parameters. Tissue sections were prepared and stained immunohistochemically to evaluate the structural integrity of the cornea and conjunctiva. In blank controls, the cornea remained undamaged, whereas in UVB-exposed mice, the corneal surface was disrupted; this disruption significantly correlated with a concomitant decline in visual acuity. Both the UVB/UV400 and UVB/photochromic groups had sharper visual acuity and a healthier corneal surface than the UVB/no lens group. Eyes in both protected groups also showed better corneal and conjunctival structural integrity than unprotected eyes. Furthermore, there were fewer apoptotic cells and less polymorphonuclear leukocyte infiltration in corneas protected by the spectacle lenses. The model established herein reliably determines the protective effect of UV-blocking ophthalmic biomaterials, because the in vivo protection against UV-induced ocular damage and visual acuity decline was easily defined.

Lip-reading aids word recognition most in moderate noise: a Bayesian explanation using high-dimensional feature space.

PubMed

Ma, Wei Ji; Zhou, Xiang; Ross, Lars A; Foxe, John J; Parra, Lucas C

2009-01-01

Watching a speaker's facial movements can dramatically enhance our ability to comprehend words, especially in noisy environments. From a general doctrine of combining information from different sensory modalities (the principle of inverse effectiveness), one would expect that the visual signals would be most effective at the highest levels of auditory noise. In contrast, we find, in accord with a recent paper, that visual information improves performance more at intermediate levels of auditory noise than at the highest levels, and we show that a novel visual stimulus containing only temporal information does the same. We present a Bayesian model of optimal cue integration that can explain these conflicts. In this model, words are regarded as points in a multidimensional space and word recognition is a probabilistic inference process. When the dimensionality of the feature space is low, the Bayesian model predicts inverse effectiveness; when the dimensionality is high, the enhancement is maximal at intermediate auditory noise levels. When the auditory and visual stimuli differ slightly in high noise, the model makes a counterintuitive prediction: as sound quality increases, the proportion of reported words corresponding to the visual stimulus should first increase and then decrease. We confirm this prediction in a behavioral experiment. We conclude that auditory-visual speech perception obeys the same notion of optimality previously observed only for simple multisensory stimuli.

Connecting Performance Analysis and Visualization to Advance Extreme Scale Computing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bremer, Peer-Timo; Mohr, Bernd; Schulz, Martin

2015-07-29

The characterization, modeling, analysis, and tuning of software performance has been a central topic in High Performance Computing (HPC) since its early beginnings. The overall goal is to make HPC software run faster on particular hardware, either through better scheduling, on-node resource utilization, or more efficient distributed communication.

Associations between pathologic tumor features and preadjuvant therapy cognitive performance in women diagnosed with breast cancer.

PubMed

Koleck, Theresa A; Bender, Catherine M; Sereika, Susan M; Ryan, Christopher M; Ghotkar, Puja; Brufsky, Adam M; Jankowitz, Rachel C; McAuliffe, Priscilla F; Clark, Beth Z; Conley, Yvette P

2017-02-01

Intertumor heterogeneity has been proposed as a potential mechanism to account for variability in cognitive performance in women diagnosed with breast cancer. The purpose of this study was to explore associations between variation in pathologic tumor features (PTFs) and variability in preadjuvant therapy cognitive performance in postmenopausal women newly diagnosed with early-stage breast cancer. Participants (N = 329) completed a comprehensive battery of neuropsychological tests to evaluate cognitive performance after primary surgery but prior to initiation of adjuvant anastrozole±chemotherapy. PTF data were abstracted from medical records. Robust multiple linear regression models were fit to estimate associations between individual PTFs and the cognitive function composite domain scores. All models controlled for age, estimated intelligence, and levels of depressive symptoms, anxiety, fatigue, and pain. Diagnosis of a HER2-positive tumor contributed to poorer verbal (b = -0.287, P = 0.018), visual (b = -0.270, P = 0.001), and visual working (b = -0.490, P < 0.001) memory performance compared to diagnosis of a HER2-negative tumor. Similarly, as HER2 immunohistochemistry classification score increased, verbal (b = -0.072, P = 0.093), visual (b = -0.081, P = 0.003), and visual working (b = -0.170, P < 0.001) memory performance score decreased. Associations with performance were also noted between location, focality/centricity, hormone receptor expression, cellular proliferation (i.e., Ki67), and Oncotype DX ® Breast Cancer Assay Recurrence Score ® .) Our results suggest that certain PTFs related to more aggressive tumor phenotypes or inferior breast cancer prognosis may be implicated in poorer preadjuvant therapy cognitive performance. Follow-up studies that include a cognitive assessment before primary surgery should be conducted to further delineate the role of intertumor heterogeneity on cognitive performance. © 2016 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Moon Trek: NASA's New Online Portal for Lunar Mapping and Modeling

NASA Astrophysics Data System (ADS)

Day, B. H.; Law, E. S.

2016-11-01

This presentation introduces Moon Trek, a new name for a major new release of NASA's Lunar Mapping and Modeling Portal (LMMP). The new Trek interface provides greatly improved navigation, 3D visualization, performance, and reliability.

Addition of visual noise boosts evoked potential-based brain-computer interface.

PubMed

Xie, Jun; Xu, Guanghua; Wang, Jing; Zhang, Sicong; Zhang, Feng; Li, Yeping; Han, Chengcheng; Li, Lili

2014-05-14

Although noise has a proven beneficial role in brain functions, there have not been any attempts on the dedication of stochastic resonance effect in neural engineering applications, especially in researches of brain-computer interfaces (BCIs). In our study, a steady-state motion visual evoked potential (SSMVEP)-based BCI with periodic visual stimulation plus moderate spatiotemporal noise can achieve better offline and online performance due to enhancement of periodic components in brain responses, which was accompanied by suppression of high harmonics. Offline results behaved with a bell-shaped resonance-like functionality and 7-36% online performance improvements can be achieved when identical visual noise was adopted for different stimulation frequencies. Using neural encoding modeling, these phenomena can be explained as noise-induced input-output synchronization in human sensory systems which commonly possess a low-pass property. Our work demonstrated that noise could boost BCIs in addressing human needs.

76 FR 31223 - Special Conditions: Bombardier Model BD-700-1A10 and BD-700-1A11 Airplanes, Head-up Display (HUD...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-05-31

... interfere with the effective use of outside visual references for required pilot tasks. 2. To avoid... the requirements of the original approval. 3. The safety and performance of the pilot tasks associated....773 does not permit visual distortions and reflections that could interfere with the pilot's normal...

Biomarkers for PTSD

DTIC Science & Technology

2014-07-01

Molecular evidence of stress- induced acute heart injury in a mouse model simulating posttraumatic stress disorder. Proc Natl Acad Sci U S A. 2014 Feb...obtaining measures aligned with the core neurocognitive domains: IQ, working memory ( auditory /visual), processing speed, verbal memory (immediate...in the test sample and combined sample with a similar pattern for the validation sample. Similarly, performance on tests of auditory and visual

Two Exercise Programs for People with Diabetes and Visual Impairment.

ERIC Educational Resources Information Center

Dods, J.

1993-01-01

This article describes two programs, one in Australia and one in the United States, that teach people with diabetes and visual impairment to incorporate proper diets and exercise into their daily lives and thus to gain better control of their blood glucose levels. It also presents a basic model of an exercise regimen that clients can perform at…

Virtual reality training and assessment in laparoscopic rectum surgery.

PubMed

Pan, Jun J; Chang, Jian; Yang, Xiaosong; Liang, Hui; Zhang, Jian J; Qureshi, Tahseen; Howell, Robert; Hickish, Tamas

2015-06-01

Virtual-reality (VR) based simulation techniques offer an efficient and low cost alternative to conventional surgery training. This article describes a VR training and assessment system in laparoscopic rectum surgery. To give a realistic visual performance of interaction between membrane tissue and surgery tools, a generalized cylinder based collision detection and a multi-layer mass-spring model are presented. A dynamic assessment model is also designed for hierarchy training evaluation. With this simulator, trainees can operate on the virtual rectum with both visual and haptic sensation feedback simultaneously. The system also offers surgeons instructions in real time when improper manipulation happens. The simulator has been tested and evaluated by ten subjects. This prototype system has been verified by colorectal surgeons through a pilot study. They believe the visual performance and the tactile feedback are realistic. It exhibits the potential to effectively improve the surgical skills of trainee surgeons and significantly shorten their learning curve. Copyright © 2014 John Wiley & Sons, Ltd.

Size-Sensitive Perceptual Representations Underlie Visual and Haptic Object Recognition

PubMed Central

Craddock, Matt; Lawson, Rebecca

2009-01-01

A variety of similarities between visual and haptic object recognition suggests that the two modalities may share common representations. However, it is unclear whether such common representations preserve low-level perceptual features or whether transfer between vision and haptics is mediated by high-level, abstract representations. Two experiments used a sequential shape-matching task to examine the effects of size changes on unimodal and crossmodal visual and haptic object recognition. Participants felt or saw 3D plastic models of familiar objects. The two objects presented on a trial were either the same size or different sizes and were the same shape or different but similar shapes. Participants were told to ignore size changes and to match on shape alone. In Experiment 1, size changes on same-shape trials impaired performance similarly for both visual-to-visual and haptic-to-haptic shape matching. In Experiment 2, size changes impaired performance on both visual-to-haptic and haptic-to-visual shape matching and there was no interaction between the cost of size changes and direction of transfer. Together the unimodal and crossmodal matching results suggest that the same, size-specific perceptual representations underlie both visual and haptic object recognition, and indicate that crossmodal memory for objects must be at least partly based on common perceptual representations. PMID:19956685

Video quality assessment method motivated by human visual perception

NASA Astrophysics Data System (ADS)

He, Meiling; Jiang, Gangyi; Yu, Mei; Song, Yang; Peng, Zongju; Shao, Feng

2016-11-01

Research on video quality assessment (VQA) plays a crucial role in improving the efficiency of video coding and the performance of video processing. It is well acknowledged that the motion energy model generates motion energy responses in a middle temporal area by simulating the receptive field of neurons in V1 for the motion perception of the human visual system. Motivated by the biological evidence for the visual motion perception, a VQA method is proposed in this paper, which comprises the motion perception quality index and the spatial index. To be more specific, the motion energy model is applied to evaluate the temporal distortion severity of each frequency component generated from the difference of Gaussian filter bank, which produces the motion perception quality index, and the gradient similarity measure is used to evaluate the spatial distortion of the video sequence to get the spatial quality index. The experimental results of the LIVE, CSIQ, and IVP video databases demonstrate that the random forests regression technique trained by the generated quality indices is highly correspondent to human visual perception and has many significant improvements than comparable well-performing methods. The proposed method has higher consistency with subjective perception and higher generalization capability.

Memory assessment and depression: testing for factor structure and measurement invariance of the Wechsler Memory Scale-Fourth Edition across a clinical and matched control sample.

PubMed

Pauls, Franz; Petermann, Franz; Lepach, Anja Christina

2013-01-01

Between-group comparisons are permissible and meaningfully interpretable only if diagnostic instruments are proved to measure the same latent dimensions across different groups. Addressing this issue, the present study was carried out to provide a rigorous test of measurement invariance. Confirmatory factor analyses were used to determine which model solution could best explain memory performance as measured by the Wechsler Memory Scale-Fourth Edition (WMS-IV) in a clinical depression sample and in healthy controls. Multigroup confirmatory factor analysis was conducted to evaluate the evidence for measurement invariance. A three-factor model solution including the dimensions of auditory memory, visual memory, and visual working memory was identified to best fit the data in both samples, and measurement invariance was partially satisfied. The results supported clinical utility of the WMS-IV--that is, auditory and visual memory performances of patients with depressive disorders are interpretable on the basis of the WMS-IV standardization data. However, possible differences in visual working memory functions between healthy and depressed individuals could restrict comparisons of the WMS-IV working memory index.

Visual-search model observer for assessing mass detection in CT

NASA Astrophysics Data System (ADS)

Karbaschi, Zohreh; Gifford, Howard C.

2017-03-01

Our aim is to devise model observers (MOs) to evaluate acquisition protocols in medical imaging. To optimize protocols for human observers, an MO must reliably interpret images containing quantum and anatomical noise under aliasing conditions. In this study of sampling parameters for simulated lung CT, the lesion-detection performance of human observers was compared with that of visual-search (VS) observers, a channelized nonprewhitening (CNPW) observer, and a channelized Hoteling (CH) observer. Scans of a mathematical torso phantom modeled single-slice parallel-hole CT with varying numbers of detector pixels and angular projections. Circular lung lesions had a fixed radius. Twodimensional FBP reconstructions were performed. A localization ROC study was conducted with the VS, CNPW and human observers, while the CH observer was applied in a location-known ROC study. Changing the sampling parameters had negligible effect on the CNPW and CH observers, whereas several VS observers demonstrated a sensitivity to sampling artifacts that was in agreement with how the humans performed.

Short temporal asynchrony disrupts visual object recognition

PubMed Central

Singer, Jedediah M.; Kreiman, Gabriel

2014-01-01

Humans can recognize objects and scenes in a small fraction of a second. The cascade of signals underlying rapid recognition might be disrupted by temporally jittering different parts of complex objects. Here we investigated the time course over which shape information can be integrated to allow for recognition of complex objects. We presented fragments of object images in an asynchronous fashion and behaviorally evaluated categorization performance. We observed that visual recognition was significantly disrupted by asynchronies of approximately 30 ms, suggesting that spatiotemporal integration begins to break down with even small deviations from simultaneity. However, moderate temporal asynchrony did not completely obliterate recognition; in fact, integration of visual shape information persisted even with an asynchrony of 100 ms. We describe the data with a concise model based on the dynamic reduction of uncertainty about what image was presented. These results emphasize the importance of timing in visual processing and provide strong constraints for the development of dynamical models of visual shape recognition. PMID:24819738

Attraction of position preference by spatial attention throughout human visual cortex.

PubMed

Klein, Barrie P; Harvey, Ben M; Dumoulin, Serge O

2014-10-01

Voluntary spatial attention concentrates neural resources at the attended location. Here, we examined the effects of spatial attention on spatial position selectivity in humans. We measured population receptive fields (pRFs) using high-field functional MRI (fMRI) (7T) while subjects performed an attention-demanding task at different locations. We show that spatial attention attracts pRF preferred positions across the entire visual field, not just at the attended location. This global change in pRF preferred positions systematically increases up the visual hierarchy. We model these pRF preferred position changes as an interaction between two components: an attention field and a pRF without the influence of attention. This computational model suggests that increasing effects of attention up the hierarchy result primarily from differences in pRF size and that the attention field is similar across the visual hierarchy. A similar attention field suggests that spatial attention transforms different neural response selectivities throughout the visual hierarchy in a similar manner. Copyright © 2014 Elsevier Inc. All rights reserved.

On the Visual Input Driving Human Smooth-Pursuit Eye Movements

NASA Technical Reports Server (NTRS)

Stone, Leland S.; Beutter, Brent R.; Lorenceau, Jean

1996-01-01

Current computational models of smooth-pursuit eye movements assume that the primary visual input is local retinal-image motion (often referred to as retinal slip). However, we show that humans can pursue object motion with considerable accuracy, even in the presence of conflicting local image motion. This finding indicates that the visual cortical area(s) controlling pursuit must be able to perform a spatio-temporal integration of local image motion into a signal related to object motion. We also provide evidence that the object-motion signal that drives pursuit is related to the signal that supports perception. We conclude that current models of pursuit should be modified to include a visual input that encodes perceived object motion and not merely retinal image motion. Finally, our findings suggest that the measurement of eye movements can be used to monitor visual perception, with particular value in applied settings as this non-intrusive approach would not require interrupting ongoing work or training.

Bag of Visual Words Model with Deep Spatial Features for Geographical Scene Classification

PubMed Central

Wu, Lin

2017-01-01

With the popular use of geotagging images, more and more research efforts have been placed on geographical scene classification. In geographical scene classification, valid spatial feature selection can significantly boost the final performance. Bag of visual words (BoVW) can do well in selecting feature in geographical scene classification; nevertheless, it works effectively only if the provided feature extractor is well-matched. In this paper, we use convolutional neural networks (CNNs) for optimizing proposed feature extractor, so that it can learn more suitable visual vocabularies from the geotagging images. Our approach achieves better performance than BoVW as a tool for geographical scene classification, respectively, in three datasets which contain a variety of scene categories. PMID:28706534

Cognitive predictors of copying and drawing from memory of the Rey-Osterrieth complex figure in 7- to 10-year-old children.

PubMed

Senese, Vincenzo Paolo; De Lucia, Natascia; Conson, Massimiliano

2015-01-01

Cognitive models of drawing are mainly based on assessment of copying performance of adults, whereas only a few studies have verified these models in young children. Moreover, developmental investigations have only rarely performed a systematic examination of the contribution of perceptual and representational visuo-spatial processes to copying and drawing from memory. In this study we investigated the role of visual perception and mental representation in both copying and drawing from memory skills in a sample of 227 typically developing children (53% females) aged 7-10 years. Participants underwent a neuropsychological assessment and the Rey-Osterrieth Complex Figure (ROCF). The fit and invariance of the predictive model considering visuo-spatial abilities, working memory, and executive functions were tested by means of hierarchical regressions and path analysis. Results showed that, in a gender invariant way, visual perception abilities and spatial mental representation had a direct effect on copying performance, whereas copying performance was the only specific predictor for drawing from memory. These effects were independent from age and socioeconomic status, and showed that cognitive models of drawing built up for adults could be considered for predicting copying and drawing from memory in children.

Acute exercise and aerobic fitness influence selective attention during visual search.

PubMed

Bullock, Tom; Giesbrecht, Barry

2014-01-01

Successful goal directed behavior relies on a human attention system that is flexible and able to adapt to different conditions of physiological stress. However, the effects of physical activity on multiple aspects of selective attention and whether these effects are mediated by aerobic capacity, remains unclear. The aim of the present study was to investigate the effects of a prolonged bout of physical activity on visual search performance and perceptual distraction. Two groups of participants completed a hybrid visual search flanker/response competition task in an initial baseline session and then at 17-min intervals over a 2 h 16 min test period. Participants assigned to the exercise group engaged in steady-state aerobic exercise between completing blocks of the visual task, whereas participants assigned to the control group rested in between blocks. The key result was a correlation between individual differences in aerobic capacity and visual search performance, such that those individuals that were more fit performed the search task more quickly. Critically, this relationship only emerged in the exercise group after the physical activity had begun. The relationship was not present in either group at baseline and never emerged in the control group during the test period, suggesting that under these task demands, aerobic capacity may be an important determinant of visual search performance under physical stress. The results enhance current understanding about the relationship between exercise and cognition, and also inform current models of selective attention.

Acute exercise and aerobic fitness influence selective attention during visual search

PubMed Central

Bullock, Tom; Giesbrecht, Barry

2014-01-01

Successful goal directed behavior relies on a human attention system that is flexible and able to adapt to different conditions of physiological stress. However, the effects of physical activity on multiple aspects of selective attention and whether these effects are mediated by aerobic capacity, remains unclear. The aim of the present study was to investigate the effects of a prolonged bout of physical activity on visual search performance and perceptual distraction. Two groups of participants completed a hybrid visual search flanker/response competition task in an initial baseline session and then at 17-min intervals over a 2 h 16 min test period. Participants assigned to the exercise group engaged in steady-state aerobic exercise between completing blocks of the visual task, whereas participants assigned to the control group rested in between blocks. The key result was a correlation between individual differences in aerobic capacity and visual search performance, such that those individuals that were more fit performed the search task more quickly. Critically, this relationship only emerged in the exercise group after the physical activity had begun. The relationship was not present in either group at baseline and never emerged in the control group during the test period, suggesting that under these task demands, aerobic capacity may be an important determinant of visual search performance under physical stress. The results enhance current understanding about the relationship between exercise and cognition, and also inform current models of selective attention. PMID:25426094

Attentional Control in Visual Signal Detection: Effects of Abrupt-Onset and No-Onset Stimuli

ERIC Educational Resources Information Center

Sewell, David K.; Smith, Philip L.

2012-01-01

The attention literature distinguishes two general mechanisms by which attention can benefit performance: gain (or resource) models and orienting (or switching) models. In gain models, processing efficiency is a function of a spatial distribution of capacity or resources; in orienting models, an attentional spotlight must be aligned with the…

Biologically Inspired Visual Model With Preliminary Cognition and Active Attention Adjustment.

PubMed

Qiao, Hong; Xi, Xuanyang; Li, Yinlin; Wu, Wei; Li, Fengfu

2015-11-01

Recently, many computational models have been proposed to simulate visual cognition process. For example, the hierarchical Max-Pooling (HMAX) model was proposed according to the hierarchical and bottom-up structure of V1 to V4 in the ventral pathway of primate visual cortex, which could achieve position- and scale-tolerant recognition. In our previous work, we have introduced memory and association into the HMAX model to simulate visual cognition process. In this paper, we improve our theoretical framework by mimicking a more elaborate structure and function of the primate visual cortex. We will mainly focus on the new formation of memory and association in visual processing under different circumstances as well as preliminary cognition and active adjustment in the inferior temporal cortex, which are absent in the HMAX model. The main contributions of this paper are: 1) in the memory and association part, we apply deep convolutional neural networks to extract various episodic features of the objects since people use different features for object recognition. Moreover, to achieve a fast and robust recognition in the retrieval and association process, different types of features are stored in separated clusters and the feature binding of the same object is stimulated in a loop discharge manner and 2) in the preliminary cognition and active adjustment part, we introduce preliminary cognition to classify different types of objects since distinct neural circuits in a human brain are used for identification of various types of objects. Furthermore, active cognition adjustment of occlusion and orientation is implemented to the model to mimic the top-down effect in human cognition process. Finally, our model is evaluated on two face databases CAS-PEAL-R1 and AR. The results demonstrate that our model exhibits its efficiency on visual recognition process with much lower memory storage requirement and a better performance compared with the traditional purely computational methods.

The role of visual and spatial working memory in forming mental models derived from survey and route descriptions.

PubMed

Meneghetti, Chiara; Labate, Enia; Pazzaglia, Francesca; Hamilton, Colin; Gyselinck, Valérie

2017-05-01

This study examines the involvement of spatial and visual working memory (WM) in the construction of flexible spatial models derived from survey and route descriptions. Sixty young adults listened to environment descriptions, 30 from a survey perspective and the other 30 from a route perspective, while they performed spatial (spatial tapping [ST]) and visual (dynamic visual noise [DVN]) secondary tasks - believed to overload the spatial and visual working memory (WM) components, respectively - or no secondary task (control, C). Their mental representations of the environment were tested by free recall and a verification test with both route and survey statements. Results showed that, for both recall tasks, accuracy was worse in the ST than in the C or DVN conditions. In the verification test, the effect of both ST and DVN was a decreasing accuracy for sentences testing spatial relations from the opposite perspective to the one learnt than if the perspective was the same; only ST had a stronger interference effect than the C condition for sentences from the opposite perspective from the one learnt. Overall, these findings indicate that both visual and spatial WM, and especially the latter, are involved in the construction of perspective-flexible spatial models. © 2016 The British Psychological Society.

Visual-auditory integration during speech imitation in autism.

PubMed

Williams, Justin H G; Massaro, Dominic W; Peel, Natalie J; Bosseler, Alexis; Suddendorf, Thomas

2004-01-01

Children with autistic spectrum disorder (ASD) may have poor audio-visual integration, possibly reflecting dysfunctional 'mirror neuron' systems which have been hypothesised to be at the core of the condition. In the present study, a computer program, utilizing speech synthesizer software and a 'virtual' head (Baldi), delivered speech stimuli for identification in auditory, visual or bimodal conditions. Children with ASD were poorer than controls at recognizing stimuli in the unimodal conditions, but once performance on this measure was controlled for, no group difference was found in the bimodal condition. A group of participants with ASD were also trained to develop their speech-reading ability. Training improved visual accuracy and this also improved the children's ability to utilize visual information in their processing of speech. Overall results were compared to predictions from mathematical models based on integration and non-integration, and were most consistent with the integration model. We conclude that, whilst they are less accurate in recognizing stimuli in the unimodal condition, children with ASD show normal integration of visual and auditory speech stimuli. Given that training in recognition of visual speech was effective, children with ASD may benefit from multi-modal approaches in imitative therapy and language training.

Stereo chromatic contrast sensitivity model to blue-yellow gratings.

PubMed

Yang, Jiachen; Lin, Yancong; Liu, Yun

2016-03-07

As a fundamental metric of human visual system (HVS), contrast sensitivity function (CSF) is typically measured by sinusoidal gratings at the detection of thresholds for psychophysically defined cardinal channels: luminance, red-green, and blue-yellow. Chromatic CSF, which is a quick and valid index to measure human visual performance and various retinal diseases in two-dimensional (2D) space, can not be directly applied into the measurement of human stereo visual performance. And no existing perception model considers the influence of chromatic CSF of inclined planes on depth perception in three-dimensional (3D) space. The main aim of this research is to extend traditional chromatic contrast sensitivity characteristics to 3D space and build a model applicable in 3D space, for example, strengthening stereo quality of 3D images. This research also attempts to build a vision model or method to check human visual characteristics of stereo blindness. In this paper, CRT screen was clockwise and anti-clockwise rotated respectively to form the inclined planes. Four inclined planes were selected to investigate human chromatic vision in 3D space and contrast threshold of each inclined plane was measured with 18 observers. Stimuli were isoluminant blue-yellow sinusoidal gratings. Horizontal spatial frequencies ranged from 0.05 to 5 c/d. Contrast sensitivity was calculated as the inverse function of the pooled cone contrast threshold. According to the relationship between spatial frequency of inclined plane and horizontal spatial frequency, the chromatic contrast sensitivity characteristics in 3D space have been modeled based on the experimental data. The results show that the proposed model can well predicted human chromatic contrast sensitivity characteristics in 3D space.

Development of a human eye model incorporated with intraocular scattering for visual performance assessment

NASA Astrophysics Data System (ADS)

Chen, Yi-Chun; Jiang, Chong-Jhih; Yang, Tsung-Hsun; Sun, Ching-Cherng

2012-07-01

A biometry-based human eye model was developed by using the empirical anatomic and optical data of ocular parameters. The gradient refractive index of the crystalline lens was modeled by concentric conicoid isoindical surfaces and was adaptive to accommodation and age. The chromatic dispersion of ocular media was described by Cauchy equations. The intraocular scattering model was composed of volumetric Mie scattering in the cornea and the crystalline lens, and a diffusive-surface model at the retina fundus. The retina was regarded as a Lambertian surface and was assigned its corresponding reflectance at each wavelength. The optical performance of the eye model was evaluated in CodeV and ASAP and presented by the modulation transfer functions at single and multiple wavelengths. The chromatic optical powers obtained from this model resembled that of the average physiological eyes. The scattering property was assessed by means of glare veiling luminance and compared with the CIE general disability glare equation. By replacing the transparent lens with a cataractous lens, the disability glare curve of cataracts was generated to compare with the normal disability glare curve. This model has high potential for investigating visual performance in ordinary lighting and display conditions and under the influence of glare sources.

Attention mediates the flexible allocation of visual working memory resources.

PubMed

Emrich, Stephen M; Lockhart, Holly A; Al-Aidroos, Naseem

2017-07-01

Though it is clear that it is impossible to store an unlimited amount of information in visual working memory (VWM), the limiting mechanisms remain elusive. While several models of VWM limitations exist, these typically characterize changes in performance as a function of the number of to-be-remembered items. Here, we examine whether changes in spatial attention could better account for VWM performance, independent of load. Across 2 experiments, performance was better predicted by the prioritization of memory items (i.e., attention) than by the number of items to be remembered (i.e., memory load). This relationship followed a power law, and held regardless of whether performance was assessed based on overall precision or any of 3 measures in a mixture model. Moreover, at large set sizes, even minimally attended items could receive a small proportion of resources, without any evidence for a discrete-capacity on the number of items that could be maintained in VWM. Finally, the observed data were best fit by a variable-precision model in which response error was related to the proportion of resources allocated to each item, consistent with a model of VWM in which performance is determined by the continuous allocation of attentional resources during encoding. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A Neurophysiologically Plausible Population Code Model for Feature Integration Explains Visual Crowding

PubMed Central

van den Berg, Ronald; Roerdink, Jos B. T. M.; Cornelissen, Frans W.

2010-01-01

An object in the peripheral visual field is more difficult to recognize when surrounded by other objects. This phenomenon is called “crowding”. Crowding places a fundamental constraint on human vision that limits performance on numerous tasks. It has been suggested that crowding results from spatial feature integration necessary for object recognition. However, in the absence of convincing models, this theory has remained controversial. Here, we present a quantitative and physiologically plausible model for spatial integration of orientation signals, based on the principles of population coding. Using simulations, we demonstrate that this model coherently accounts for fundamental properties of crowding, including critical spacing, “compulsory averaging”, and a foveal-peripheral anisotropy. Moreover, we show that the model predicts increased responses to correlated visual stimuli. Altogether, these results suggest that crowding has little immediate bearing on object recognition but is a by-product of a general, elementary integration mechanism in early vision aimed at improving signal quality. PMID:20098499

Demographic, Maltreatment, and Neurobiological Correlates of PTSD Symptoms in Children and Adolescents

PubMed Central

Hooper, Stephen R.; Woolley, Donald P.; Shenk, Chad E.

2010-01-01

Objective To examine the relationships of demographic, maltreatment, neurostructural and neuropsychological measures with total posttraumatic stress disorder (PTSD) symptoms. Methods Participants included 216 children with maltreatment histories (N = 49), maltreatment and PTSD (N = 49), or no maltreatment (N = 118). Participants received diagnostic interviews, brain imaging, and neuropsychological evaluations. Results We examined a hierarchical regression model comprised of independent variables including demographics, trauma and maltreatment-related variables, and hippocampal volumes and neuropsychological measures to model PTSD symptoms. Important independent contributors to this model were SES, and General Maltreatment and Sexual Abuse Factors. Although hippocampal volumes were not significant, Visual Memory was a significant contributor to this model. Conclusions Similar to adult PTSD, pediatric PTSD symptoms are associated with lower Visual Memory performance. It is an important correlate of PTSD beyond established predictors of PTSD symptoms. These results support models of developmental traumatology and suggest that treatments which enhance visual memory may decrease symptoms of PTSD. PMID:20008084

A Predictive Model of Anesthesia Depth Based on SVM in the Primary Visual Cortex

PubMed Central

Shi, Li; Li, Xiaoyuan; Wan, Hong

2013-01-01

In this paper, a novel model for predicting anesthesia depth is put forward based on local field potentials (LFPs) in the primary visual cortex (V1 area) of rats. The model is constructed using a Support Vector Machine (SVM) to realize anesthesia depth online prediction and classification. The raw LFP signal was first decomposed into some special scaling components. Among these components, those containing higher frequency information were well suited for more precise analysis of the performance of the anesthetic depth by wavelet transform. Secondly, the characteristics of anesthetized states were extracted by complexity analysis. In addition, two frequency domain parameters were selected. The above extracted features were used as the input vector of the predicting model. Finally, we collected the anesthesia samples from the LFP recordings under the visual stimulus experiments of Long Evans rats. Our results indicate that the predictive model is accurate and computationally fast, and that it is also well suited for online predicting. PMID:24044024

Visualizing weighted networks: a performance comparison of adjacency matrices versus node-link diagrams

NASA Astrophysics Data System (ADS)

McIntire, John P.; Osesina, O. Isaac; Bartley, Cecilia; Tudoreanu, M. Eduard; Havig, Paul R.; Geiselman, Eric E.

2012-06-01

Ensuring the proper and effective ways to visualize network data is important for many areas of academia, applied sciences, the military, and the public. Fields such as social network analysis, genetics, biochemistry, intelligence, cybersecurity, neural network modeling, transit systems, communications, etc. often deal with large, complex network datasets that can be difficult to interact with, study, and use. There have been surprisingly few human factors performance studies on the relative effectiveness of different graph drawings or network diagram techniques to convey information to a viewer. This is particularly true for weighted networks which include the strength of connections between nodes, not just information about which nodes are linked to other nodes. We describe a human factors study in which participants performed four separate network analysis tasks (finding a direct link between given nodes, finding an interconnected node between given nodes, estimating link strengths, and estimating the most densely interconnected nodes) on two different network visualizations: an adjacency matrix with a heat-map versus a node-link diagram. The results should help shed light on effective methods of visualizing network data for some representative analysis tasks, with the ultimate goal of improving usability and performance for viewers of network data displays.

Solving Large Problems with a Small Working Memory

ERIC Educational Resources Information Center

Pizlo, Zygmunt; Stefanov, Emil

2013-01-01

We describe an important elaboration of our multiscale/multiresolution model for solving the Traveling Salesman Problem (TSP). Our previous model emulated the non-uniform distribution of receptors on the human retina and the shifts of visual attention. This model produced near-optimal solutions of TSP in linear time by performing hierarchical…

GABAergic modulation of visual gamma and alpha oscillations and its consequences for working memory performance.

PubMed

Lozano-Soldevilla, Diego; ter Huurne, Niels; Cools, Roshan; Jensen, Ole

2014-12-15

Impressive in vitro research in rodents and computational modeling has uncovered the core mechanisms responsible for generating neuronal oscillations. In particular, GABAergic interneurons play a crucial role for synchronizing neural populations. Do these mechanistic principles apply to human oscillations associated with function? To address this, we recorded ongoing brain activity using magnetoencephalography (MEG) in healthy human subjects participating in a double-blind pharmacological study receiving placebo, 0.5 mg and 1.5 mg of lorazepam (LZP; a benzodiazepine upregulating GABAergic conductance). Participants performed a demanding visuospatial working memory (WM) task. We found that occipital gamma power associated with WM recognition increased with LZP dosage. Importantly, the frequency of the gamma activity decreased with dosage, as predicted by models derived from the rat hippocampus. A regionally specific gamma increase correlated with the drug-related performance decrease. Despite the system-wide pharmacological intervention, gamma power drug modulations were specific to visual cortex: sensorimotor gamma power and frequency during button presses remained unaffected. In contrast, occipital alpha power modulations during the delay interval decreased parametrically with drug dosage, predicting performance impairment. Consistent with alpha oscillations reflecting functional inhibition, LZP affected alpha power strongly in early visual regions not required for the task demonstrating a regional specific occipital impairment. GABAergic interneurons are strongly implicated in the generation of gamma and alpha oscillations in human occipital cortex where drug-induced power modulations predicted WM performance. Our findings bring us an important step closer to linking neuronal dynamics to behavior by embracing established animal models. Copyright © 2014 Elsevier Ltd. All rights reserved.

Concepts to Support HRP Integration Using Publications and Modeling

NASA Technical Reports Server (NTRS)

Mindock, J.; Lumpkins, S.; Shelhamer, M.

2014-01-01

Initial efforts are underway to enhance the Human Research Program (HRP)'s identification and support of potential cross-disciplinary scientific collaborations. To increase the emphasis on integration in HRP's science portfolio management, concepts are being explored through the development of a set of tools. These tools are intended to enable modeling, analysis, and visualization of the state of the human system in the spaceflight environment; HRP's current understanding of that state with an indication of uncertainties; and how that state changes due to HRP programmatic progress and design reference mission definitions. In this talk, we will discuss proof-of-concept work performed using a subset of publications captured in the HRP publications database. The publications were tagged in the database with words representing factors influencing health and performance in spaceflight, as well as with words representing the risks HRP research is reducing. Analysis was performed on the publication tag data to identify relationships between factors and between risks. Network representations were then created as one type of visualization of these relationships. This enables future analyses of the structure of the networks based on results from network theory. Such analyses can provide insights into HRP's current human system knowledge state as informed by the publication data. The network structure analyses can also elucidate potential improvements by identifying network connections to establish or strengthen for maximized information flow. The relationships identified in the publication data were subsequently used as inputs to a model captured in the Systems Modeling Language (SysML), which functions as a repository for relationship information to be gleaned from multiple sources. Example network visualization outputs from a simple SysML model were then also created to compare to the visualizations based on the publication data only. We will also discuss ideas for building upon this proof-of-concept work to further support an integrated approach to human spaceflight risk reduction.

Visual-vestibular cue integration for heading perception: applications of optimal cue integration theory.

PubMed

Fetsch, Christopher R; Deangelis, Gregory C; Angelaki, Dora E

2010-05-01

The perception of self-motion is crucial for navigation, spatial orientation and motor control. In particular, estimation of one's direction of translation, or heading, relies heavily on multisensory integration in most natural situations. Visual and nonvisual (e.g., vestibular) information can be used to judge heading, but each modality alone is often insufficient for accurate performance. It is not surprising, then, that visual and vestibular signals converge frequently in the nervous system, and that these signals interact in powerful ways at the level of behavior and perception. Early behavioral studies of visual-vestibular interactions consisted mainly of descriptive accounts of perceptual illusions and qualitative estimation tasks, often with conflicting results. In contrast, cue integration research in other modalities has benefited from the application of rigorous psychophysical techniques, guided by normative models that rest on the foundation of ideal-observer analysis and Bayesian decision theory. Here we review recent experiments that have attempted to harness these so-called optimal cue integration models for the study of self-motion perception. Some of these studies used nonhuman primate subjects, enabling direct comparisons between behavioral performance and simultaneously recorded neuronal activity. The results indicate that humans and monkeys can integrate visual and vestibular heading cues in a manner consistent with optimal integration theory, and that single neurons in the dorsal medial superior temporal area show striking correlates of the behavioral effects. This line of research and other applications of normative cue combination models should continue to shed light on mechanisms of self-motion perception and the neuronal basis of multisensory integration.

Manipulating the fidelity of lower extremity visual feedback to identify obstacle negotiation strategies in immersive virtual reality.

PubMed

Kim, Aram; Zhou, Zixuan; Kretch, Kari S; Finley, James M

2017-07-01

The ability to successfully navigate obstacles in our environment requires integration of visual information about the environment with estimates of our body's state. Previous studies have used partial occlusion of the visual field to explore how information about the body and impending obstacles are integrated to mediate a successful clearance strategy. However, because these manipulations often remove information about both the body and obstacle, it remains to be seen how information about the lower extremities alone is utilized during obstacle crossing. Here, we used an immersive virtual reality (VR) interface to explore how visual feedback of the lower extremities influences obstacle crossing performance. Participants wore a head-mounted display while walking on treadmill and were instructed to step over obstacles in a virtual corridor in four different feedback trials. The trials involved: (1) No visual feedback of the lower extremities, (2) an endpoint-only model, (3) a link-segment model, and (4) a volumetric multi-segment model. We found that the volumetric model improved success rate, placed their trailing foot before crossing and leading foot after crossing more consistently, and placed their leading foot closer to the obstacle after crossing compared to no model. This knowledge is critical for the design of obstacle negotiation tasks in immersive virtual environments as it may provide information about the fidelity necessary to reproduce ecologically valid practice environments.

Quality-Related Monitoring and Grading of Granulated Products by Weibull-Distribution Modeling of Visual Images with Semi-Supervised Learning

PubMed Central

Liu, Jinping; Tang, Zhaohui; Xu, Pengfei; Liu, Wenzhong; Zhang, Jin; Zhu, Jianyong

2016-01-01

The topic of online product quality inspection (OPQI) with smart visual sensors is attracting increasing interest in both the academic and industrial communities on account of the natural connection between the visual appearance of products with their underlying qualities. Visual images captured from granulated products (GPs), e.g., cereal products, fabric textiles, are comprised of a large number of independent particles or stochastically stacking locally homogeneous fragments, whose analysis and understanding remains challenging. A method of image statistical modeling-based OPQI for GP quality grading and monitoring by a Weibull distribution(WD) model with a semi-supervised learning classifier is presented. WD-model parameters (WD-MPs) of GP images’ spatial structures, obtained with omnidirectional Gaussian derivative filtering (OGDF), which were demonstrated theoretically to obey a specific WD model of integral form, were extracted as the visual features. Then, a co-training-style semi-supervised classifier algorithm, named COSC-Boosting, was exploited for semi-supervised GP quality grading, by integrating two independent classifiers with complementary nature in the face of scarce labeled samples. Effectiveness of the proposed OPQI method was verified and compared in the field of automated rice quality grading with commonly-used methods and showed superior performance, which lays a foundation for the quality control of GP on assembly lines. PMID:27367703

Correction of Refractive Errors in Rhesus Macaques (Macaca mulatta) Involved in Visual Research

PubMed Central

Mitchell, Jude F; Boisvert, Chantal J; Reuter, Jon D; Reynolds, John H; Leblanc, Mathias

2014-01-01

Macaques are the most common animal model for studies in vision research, and due to their high value as research subjects, often continue to participate in studies well into old age. As is true in humans, visual acuity in macaques is susceptible to refractive errors. Here we report a case study in which an aged macaque demonstrated clear impairment in visual acuity according to performance on a demanding behavioral task. Refraction demonstrated bilateral myopia that significantly affected behavioral and visual tasks. Using corrective lenses, we were able to restore visual acuity. After correction of myopia, the macaque's performance on behavioral tasks was comparable to that of a healthy control. We screened 20 other male macaques to assess the incidence of refractive errors and ocular pathologies in a larger population. Hyperopia was the most frequent ametropia but was mild in all cases. A second macaque had mild myopia and astigmatism in one eye. There were no other pathologies observed on ocular examination. We developed a simple behavioral task that visual research laboratories could use to test visual acuity in macaques. The test was reliable and easily learned by the animals in 1 d. This case study stresses the importance of screening macaques involved in visual science for refractive errors and ocular pathologies to ensure the quality of research; we also provide simple methodology for screening visual acuity in these animals. PMID:25427343

Correction of refractive errors in rhesus macaques (Macaca mulatta) involved in visual research.

PubMed

Mitchell, Jude F; Boisvert, Chantal J; Reuter, Jon D; Reynolds, John H; Leblanc, Mathias

2014-08-01

Macaques are the most common animal model for studies in vision research, and due to their high value as research subjects, often continue to participate in studies well into old age. As is true in humans, visual acuity in macaques is susceptible to refractive errors. Here we report a case study in which an aged macaque demonstrated clear impairment in visual acuity according to performance on a demanding behavioral task. Refraction demonstrated bilateral myopia that significantly affected behavioral and visual tasks. Using corrective lenses, we were able to restore visual acuity. After correction of myopia, the macaque's performance on behavioral tasks was comparable to that of a healthy control. We screened 20 other male macaques to assess the incidence of refractive errors and ocular pathologies in a larger population. Hyperopia was the most frequent ametropia but was mild in all cases. A second macaque had mild myopia and astigmatism in one eye. There were no other pathologies observed on ocular examination. We developed a simple behavioral task that visual research laboratories could use to test visual acuity in macaques. The test was reliable and easily learned by the animals in 1 d. This case study stresses the importance of screening macaques involved in visual science for refractive errors and ocular pathologies to ensure the quality of research; we also provide simple methodology for screening visual acuity in these animals.

Learning to Recognize Patterns: Changes in the Visual Field with Familiarity

NASA Astrophysics Data System (ADS)

Bebko, James M.; Uchikawa, Keiji; Saida, Shinya; Ikeda, Mitsuo

1995-01-01

Two studies were conducted to investigate changes which take place in the visual information processing of novel stimuli as they become familiar. Japanese writing characters (Hiragana and Kanji) which were unfamiliar to two native English speaking subjects were presented using a moving window technique to restrict their visual fields. Study time for visual recognition was recorded across repeated sessions, and with varying visual field restrictions. The critical visual field was defined as the size of the visual field beyond which further increases did not improve the speed of recognition performance. In the first study, when the Hiragana patterns were novel, subjects needed to see about half of the entire pattern simultaneously to maintain optimal performance. However, the critical visual field size decreased as familiarity with the patterns increased. These results were replicated in the second study with more complex Kanji characters. In addition, the critical field size decreased as pattern complexity decreased. We propose a three component model of pattern perception. In the first stage a representation of the stimulus must be constructed by the subject, and restricting of the visual field interferes dramatically with this component when stimuli are unfamiliar. With increased familiarity, subjects become able to reconstruct a previous representation from very small, unique segments of the pattern, analogous to the informativeness areas hypothesized by Loftus and Mackworth [J. Exp. Psychol., 4 (1978) 565].

Accuracy of visual inspection performed by community health workers in cervical cancer screening.

PubMed

Driscoll, Susan D; Tappen, Ruth M; Newman, David; Voege-Harvey, Kathi

2018-05-22

Cervical cancer remains the leading cause of cancer and mortality in low-resource areas with healthcare personnel shortages. Visual inspection is a low-resource alternative method of cervical cancer screening in areas with limited access to healthcare. To assess accuracy of visual inspection performed by community health workers (CHWs) and licensed providers, and the effect of provider training on visual inspection accuracy. Five databases and four websites were queried for studies published in English up to December 31, 2015. Derivations of "cervical cancer screening" and "visual inspection" were search terms. Visual inspection screening studies with provider definitions, colposcopy reference standards, and accuracy data were included. A priori variables were extracted by two independent reviewers. Bivariate linear mixed-effects models were used to compare visual inspection accuracy. Provider type was a significant predictor of visual inspection sensitivity (P=0.048); sensitivity was 15 percentage points higher among CHWs than physicians (P=0.014). Components of provider training were significant predictors of sensitivity and specificity. Community-based visual inspection programs using adequately trained CHWs could reduce barriers and expand access to screening, thereby decreasing cervical cancer incidence and mortality for women at highest risk and those living in remote areas with limited access to healthcare personnel. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Clinical-Radiological Parameters Improve the Prediction of the Thrombolysis Time Window by Both MRI Signal Intensities and DWI-FLAIR Mismatch.

PubMed

Madai, Vince Istvan; Wood, Carla N; Galinovic, Ivana; Grittner, Ulrike; Piper, Sophie K; Revankar, Gajanan S; Martin, Steve Z; Zaro-Weber, Olivier; Moeller-Hartmann, Walter; von Samson-Himmelstjerna, Federico C; Heiss, Wolf-Dieter; Ebinger, Martin; Fiebach, Jochen B; Sobesky, Jan

2016-01-01

With regard to acute stroke, patients with unknown time from stroke onset are not eligible for thrombolysis. Quantitative diffusion weighted imaging (DWI) and fluid attenuated inversion recovery (FLAIR) MRI relative signal intensity (rSI) biomarkers have been introduced to predict eligibility for thrombolysis, but have shown heterogeneous results in the past. In the present work, we investigated whether the inclusion of easily obtainable clinical-radiological parameters would improve the prediction of the thrombolysis time window by rSIs and compared their performance to the visual DWI-FLAIR mismatch. In a retrospective study, patients from 2 centers with proven stroke with onset <12 h were included. The DWI lesion was segmented and overlaid on ADC and FLAIR images. rSI mean and SD, were calculated as follows: (mean ROI value/mean value of the unaffected hemisphere). Additionally, the visual DWI-FLAIR mismatch was evaluated. Prediction of the thrombolysis time window was evaluated by the area-under-the-curve (AUC) derived from receiver operating characteristic (ROC) curve analysis. Factors such as the association of age, National Institutes of Health Stroke Scale, MRI field strength, lesion size, vessel occlusion and Wahlund-Score with rSI were investigated and the models were adjusted and stratified accordingly. In 82 patients, the unadjusted rSI measures DWI-mean and -SD showed the highest AUCs (AUC 0.86-0.87). Adjustment for clinical-radiological covariates significantly improved the performance of FLAIR-mean (0.91) and DWI-SD (0.91). The best prediction results based on the AUC were found for the final stratified and adjusted models of DWI-SD (0.94) and FLAIR-mean (0.96) and a multivariable DWI-FLAIR model (0.95). The adjusted visual DWI-FLAIR mismatch did not perform in a significantly worse manner (0.89). ADC-rSIs showed fair performance in all models. Quantitative DWI and FLAIR MRI biomarkers as well as the visual DWI-FLAIR mismatch provide excellent prediction of eligibility for thrombolysis in acute stroke, when easily obtainable clinical-radiological parameters are included in the prediction models. © 2016 S. Karger AG, Basel.

A computational visual saliency model based on statistics and machine learning.

PubMed

Lin, Ru-Je; Lin, Wei-Song

2014-08-01

Identifying the type of stimuli that attracts human visual attention has been an appealing topic for scientists for many years. In particular, marking the salient regions in images is useful for both psychologists and many computer vision applications. In this paper, we propose a computational approach for producing saliency maps using statistics and machine learning methods. Based on four assumptions, three properties (Feature-Prior, Position-Prior, and Feature-Distribution) can be derived and combined by a simple intersection operation to obtain a saliency map. These properties are implemented by a similarity computation, support vector regression (SVR) technique, statistical analysis of training samples, and information theory using low-level features. This technique is able to learn the preferences of human visual behavior while simultaneously considering feature uniqueness. Experimental results show that our approach performs better in predicting human visual attention regions than 12 other models in two test databases. © 2014 ARVO.

Visualizing projected Climate Changes - the CMIP5 Multi-Model Ensemble

NASA Astrophysics Data System (ADS)

Böttinger, Michael; Eyring, Veronika; Lauer, Axel; Meier-Fleischer, Karin

2017-04-01

Large ensembles add an additional dimension to climate model simulations. Internal variability of the climate system can be assessed for example by multiple climate model simulations with small variations in the initial conditions or by analyzing the spread in large ensembles made by multiple climate models under common protocols. This spread is often used as a measure of uncertainty in climate projections. In the context of the fifth phase of the WCRP's Coupled Model Intercomparison Project (CMIP5), more than 40 different coupled climate models were employed to carry out a coordinated set of experiments. Time series of the development of integral quantities such as the global mean temperature change for all models visualize the spread in the multi-model ensemble. A similar approach can be applied to 2D-visualizations of projected climate changes such as latitude-longitude maps showing the multi-model mean of the ensemble by adding a graphical representation of the uncertainty information. This has been demonstrated for example with static figures in chapter 12 of the last IPCC report (AR5) using different so-called stippling and hatching techniques. In this work, we focus on animated visualizations of multi-model ensemble climate projections carried out within CMIP5 as a way of communicating climate change results to the scientific community as well as to the public. We take a closer look at measures of robustness or uncertainty used in recent publications suitable for animated visualizations. Specifically, we use the ESMValTool [1] to process and prepare the CMIP5 multi-model data in combination with standard visualization tools such as NCL and the commercial 3D visualization software Avizo to create the animations. We compare different visualization techniques such as height fields or shading with transparency for creating animated visualization of ensemble mean changes in temperature and precipitation including corresponding robustness measures. [1] Eyring, V., Righi, M., Lauer, A., Evaldsson, M., Wenzel, S., Jones, C., Anav, A., Andrews, O., Cionni, I., Davin, E. L., Deser, C., Ehbrecht, C., Friedlingstein, P., Gleckler, P., Gottschaldt, K.-D., Hagemann, S., Juckes, M., Kindermann, S., Krasting, J., Kunert, D., Levine, R., Loew, A., Mäkelä, J., Martin, G., Mason, E., Phillips, A. S., Read, S., Rio, C., Roehrig, R., Senftleben, D., Sterl, A., van Ulft, L. H., Walton, J., Wang, S., and Williams, K. D.: ESMValTool (v1.0) - a community diagnostic and performance metrics tool for routine evaluation of Earth system models in CMIP, Geosci. Model Dev., 9, 1747-1802, doi:10.5194/gmd-9-1747-2016, 2016.

Flow-visualization study of the X-29A aircraft at high angles of attack using a 1/48-scale model

NASA Technical Reports Server (NTRS)

Cotton, Stacey J.; Bjarke, Lisa J.

1994-01-01

A water-tunnel study on a 1/48-scale model of the X-29A aircraft was performed at the NASA Dryden Flow Visualization Facility. The water-tunnel test enhanced the results of the X-29A flight tests by providing flow-visualization data for comparison and insights into the aerodynamic characteristics of the aircraft. The model was placed in the water tunnel at angles of attack of 20 to 55 deg. and with angles of sideslip from 0 to 5 deg. In general, flow-visualization techniques provided useful information on vortex formation, separation, and breakdown and their role in yaw asymmetries and tail buffeting. Asymmetric forebody vortices were observed at angles of attack greater than 30 deg. with 0 deg. sideslip and greater than 20 deg. with 5 deg. sideslip. While the asymmetric flows observed in the water tunnel did not agree fully with the flight data, they did show some of the same trends. In addition, the flow visualization indicated that the interaction of forebody vortices and the wing wake at angles of attack between 20 and 35 deg. may cause vertical-tail buffeting observed in flight.

Increased conspicuousness can explain the match between visual sensitivities and blue plumage colours in fairy-wrens

PubMed Central

Delhey, Kaspar; Hall, Michelle; Kingma, Sjouke A.; Peters, Anne

2013-01-01

Colour signals are expected to match visual sensitivities of intended receivers. In birds, evolutionary shifts from violet-sensitive (V-type) to ultraviolet-sensitive (U-type) vision have been linked to increased prevalence of colours rich in shortwave reflectance (ultraviolet/blue), presumably due to better perception of such colours by U-type vision. Here we provide the first test of this widespread idea using fairy-wrens and allies (Family Maluridae) as a model, a family where shifts in visual sensitivities from V- to U-type eyes are associated with male nuptial plumage rich in ultraviolet/blue colours. Using psychophysical visual models, we compared the performance of both types of visual systems at two tasks: (i) detecting contrast between male plumage colours and natural backgrounds, and (ii) perceiving intraspecific chromatic variation in male plumage. While U-type outperforms V-type vision at both tasks, the crucial test here is whether U-type vision performs better at detecting and discriminating ultraviolet/blue colours when compared with other colours. This was true for detecting contrast between plumage colours and natural backgrounds (i), but not for discriminating intraspecific variability (ii). Our data indicate that selection to maximize conspicuousness to conspecifics may have led to the correlation between ultraviolet/blue colours and U-type vision in this clade of birds. PMID:23118438

Semantic extraction and processing of medical records for patient-oriented visual index

NASA Astrophysics Data System (ADS)

Zheng, Weilin; Dong, Wenjie; Chen, Xiangjiao; Zhang, Jianguo

2012-02-01

To have comprehensive and completed understanding healthcare status of a patient, doctors need to search patient medical records from different healthcare information systems, such as PACS, RIS, HIS, USIS, as a reference of diagnosis and treatment decisions for the patient. However, it is time-consuming and tedious to do these procedures. In order to solve this kind of problems, we developed a patient-oriented visual index system (VIS) to use the visual technology to show health status and to retrieve the patients' examination information stored in each system with a 3D human model. In this presentation, we present a new approach about how to extract the semantic and characteristic information from the medical record systems such as RIS/USIS to create the 3D Visual Index. This approach includes following steps: (1) Building a medical characteristic semantic knowledge base; (2) Developing natural language processing (NLP) engine to perform semantic analysis and logical judgment on text-based medical records; (3) Applying the knowledge base and NLP engine on medical records to extract medical characteristics (e.g., the positive focus information), and then mapping extracted information to related organ/parts of 3D human model to create the visual index. We performed the testing procedures on 559 samples of radiological reports which include 853 focuses, and achieved 828 focuses' information. The successful rate of focus extraction is about 97.1%.

Phonological Concept Learning.

PubMed

Moreton, Elliott; Pater, Joe; Pertsova, Katya

2017-01-01

Linguistic and non-linguistic pattern learning have been studied separately, but we argue for a comparative approach. Analogous inductive problems arise in phonological and visual pattern learning. Evidence from three experiments shows that human learners can solve them in analogous ways, and that human performance in both cases can be captured by the same models. We test GMECCS (Gradual Maximum Entropy with a Conjunctive Constraint Schema), an implementation of the Configural Cue Model (Gluck & Bower, ) in a Maximum Entropy phonotactic-learning framework (Goldwater & Johnson, ; Hayes & Wilson, ) with a single free parameter, against the alternative hypothesis that learners seek featurally simple algebraic rules ("rule-seeking"). We study the full typology of patterns introduced by Shepard, Hovland, and Jenkins () ("SHJ"), instantiated as both phonotactic patterns and visual analogs, using unsupervised training. Unlike SHJ, Experiments 1 and 2 found that both phonotactic and visual patterns that depended on fewer features could be more difficult than those that depended on more features, as predicted by GMECCS but not by rule-seeking. GMECCS also correctly predicted performance differences between stimulus subclasses within each pattern. A third experiment tried supervised training (which can facilitate rule-seeking in visual learning) to elicit simple rule-seeking phonotactic learning, but cue-based behavior persisted. We conclude that similar cue-based cognitive processes are available for phonological and visual concept learning, and hence that studying either kind of learning can lead to significant insights about the other. Copyright © 2015 Cognitive Science Society, Inc.

Visual recognition and inference using dynamic overcomplete sparse learning.

PubMed

Murray, Joseph F; Kreutz-Delgado, Kenneth

2007-09-01

We present a hierarchical architecture and learning algorithm for visual recognition and other visual inference tasks such as imagination, reconstruction of occluded images, and expectation-driven segmentation. Using properties of biological vision for guidance, we posit a stochastic generative world model and from it develop a simplified world model (SWM) based on a tractable variational approximation that is designed to enforce sparse coding. Recent developments in computational methods for learning overcomplete representations (Lewicki & Sejnowski, 2000; Teh, Welling, Osindero, & Hinton, 2003) suggest that overcompleteness can be useful for visual tasks, and we use an overcomplete dictionary learning algorithm (Kreutz-Delgado, et al., 2003) as a preprocessing stage to produce accurate, sparse codings of images. Inference is performed by constructing a dynamic multilayer network with feedforward, feedback, and lateral connections, which is trained to approximate the SWM. Learning is done with a variant of the back-propagation-through-time algorithm, which encourages convergence to desired states within a fixed number of iterations. Vision tasks require large networks, and to make learning efficient, we take advantage of the sparsity of each layer to update only a small subset of elements in a large weight matrix at each iteration. Experiments on a set of rotated objects demonstrate various types of visual inference and show that increasing the degree of overcompleteness improves recognition performance in difficult scenes with occluded objects in clutter.

Top-down modulation of ventral occipito-temporal responses during visual word recognition.

PubMed

Twomey, Tae; Kawabata Duncan, Keith J; Price, Cathy J; Devlin, Joseph T

2011-04-01

Although interactivity is considered a fundamental principle of cognitive (and computational) models of reading, it has received far less attention in neural models of reading that instead focus on serial stages of feed-forward processing from visual input to orthographic processing to accessing the corresponding phonological and semantic information. In particular, the left ventral occipito-temporal (vOT) cortex is proposed to be the first stage where visual word recognition occurs prior to accessing nonvisual information such as semantics and phonology. We used functional magnetic resonance imaging (fMRI) to investigate whether there is evidence that activation in vOT is influenced top-down by the interaction of visual and nonvisual properties of the stimuli during visual word recognition tasks. Participants performed two different types of lexical decision tasks that focused on either visual or nonvisual properties of the word or word-like stimuli. The design allowed us to investigate how vOT activation during visual word recognition was influenced by a task change to the same stimuli and by a stimulus change during the same task. We found both stimulus- and task-driven modulation of vOT activation that can only be explained by top-down processing of nonvisual aspects of the task and stimuli. Our results are consistent with the hypothesis that vOT acts as an interface linking visual form with nonvisual processing in both bottom up and top down directions. Such interactive processing at the neural level is in agreement with cognitive and computational models of reading but challenges some of the assumptions made by current neuro-anatomical models of reading. Copyright © 2011 Elsevier Inc. All rights reserved.

Stimulus information contaminates summation tests of independent neural representations of features

NASA Technical Reports Server (NTRS)

Shimozaki, Steven S.; Eckstein, Miguel P.; Abbey, Craig K.

2002-01-01

Many models of visual processing assume that visual information is analyzed into separable and independent neural codes, or features. A common psychophysical test of independent features is known as a summation study, which measures performance in a detection, discrimination, or visual search task as the number of proposed features increases. Improvement in human performance with increasing number of available features is typically attributed to the summation, or combination, of information across independent neural coding of the features. In many instances, however, increasing the number of available features also increases the stimulus information in the task, as assessed by an optimal observer that does not include the independent neural codes. In a visual search task with spatial frequency and orientation as the component features, a particular set of stimuli were chosen so that all searches had equivalent stimulus information, regardless of the number of features. In this case, human performance did not improve with increasing number of features, implying that the improvement observed with additional features may be due to stimulus information and not the combination across independent features.

A model of attention-guided visual perception and recognition.

PubMed

Rybak, I A; Gusakova, V I; Golovan, A V; Podladchikova, L N; Shevtsova, N A

1998-08-01

A model of visual perception and recognition is described. The model contains: (i) a low-level subsystem which performs both a fovea-like transformation and detection of primary features (edges), and (ii) a high-level subsystem which includes separated 'what' (sensory memory) and 'where' (motor memory) structures. Image recognition occurs during the execution of a 'behavioral recognition program' formed during the primary viewing of the image. The recognition program contains both programmed attention window movements (stored in the motor memory) and predicted image fragments (stored in the sensory memory) for each consecutive fixation. The model shows the ability to recognize complex images (e.g. faces) invariantly with respect to shift, rotation and scale.

Supervised guiding long-short term memory for image caption generation based on object classes

NASA Astrophysics Data System (ADS)

Wang, Jian; Cao, Zhiguo; Xiao, Yang; Qi, Xinyuan

2018-03-01

The present models of image caption generation have the problems of image visual semantic information attenuation and errors in guidance information. In order to solve these problems, we propose a supervised guiding Long Short Term Memory model based on object classes, named S-gLSTM for short. It uses the object detection results from R-FCN as supervisory information with high confidence, and updates the guidance word set by judging whether the last output matches the supervisory information. S-gLSTM learns how to extract the current interested information from the image visual se-mantic information based on guidance word set. The interested information is fed into the S-gLSTM at each iteration as guidance information, to guide the caption generation. To acquire the text-related visual semantic information, the S-gLSTM fine-tunes the weights of the network through the back-propagation of the guiding loss. Complementing guidance information at each iteration solves the problem of visual semantic information attenuation in the traditional LSTM model. Besides, the supervised guidance information in our model can reduce the impact of the mismatched words on the caption generation. We test our model on MSCOCO2014 dataset, and obtain better performance than the state-of-the- art models.

The internal model: A study of the relative contribution of proprioception and visual information to failure detection in dynamic systems. [sensitivity of operators versus monitors to failures

NASA Technical Reports Server (NTRS)

Kessel, C.; Wickens, C. D.

1978-01-01

The development of the internal model as it pertains to the detection of step changes in the order of control dynamics is investigated for two modes of participation: whether the subjects are actively controlling those dynamics or are monitoring an autopilot controlling them. A transfer of training design was used to evaluate the relative contribution of proprioception and visual information to the overall accuracy of the internal model. Sixteen subjects either tracked or monitored the system dynamics as a 2-dimensional pursuit display under single task conditions and concurrently with a sub-critical tracking task at two difficulty levels. Detection performance was faster and more accurate in the manual as opposed to the autopilot mode. The concurrent tracking task produced a decrement in detection performance for all conditions though this was more marked for the manual mode. The development of an internal model in the manual mode transferred positively to the automatic mode producing enhanced detection performance. There was no transfer from the internal model developed in the automatic mode to the manual mode.

Robotic Navigation Emulating Human Performance

DTIC Science & Technology

2012-03-10

information given”. The special role and significance of shape in visual perception was appreciated and highlighted by the Gestalt Psychologists...denigrate this as well as many other contributions of the Gestalt Psychologists to visual perception . The few who did try to work on it tried to formulate... theories and models of FGO without clarifying the ill-defined concepts used by Gestalt Psychologists before the Cognitive Revolution. This led to a

Graphical Technique to Support the Teaching/Learning Process of Software Process Reference Models

NASA Astrophysics Data System (ADS)

Espinosa-Curiel, Ismael Edrein; Rodríguez-Jacobo, Josefina; Fernández-Zepeda, José Alberto

In this paper, we propose a set of diagrams to visualize software process reference models (PRM). The diagrams, called dimods, are the combination of some visual and process modeling techniques such as rich pictures, mind maps, IDEF and RAD diagrams. We show the use of this technique by designing a set of dimods for the Mexican Software Industry Process Model (MoProSoft). Additionally, we perform an evaluation of the usefulness of dimods. The result of the evaluation shows that dimods may be a support tool that facilitates the understanding, memorization, and learning of software PRMs in both, software development organizations and universities. The results also show that dimods may have advantages over the traditional description methods for these types of models.

Modeling of the First Layers in the Fly's Eye

NASA Technical Reports Server (NTRS)

Moya, J. A.; Wilcox, M. J.; Donohoe, G. W.

1997-01-01

Increased autonomy of robots would yield significant advantages in the exploration of space. The shortfalls of computer vision can, however, pose significant limitations on a robot's potential. At the same time, simple insects which are largely hard-wired have effective visual systems. The understanding of insect vision systems thus may lead to improved approaches to visual tasks. A good starting point for the study of a vision system is its eye. In this paper, a model of the sensory portion of the fly's eye is presented. The effectiveness of the model is briefly addressed by a comparison of its performance to experimental data.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

Gusakova, Valentina I.; Podladchikova, Lubov N.; Shaposhnikov, Dmitry G.; Markin, Sergey N.; Golovan, Alexander V.; Lee, Seong-Whan

1999-08-01

At present, in computer vision, the approach based on modeling the biological vision mechanisms is extensively developed. However, up to now, real world image processing has no effective solution in frameworks of both biologically inspired and conventional approaches. Evidently, new algorithms and system architectures based on advanced biological motivation should be developed for solution of computational problems related to this visual task. Basic problems that should be solved for creation of effective artificial visual system to process real world imags are a search for new algorithms of low-level image processing that, in a great extent, determine system performance. In the present paper, the result of psychophysical experiments and several advanced biologically motivated algorithms for low-level processing are presented. These algorithms are based on local space-variant filter, context encoding visual information presented in the center of input window, and automatic detection of perceptually important image fragments. The core of latter algorithm are using local feature conjunctions such as noncolinear oriented segment and composite feature map formation. Developed algorithms were integrated into foveal active vision model, the MARR. It is supposed that proposed algorithms may significantly improve model performance while real world image processing during memorizing, search, and recognition.

PFIESTERIA PISCICIDA-INDUCED COGNITIVE EFFECTS: VISUAL SIGNAL DETECTION PERFORMANCE AND REVERSAL.

EPA Science Inventory

Humans exposed to Pfiesteria piscicida report cognitive impairment. In a rat model, we showed that exposure to Pfiesteria impaired learning a new task, but not performance of previously-learned behavior. In this study, we characterized the behavioral effects of Pfiesteria in rats...

Interactive projection for aerial dance using depth sensing camera

NASA Astrophysics Data System (ADS)

Dubnov, Tammuz; Seldess, Zachary; Dubnov, Shlomo

2014-02-01

This paper describes an interactive performance system for oor and Aerial Dance that controls visual and sonic aspects of the presentation via a depth sensing camera (MS Kinect). In order to detect, measure and track free movement in space, 3 degree of freedom (3-DOF) tracking in space (on the ground and in the air) is performed using IR markers. Gesture tracking and recognition is performed using a simpli ed HMM model that allows robust mapping of the actor's actions to graphics and sound. Additional visual e ects are achieved by segmentation of the actor body based on depth information, allowing projection of separate imagery on the performer and the backdrop. Artistic use of augmented reality performance relative to more traditional concepts of stage design and dramaturgy are discussed.

The Teacher, the Physician and the Person: Exploring Causal Connections between Teaching Performance and Role Model Types Using Directed Acyclic Graphs

PubMed Central

Boerebach, Benjamin C. M.; Lombarts, Kiki M. J. M. H.; Scherpbier, Albert J. J.; Arah, Onyebuchi A.

2013-01-01

Background In fledgling areas of research, evidence supporting causal assumptions is often scarce due to the small number of empirical studies conducted. In many studies it remains unclear what impact explicit and implicit causal assumptions have on the research findings; only the primary assumptions of the researchers are often presented. This is particularly true for research on the effect of faculty’s teaching performance on their role modeling. Therefore, there is a need for robust frameworks and methods for transparent formal presentation of the underlying causal assumptions used in assessing the causal effects of teaching performance on role modeling. This study explores the effects of different (plausible) causal assumptions on research outcomes. Methods This study revisits a previously published study about the influence of faculty’s teaching performance on their role modeling (as teacher-supervisor, physician and person). We drew eight directed acyclic graphs (DAGs) to visually represent different plausible causal relationships between the variables under study. These DAGs were subsequently translated into corresponding statistical models, and regression analyses were performed to estimate the associations between teaching performance and role modeling. Results The different causal models were compatible with major differences in the magnitude of the relationship between faculty’s teaching performance and their role modeling. Odds ratios for the associations between teaching performance and the three role model types ranged from 31.1 to 73.6 for the teacher-supervisor role, from 3.7 to 15.5 for the physician role, and from 2.8 to 13.8 for the person role. Conclusions Different sets of assumptions about causal relationships in role modeling research can be visually depicted using DAGs, which are then used to guide both statistical analysis and interpretation of results. Since study conclusions can be sensitive to different causal assumptions, results should be interpreted in the light of causal assumptions made in each study. PMID:23936020

Peripheral visual performance enhancement by neurofeedback training.

PubMed

Nan, Wenya; Wan, Feng; Lou, Chin Ian; Vai, Mang I; Rosa, Agostinho

2013-12-01

Peripheral visual performance is an important ability for everyone, and a positive inter-individual correlation is found between the peripheral visual performance and the alpha amplitude during the performance test. This study investigated the effect of alpha neurofeedback training on the peripheral visual performance. A neurofeedback group of 13 subjects finished 20 sessions of alpha enhancement feedback within 20 days. The peripheral visual performance was assessed by a new dynamic peripheral visual test on the first and last training day. The results revealed that the neurofeedback group showed significant enhancement of the peripheral visual performance as well as the relative alpha amplitude during the peripheral visual test. It was not the case in the non-neurofeedback control group, which performed the tests within the same time frame as the neurofeedback group but without any training sessions. These findings suggest that alpha neurofeedback training was effective in improving peripheral visual performance. To the best of our knowledge, this is the first study to show evidence for performance improvement in peripheral vision via alpha neurofeedback training.

Feed-forward segmentation of figure-ground and assignment of border-ownership.

PubMed

Supèr, Hans; Romeo, August; Keil, Matthias

2010-05-19

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment.

Feed-Forward Segmentation of Figure-Ground and Assignment of Border-Ownership

PubMed Central

Supèr, Hans; Romeo, August; Keil, Matthias

2010-01-01

Figure-ground is the segmentation of visual information into objects and their surrounding backgrounds. Two main processes herein are boundary assignment and surface segregation, which rely on the integration of global scene information. Recurrent processing either by intrinsic horizontal connections that connect surrounding neurons or by feedback projections from higher visual areas provide such information, and are considered to be the neural substrate for figure-ground segmentation. On the contrary, a role of feedforward projections in figure-ground segmentation is unknown. To have a better understanding of a role of feedforward connections in figure-ground organization, we constructed a feedforward spiking model using a biologically plausible neuron model. By means of surround inhibition our simple 3-layered model performs figure-ground segmentation and one-sided border-ownership coding. We propose that the visual system uses feed forward suppression for figure-ground segmentation and border-ownership assignment. PMID:20502718

Crack Damage Detection Method via Multiple Visual Features and Efficient Multi-Task Learning Model.

PubMed

Wang, Baoxian; Zhao, Weigang; Gao, Po; Zhang, Yufeng; Wang, Zhe

2018-06-02

This paper proposes an effective and efficient model for concrete crack detection. The presented work consists of two modules: multi-view image feature extraction and multi-task crack region detection. Specifically, multiple visual features (such as texture, edge, etc.) of image regions are calculated, which can suppress various background noises (such as illumination, pockmark, stripe, blurring, etc.). With the computed multiple visual features, a novel crack region detector is advocated using a multi-task learning framework, which involves restraining the variability for different crack region features and emphasizing the separability between crack region features and complex background ones. Furthermore, the extreme learning machine is utilized to construct this multi-task learning model, thereby leading to high computing efficiency and good generalization. Experimental results of the practical concrete images demonstrate that the developed algorithm can achieve favorable crack detection performance compared with traditional crack detectors.

The role of visual attention in predicting driving impairment in older adults.

PubMed

Hoffman, Lesa; McDowd, Joan M; Atchley, Paul; Dubinsky, Richard

2005-12-01

This study evaluated the role of visual attention (as measured by the DriverScan change detection task and the Useful Field of View Test [UFOV]) in the prediction of driving impairment in 155 adults between the ages of 63 and 87. In contrast to previous research, participants were not oversampled for visual impairment or history of automobile accidents. Although a history of automobile accidents within the past 3 years could not be predicted using any variable, driving performance in a low-fidelity simulator could be significantly predicted by performance in the change detection task and by the divided and selection attention subtests of the UFOV in structural equation models. The sensitivity and specificity of each measure in identifying at-risk drivers were also evaluated with receiver operating characteristic curves.

Serial recall of colors: Two models of memory for serial order applied to continuous visual stimuli.

PubMed

Peteranderl, Sonja; Oberauer, Klaus

2018-01-01

This study investigated the effects of serial position and temporal distinctiveness on serial recall of simple visual stimuli. Participants observed lists of five colors presented at varying, unpredictably ordered interitem intervals, and their task was to reproduce the colors in their order of presentation by selecting colors on a continuous-response scale. To control for the possibility of verbal labeling, articulatory suppression was required in one of two experimental sessions. The predictions were derived through simulation from two computational models of serial recall: SIMPLE represents the class of temporal-distinctiveness models, whereas SOB-CS represents event-based models. According to temporal-distinctiveness models, items that are temporally isolated within a list are recalled more accurately than items that are temporally crowded. In contrast, event-based models assume that the time intervals between items do not affect recall performance per se, although free time following an item can improve memory for that item because of extended time for the encoding. The experimental and the simulated data were fit to an interference measurement model to measure the tendency to confuse items with other items nearby on the list-the locality constraint-in people as well as in the models. The continuous-reproduction performance showed a pronounced primacy effect with no recency, as well as some evidence for transpositions obeying the locality constraint. Though not entirely conclusive, this evidence favors event-based models over a role for temporal distinctiveness. There was also a strong detrimental effect of articulatory suppression, suggesting that verbal codes can be used to support serial-order memory of simple visual stimuli.

Software complex for geophysical data visualization

NASA Astrophysics Data System (ADS)

Kryukov, Ilya A.; Tyugin, Dmitry Y.; Kurkin, Andrey A.; Kurkina, Oxana E.

2013-04-01

The effectiveness of current research in geophysics is largely determined by the degree of implementation of the procedure of data processing and visualization with the use of modern information technology. Realistic and informative visualization of the results of three-dimensional modeling of geophysical processes contributes significantly into the naturalness of physical modeling and detailed view of the phenomena. The main difficulty in this case is to interpret the results of the calculations: it is necessary to be able to observe the various parameters of the three-dimensional models, build sections on different planes to evaluate certain characteristics and make a rapid assessment. Programs for interpretation and visualization of simulations are spread all over the world, for example, software systems such as ParaView, Golden Software Surfer, Voxler, Flow Vision and others. However, it is not always possible to solve the problem of visualization with the help of a single software package. Preprocessing, data transfer between the packages and setting up a uniform visualization style can turn into a long and routine work. In addition to this, sometimes special display modes for specific data are required and existing products tend to have more common features and are not always fully applicable to certain special cases. Rendering of dynamic data may require scripting languages that does not relieve the user from writing code. Therefore, the task was to develop a new and original software complex for the visualization of simulation results. Let us briefly list of the primary features that are developed. Software complex is a graphical application with a convenient and simple user interface that displays the results of the simulation. Complex is also able to interactively manage the image, resize the image without loss of quality, apply a two-dimensional and three-dimensional regular grid, set the coordinate axes with data labels and perform slice of data. The feature of geophysical data is their size. Detailed maps used in the simulations are large, thus rendering in real time can be difficult task even for powerful modern computers. Therefore, the performance of the software complex is an important aspect of this work. Complex is based on the latest version of graphic API: Microsoft - DirectX 11, which reduces overhead and harness the power of modern hardware. Each geophysical calculation is the adjustment of the mathematical model for a particular case, so the architecture of the complex visualization is created with the scalability and the ability to customize visualization objects, for better visibility and comfort. In the present study, software complex 'GeoVisual' was developed. One of the main features of this research is the use of bleeding-edge techniques of computer graphics in scientific visualization. The research was supported by The Ministry of education and science of Russian Federation, project 14.B37.21.0642.

Both memory and attention systems contribute to visual search for targets cued by implicitly learned context

PubMed Central

Giesbrecht, Barry; Sy, Jocelyn L.; Guerin, Scott A.

2012-01-01

Environmental context learned without awareness can facilitate visual processing of goal-relevant information. According to one view, the benefit of implicitly learned context relies on the neural systems involved in spatial attention and hippocampus-mediated memory. While this view has received empirical support, it contradicts traditional models of hippocampal function. The purpose of the present work was to clarify the influence of spatial context on visual search performance and on brain structures involved memory and attention. Event-related functional magnetic resonance imaging revealed that activity in the hippocampus as well as in visual and parietal cortex was modulated by learned visual context even though participants’ subjective reports and performance on a post-experiment recognition task indicated no explicit knowledge of the learned context. Moreover, the magnitude of the initial selective hippocampus response predicted the magnitude of the behavioral benefit due to context observed at the end of the experiment. The results suggest that implicit contextual learning is mediated by attention and memory and that these systems interact to support search of our environment. PMID:23099047

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

PubMed

Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A

2017-10-01

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P < .001) with pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P < .001) and diffusing capacity for carbon monoxide percentage predicted (ρ = -0.40, P < .001). Asymptotic χ 2 tests showed that inclusion of DTA score significantly improved fit of both baseline and longitudinal linear mixed models in the prediction of pulmonary function (P < .001 for both). Conclusion When compared with semiquantitative visual assessment and CT histogram-based measurements, DTA score provides additional information that can be used to predict diminished function. Automatic quantification of lung fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

Timing in audiovisual speech perception: A mini review and new psychophysical data.

PubMed

Venezia, Jonathan H; Thurman, Steven M; Matchin, William; George, Sahara E; Hickok, Gregory

2016-02-01

Recent influential models of audiovisual speech perception suggest that visual speech aids perception by generating predictions about the identity of upcoming speech sounds. These models place stock in the assumption that visual speech leads auditory speech in time. However, it is unclear whether and to what extent temporally-leading visual speech information contributes to perception. Previous studies exploring audiovisual-speech timing have relied upon psychophysical procedures that require artificial manipulation of cross-modal alignment or stimulus duration. We introduce a classification procedure that tracks perceptually relevant visual speech information in time without requiring such manipulations. Participants were shown videos of a McGurk syllable (auditory /apa/ + visual /aka/ = perceptual /ata/) and asked to perform phoneme identification (/apa/ yes-no). The mouth region of the visual stimulus was overlaid with a dynamic transparency mask that obscured visual speech in some frames but not others randomly across trials. Variability in participants' responses (~35 % identification of /apa/ compared to ~5 % in the absence of the masker) served as the basis for classification analysis. The outcome was a high resolution spatiotemporal map of perceptually relevant visual features. We produced these maps for McGurk stimuli at different audiovisual temporal offsets (natural timing, 50-ms visual lead, and 100-ms visual lead). Briefly, temporally-leading (~130 ms) visual information did influence auditory perception. Moreover, several visual features influenced perception of a single speech sound, with the relative influence of each feature depending on both its temporal relation to the auditory signal and its informational content.

Timing in Audiovisual Speech Perception: A Mini Review and New Psychophysical Data

PubMed Central

Venezia, Jonathan H.; Thurman, Steven M.; Matchin, William; George, Sahara E.; Hickok, Gregory

2015-01-01

Recent influential models of audiovisual speech perception suggest that visual speech aids perception by generating predictions about the identity of upcoming speech sounds. These models place stock in the assumption that visual speech leads auditory speech in time. However, it is unclear whether and to what extent temporally-leading visual speech information contributes to perception. Previous studies exploring audiovisual-speech timing have relied upon psychophysical procedures that require artificial manipulation of cross-modal alignment or stimulus duration. We introduce a classification procedure that tracks perceptually-relevant visual speech information in time without requiring such manipulations. Participants were shown videos of a McGurk syllable (auditory /apa/ + visual /aka/ = perceptual /ata/) and asked to perform phoneme identification (/apa/ yes-no). The mouth region of the visual stimulus was overlaid with a dynamic transparency mask that obscured visual speech in some frames but not others randomly across trials. Variability in participants' responses (∼35% identification of /apa/ compared to ∼5% in the absence of the masker) served as the basis for classification analysis. The outcome was a high resolution spatiotemporal map of perceptually-relevant visual features. We produced these maps for McGurk stimuli at different audiovisual temporal offsets (natural timing, 50-ms visual lead, and 100-ms visual lead). Briefly, temporally-leading (∼130 ms) visual information did influence auditory perception. Moreover, several visual features influenced perception of a single speech sound, with the relative influence of each feature depending on both its temporal relation to the auditory signal and its informational content. PMID:26669309

Numerical simulation of human orientation perception during lunar landing

NASA Astrophysics Data System (ADS)

Clark, Torin K.; Young, Laurence R.; Stimpson, Alexander J.; Duda, Kevin R.; Oman, Charles M.

2011-09-01

In lunar landing it is necessary to select a suitable landing point and then control a stable descent to the surface. In manned landings, astronauts will play a critical role in monitoring systems and adjusting the descent trajectory through either supervisory control and landing point designations, or by direct manual control. For the astronauts to ensure vehicle performance and safety, they will have to accurately perceive vehicle orientation. A numerical model for human spatial orientation perception was simulated using input motions from lunar landing trajectories to predict the potential for misperceptions. Three representative trajectories were studied: an automated trajectory, a landing point designation trajectory, and a challenging manual control trajectory. These trajectories were studied under three cases with different cues activated in the model to study the importance of vestibular cues, visual cues, and the effect of the descent engine thruster creating dust blowback. The model predicts that spatial misperceptions are likely to occur as a result of the lunar landing motions, particularly with limited or incomplete visual cues. The powered descent acceleration profile creates a somatogravic illusion causing the astronauts to falsely perceive themselves and the vehicle as upright, even when the vehicle has a large pitch or roll angle. When visual pathways were activated within the model these illusions were mostly suppressed. Dust blowback, obscuring the visual scene out the window, was also found to create disorientation. These orientation illusions are likely to interfere with the astronauts' ability to effectively control the vehicle, potentially degrading performance and safety. Therefore suitable countermeasures, including disorientation training and advanced displays, are recommended.

Nonuniform Changes in the Distribution of Visual Attention from Visual Complexity and Action: A Driving Simulation Study.

PubMed

Park, George D; Reed, Catherine L

2015-02-01

Researchers acknowledge the interplay between action and attention, but typically consider action as a response to successful attentional selection or the correlation of performance on separate action and attention tasks. We investigated how concurrent action with spatial monitoring affects the distribution of attention across the visual field. We embedded a functional field of view (FFOV) paradigm with concurrent central object recognition and peripheral target localization tasks in a simulated driving environment. Peripheral targets varied across 20-60 deg eccentricity at 11 radial spokes. Three conditions assessed the effects of visual complexity and concurrent action on the size and shape of the FFOV: (1) with no background, (2) with driving background, and (3) with driving background and vehicle steering. The addition of visual complexity slowed task performance and reduced the FFOV size but did not change the baseline shape. In contrast, the addition of steering produced not only shrinkage of the FFOV, but also changes in the FFOV shape. Nonuniform performance decrements occurred in proximal regions used for the central task and for steering, independent of interference from context elements. Multifocal attention models should consider the role of action and account for nonhomogeneities in the distribution of attention. © 2015 SAGE Publications.

Aligning Where to See and What to Tell: Image Captioning with Region-Based Attention and Scene-Specific Contexts.

PubMed

Fu, Kun; Jin, Junqi; Cui, Runpeng; Sha, Fei; Zhang, Changshui

2017-12-01

Recent progress on automatic generation of image captions has shown that it is possible to describe the most salient information conveyed by images with accurate and meaningful sentences. In this paper, we propose an image captioning system that exploits the parallel structures between images and sentences. In our model, the process of generating the next word, given the previously generated ones, is aligned with the visual perception experience where the attention shifts among the visual regions-such transitions impose a thread of ordering in visual perception. This alignment characterizes the flow of latent meaning, which encodes what is semantically shared by both the visual scene and the text description. Our system also makes another novel modeling contribution by introducing scene-specific contexts that capture higher-level semantic information encoded in an image. The contexts adapt language models for word generation to specific scene types. We benchmark our system and contrast to published results on several popular datasets, using both automatic evaluation metrics and human evaluation. We show that either region-based attention or scene-specific contexts improves systems without those components. Furthermore, combining these two modeling ingredients attains the state-of-the-art performance.

Dynamic wake prediction and visualization with uncertainty analysis

NASA Technical Reports Server (NTRS)

Holforty, Wendy L. (Inventor); Powell, J. David (Inventor)

2005-01-01

A dynamic wake avoidance system utilizes aircraft and atmospheric parameters readily available in flight to model and predict airborne wake vortices in real time. A novel combination of algorithms allows for a relatively simple yet robust wake model to be constructed based on information extracted from a broadcast. The system predicts the location and movement of the wake based on the nominal wake model and correspondingly performs an uncertainty analysis on the wake model to determine a wake hazard zone (no fly zone), which comprises a plurality of wake planes, each moving independently from another. The system selectively adjusts dimensions of each wake plane to minimize spatial and temporal uncertainty, thereby ensuring that the actual wake is within the wake hazard zone. The predicted wake hazard zone is communicated in real time directly to a user via a realistic visual representation. In an example, the wake hazard zone is visualized on a 3-D flight deck display to enable a pilot to visualize or see a neighboring aircraft as well as its wake. The system substantially enhances the pilot's situational awareness and allows for a further safe decrease in spacing, which could alleviate airport and airspace congestion.

Visualizing dynamic geosciences phenomena using an octree-based view-dependent LOD strategy within virtual globes

NASA Astrophysics Data System (ADS)

Li, Jing; Wu, Huayi; Yang, Chaowei; Wong, David W.; Xie, Jibo

2011-09-01

Geoscientists build dynamic models to simulate various natural phenomena for a better understanding of our planet. Interactive visualizations of these geoscience models and their outputs through virtual globes on the Internet can help the public understand the dynamic phenomena related to the Earth more intuitively. However, challenges arise when the volume of four-dimensional data (4D), 3D in space plus time, is huge for rendering. Datasets loaded from geographically distributed data servers require synchronization between ingesting and rendering data. Also the visualization capability of display clients varies significantly in such an online visualization environment; some may not have high-end graphic cards. To enhance the efficiency of visualizing dynamic volumetric data in virtual globes, this paper proposes a systematic framework, in which an octree-based multiresolution data structure is implemented to organize time series 3D geospatial data to be used in virtual globe environments. This framework includes a view-dependent continuous level of detail (LOD) strategy formulated as a synchronized part of the virtual globe rendering process. Through the octree-based data retrieval process, the LOD strategy enables the rendering of the 4D simulation at a consistent and acceptable frame rate. To demonstrate the capabilities of this framework, data of a simulated dust storm event are rendered in World Wind, an open source virtual globe. The rendering performances with and without the octree-based LOD strategy are compared. The experimental results show that using the proposed data structure and processing strategy significantly enhances the visualization performance when rendering dynamic geospatial phenomena in virtual globes.

Modeling trial by trial and block feedback in perceptual learning

PubMed Central

Liu, Jiajuan; Dosher, Barbara; Lu, Zhong-Lin

2014-01-01

Feedback has been shown to play a complex role in visual perceptual learning. It is necessary for performance improvement in some conditions while not others. Different forms of feedback, such as trial-by-trial feedback or block feedback, may both facilitate learning, but with different mechanisms. False feedback can abolish learning. We account for all these results with the Augmented Hebbian Reweight Model (AHRM). Specifically, three major factors in the model advance performance improvement: the external trial-by-trial feedback when available, the self-generated output as an internal feedback when no external feedback is available, and the adaptive criterion control based on the block feedback. Through simulating a comprehensive feedback study (Herzog & Fahle 1997, Vision Research, 37 (15), 2133–2141), we show that the model predictions account for the pattern of learning in seven major feedback conditions. The AHRM can fully explain the complex empirical results on the role of feedback in visual perceptual learning. PMID:24423783

Intercepting a moving target: On-line or model-based control?

PubMed

Zhao, Huaiyong; Warren, William H

2017-05-01

When walking to intercept a moving target, people take an interception path that appears to anticipate the target's trajectory. According to the constant bearing strategy, the observer holds the bearing direction of the target constant based on current visual information, consistent with on-line control. Alternatively, the interception path might be based on an internal model of the target's motion, known as model-based control. To investigate these two accounts, participants walked to intercept a moving target in a virtual environment. We degraded the target's visibility by blurring the target to varying degrees in the midst of a trial, in order to influence its perceived speed and position. Reduced levels of visibility progressively impaired interception accuracy and precision; total occlusion impaired performance most and yielded nonadaptive heading adjustments. Thus, performance strongly depended on current visual information and deteriorated qualitatively when it was withdrawn. The results imply that locomotor interception is normally guided by current information rather than an internal model of target motion, consistent with on-line control.

A Computational Model of Afterimage Rotation in the Peripheral Drift Illusion Based on Retinal ON/OFF Responses

PubMed Central

Hayashi, Yuichiro; Ishii, Shin; Urakubo, Hidetoshi

2014-01-01

Human observers perceive illusory rotations after the disappearance of circularly repeating patches containing dark-to-light luminance. This afterimage rotation is a very powerful phenomenon, but little is known about the mechanisms underlying it. Here, we use a computational model to show that the afterimage rotation can be explained by a combination of fast light adaptation and the physiological architecture of the early visual system, consisting of ON- and OFF-type visual pathways. In this retinal ON/OFF model, the afterimage rotation appeared as a rotation of focus lines of retinal ON/OFF responses. Focus lines rotated clockwise on a light background, but counterclockwise on a dark background. These findings were consistent with the results of psychophysical experiments, which were also performed by us. Additionally, the velocity of the afterimage rotation was comparable with that observed in our psychophysical experiments. These results suggest that the early visual system (including the retina) is responsible for the generation of the afterimage rotation, and that this illusory rotation may be systematically misinterpreted by our high-level visual system. PMID:25517906

Incorporating a Wheeled Vehicle Model in a New Monocular Visual Odometry Algorithm for Dynamic Outdoor Environments

PubMed Central

Jiang, Yanhua; Xiong, Guangming; Chen, Huiyan; Lee, Dah-Jye

2014-01-01

This paper presents a monocular visual odometry algorithm that incorporates a wheeled vehicle model for ground vehicles. The main innovation of this algorithm is to use the single-track bicycle model to interpret the relationship between the yaw rate and side slip angle, which are the two most important parameters that describe the motion of a wheeled vehicle. Additionally, the pitch angle is also considered since the planar-motion hypothesis often fails due to the dynamic characteristics of wheel suspensions and tires in real-world environments. Linearization is used to calculate a closed-form solution of the motion parameters that works as a hypothesis generator in a RAndom SAmple Consensus (RANSAC) scheme to reduce the complexity in solving equations involving trigonometric. All inliers found are used to refine the winner solution through minimizing the reprojection error. Finally, the algorithm is applied to real-time on-board visual localization applications. Its performance is evaluated by comparing against the state-of-the-art monocular visual odometry methods using both synthetic data and publicly available datasets over several kilometers in dynamic outdoor environments. PMID:25256109

Correlating optical bench performance with clinical defocus curves in varifocal and trifocal intraocular lenses.

PubMed

Plaza-Puche, Ana B; Alió, Jorge L; MacRae, Scott; Zheleznyak, Len; Sala, Esperanza; Yoon, Geunyoung

2015-05-01

To investigate the correlations existing between a trifocal intraocular lens (IOL) and a varifocal IOL using the "ex vivo" optical bench through-focus image quality analysis and the clinical visual performance in real patients by study of the defocus curves. This prospective, consecutive, nonrandomized, comparative study included a total of 64 eyes of 42 patients. Three groups of eyes were differentiated according to the IOL implanted: 22 eyes implanted with the varifocal Lentis Mplus LS-313 IOL (Oculentis GmbH, Berlin, Germany); 22 eyes implanted with the trifocal FineVision IOL (Physiol, Liege, Belgium), and 20 eyes implanted with the monofocal Acrysof SA60AT IOL (Alcon Laboratories, Inc., Fort Worth, TX). Visual outcomes and defocus curve were evaluated postoperatively. Optical bench through-focus performance was quantified by computing an image quality metric and the cross-correlation coefficient between an unaberrated reference image and captured retinal images from a model eye with a 3.0-mm artificial pupil. Statistically significant differences among defocus curves of different IOLs were detected for the levels of defocus from -4.00 to -1.00 diopters (D) (P < .01). Significant correlations were found between the optical bench image quality metric results and logMAR visual acuity scale in all groups (Lentis Mplus group: r = -0.97, P < .01; FineVision group: r = -0.82, P < .01; Acrys of group: r = -0.99, P < .01). Linear predicting models were obtained. Significant correlations were found between logMAR visual acuity and image quality metric for the multifocal and monofocal IOLs analyzed. This finding enables surgeons to predict visual outcomes from the optical bench analysis. Copyright 2015, SLACK Incorporated.

Colour spaces in ecology and evolutionary biology.

PubMed

Renoult, Julien P; Kelber, Almut; Schaefer, H Martin

2017-02-01

The recognition that animals sense the world in a different way than we do has unlocked important lines of research in ecology and evolutionary biology. In practice, the subjective study of natural stimuli has been permitted by perceptual spaces, which are graphical models of how stimuli are perceived by a given animal. Because colour vision is arguably the best-known sensory modality in most animals, a diversity of colour spaces are now available to visual ecologists, ranging from generalist and basic models allowing rough but robust predictions on colour perception, to species-specific, more complex models giving accurate but context-dependent predictions. Selecting among these models is most often influenced by historical contingencies that have associated models to specific questions and organisms; however, these associations are not always optimal. The aim of this review is to provide visual ecologists with a critical perspective on how models of colour space are built, how well they perform and where their main limitations are with regard to their most frequent uses in ecology and evolutionary biology. We propose a classification of models based on their complexity, defined as whether and how they model the mechanisms of chromatic adaptation and receptor opponency, the nonlinear association between the stimulus and its perception, and whether or not models have been fitted to experimental data. Then, we review the effect of modelling these mechanisms on predictions of colour detection and discrimination, colour conspicuousness, colour diversity and diversification, and for comparing the perception of colour traits between distinct perceivers. While a few rules emerge (e.g. opponent log-linear models should be preferred when analysing very distinct colours), in general model parameters still have poorly known effects. Colour spaces have nonetheless permitted significant advances in ecology and evolutionary biology, and more progress is expected if ecologists compare results between models and perform behavioural experiments more routinely. Such an approach would further contribute to a better understanding of colour vision and its links to the behavioural ecology of animals. While visual ecology is essentially a transfer of knowledge from visual sciences to evolutionary ecology, we hope that the discipline will benefit both fields more evenly in the future. © 2015 Cambridge Philosophical Society.

Electroosmotic pump performance is affected by concentration polarizations of both electrodes and pump

PubMed Central

Suss, Matthew E.; Mani, Ali; Zangle, Thomas A.; Santiago, Juan G.

2010-01-01

Current methods of optimizing electroosmotic (EO) pump performance include reducing pore diameter and reducing ionic strength of the pumped electrolyte. However, these approaches each increase the fraction of total ionic current carried by diffuse electric double layer (EDL) counterions. When this fraction becomes significant, concentration polarization (CP) effects become important, and traditional EO pump models are no longer valid. We here report on the first simultaneous concentration field measurements, pH visualizations, flow rate, and voltage measurements on such systems. Together, these measurements elucidate key parameters affecting EO pump performance in the CP dominated regime. Concentration field visualizations show propagating CP enrichment and depletion fronts sourced by our pump substrate and traveling at order mm/min velocities through millimeter-scale channels connected serially to our pump. The observed propagation in millimeter-scale channels is not explained by current propagating CP models. Additionally, visualizations show that CP fronts are sourced by and propagate from the electrodes of our system, and then interact with the EO pump-generated CP zones. With pH visualizations, we directly detect that electrolyte properties vary sharply across the anode enrichment front interface. Our observations lead us to hypothesize possible mechanisms for the propagation of both pump- and electrode-sourced CP zones. Lastly, our experiments show the dynamics associated with the interaction of electrode and membrane CP fronts, and we describe the effect of these phenomena on EO pump flow rates and applied voltages under galvanostatic conditions. PMID:21516230

Seeing the Errors You Feel Enhances Locomotor Performance but Not Learning.

PubMed

Roemmich, Ryan T; Long, Andrew W; Bastian, Amy J

2016-10-24

In human motor learning, it is thought that the more information we have about our errors, the faster we learn. Here, we show that additional error information can lead to improved motor performance without any concomitant improvement in learning. We studied split-belt treadmill walking that drives people to learn a new gait pattern using sensory prediction errors detected by proprioceptive feedback. When we also provided visual error feedback, participants acquired the new walking pattern far more rapidly and showed accelerated restoration of the normal walking pattern during washout. However, when the visual error feedback was removed during either learning or washout, errors reappeared with performance immediately returning to the level expected based on proprioceptive learning alone. These findings support a model with two mechanisms: a dual-rate adaptation process that learns invariantly from sensory prediction error detected by proprioception and a visual-feedback-dependent process that monitors learning and corrects residual errors but shows no learning itself. We show that our voluntary correction model accurately predicted behavior in multiple situations where visual feedback was used to change acquisition of new walking patterns while the underlying learning was unaffected. The computational and behavioral framework proposed here suggests that parallel learning and error correction systems allow us to rapidly satisfy task demands without necessarily committing to learning, as the relative permanence of learning may be inappropriate or inefficient when facing environments that are liable to change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Qualitative similarities in the visual short-term memory of pigeons and people.

PubMed

Gibson, Brett; Wasserman, Edward; Luck, Steven J

2011-10-01

Visual short-term memory plays a key role in guiding behavior, and individual differences in visual short-term memory capacity are strongly predictive of higher cognitive abilities. To provide a broader evolutionary context for understanding this memory system, we directly compared the behavior of pigeons and humans on a change detection task. Although pigeons had a lower storage capacity and a higher lapse rate than humans, both species stored multiple items in short-term memory and conformed to the same basic performance model. Thus, despite their very different evolutionary histories and neural architectures, pigeons and humans have functionally similar visual short-term memory systems, suggesting that the functional properties of visual short-term memory are subject to similar selective pressures across these distant species.

Modeling the role of parallel processing in visual search.

PubMed

Cave, K R; Wolfe, J M

1990-04-01

Treisman's Feature Integration Theory and Julesz's Texton Theory explain many aspects of visual search. However, these theories require that parallel processing mechanisms not be used in many visual searches for which they would be useful, and they imply that visual processing should be much slower than it is. Most importantly, they cannot account for recent data showing that some subjects can perform some conjunction searches very efficiently. Feature Integration Theory can be modified so that it accounts for these data and helps to answer these questions. In this new theory, which we call Guided Search, the parallel stage guides the serial stage as it chooses display elements to process. A computer simulation of Guided Search produces the same general patterns as human subjects in a number of different types of visual search.

Directly Comparing Computer and Human Performance in Language Understanding and Visual Reasoning.

ERIC Educational Resources Information Center

Baker, Eva L.; And Others

Evaluation models are being developed for assessing artificial intelligence (AI) systems in terms of similar performance by groups of people. Natural language understanding and vision systems are the areas of concentration. In simplest terms, the goal is to norm a given natural language system's performance on a sample of people. The specific…

Does walking speed mediate the association between visual impairment and self-report of mobility disability? The Salisbury Eye Evaluation Study.

PubMed

Swenor, Bonnielin K; Bandeen-Roche, Karen; Muñoz, Beatriz; West, Sheila K

2014-08-01

To determine whether performance speeds mediate the association between visual impairment and self-reported mobility disability over an 8-year period. Longitudinal analysis. Salisbury, Maryland. Salisbury Eye Evaluation Study participants aged 65 and older (N=2,520). Visual impairment was defined as best-corrected visual acuity worse than 20/40 in the better-seeing eye or visual field less than 20°. Self-reported mobility disability on three tasks was assessed: walking up stairs, walking down stairs, and walking 150 feet. Performance speed on three similar tasks was measured: walking up steps (steps/s), walking down steps (steps/s), and walking 4 m (m/s). For each year of observation, the odds of reporting mobility disability was significantly greater for participants who were visually impaired (VI) than for those who were not (NVI) (odds ratio (OR) difficulty walking up steps=1.58, 95% confidence interval (CI)=1.32-1.89; OR difficulty walking down steps=1.90, 95% CI=1.59-2.28; OR difficulty walking 150 feet=2.11, 95% CI=1.77-2.51). Once performance speed on a similar mobility task was included in the models, VI participants were no longer more likely to report mobility disability than those who were NVI (OR difficulty walking up steps=0.84, 95% CI=0.65-1.11; OR difficulty walking down steps=0.96, 95% CI=0.74-1.24; OR difficulty walking 150 feet=1.22, 95% CI=0.98-1.50). Slower performance speed in VI individuals largely accounted for the difference in the odds of reporting mobility disability, suggesting that VI older adults walk slower and are therefore more likely to report mobility disability than those who are NVI. Improving mobility performance in older adults with visual impairment may minimize the perception of mobility disability. © 2014, Copyright the Authors Journal compilation © 2014, The American Geriatrics Society.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

The roofline model: A pedagogical tool for program analysis and optimization

DOE PAGES

Williams, Samuel; Patterson, David; Oliker, Leonid; ...

2008-08-01

This article consists of a collection of slides from the authors' conference presentation. The Roofline model is a visually intuitive figure for kernel analysis and optimization. We believe undergraduates will find it useful in assessing performance and scalability limitations. It is easily extended to other architectural paradigms. It is easily extendable to other metrics: performance (sort, graphics, crypto..) bandwidth (L2, PCIe, ..). Furthermore, a performance counters could be used to generate a runtime-specific roofline that would greatly aide the optimization.

Validating Visual Cues In Flight Simulator Visual Displays

NASA Astrophysics Data System (ADS)

Aronson, Moses

1987-09-01

Currently evaluation of visual simulators are performed by either pilot opinion questionnaires or comparison of aircraft terminal performance. The approach here is to compare pilot performance in the flight simulator with a visual display to his performance doing the same visual task in the aircraft as an indication that the visual cues are identical. The A-7 Night Carrier Landing task was selected. Performance measures which had high pilot performance prediction were used to compare two samples of existing pilot performance data to prove that the visual cues evoked the same performance. The performance of four pilots making 491 night landing approaches in an A-7 prototype part task trainer were compared with the performance of 3 pilots performing 27 A-7E carrier landing qualification approaches on the CV-60 aircraft carrier. The results show that the pilots' performances were similar, therefore concluding that the visual cues provided in the simulator were identical to those provided in the real world situation. Differences between the flight simulator's flight characteristics and the aircraft have less of an effect than the pilots individual performances. The measurement parameters used in the comparison can be used for validating the visual display for adequacy for training.

Model of rhythmic ball bouncing using a visually controlled neural oscillator.

PubMed

Avrin, Guillaume; Siegler, Isabelle A; Makarov, Maria; Rodriguez-Ayerbe, Pedro

2017-10-01

The present paper investigates the sensory-driven modulations of central pattern generator dynamics that can be expected to reproduce human behavior during rhythmic hybrid tasks. We propose a theoretical model of human sensorimotor behavior able to account for the observed data from the ball-bouncing task. The novel control architecture is composed of a Matsuoka neural oscillator coupled with the environment through visual sensory feedback. The architecture's ability to reproduce human-like performance during the ball-bouncing task in the presence of perturbations is quantified by comparison of simulated and recorded trials. The results suggest that human visual control of the task is achieved online. The adaptive behavior is made possible by a parametric and state control of the limit cycle emerging from the interaction of the rhythmic pattern generator, the musculoskeletal system, and the environment. NEW & NOTEWORTHY The study demonstrates that a behavioral model based on a neural oscillator controlled by visual information is able to accurately reproduce human modulations in a motor action with respect to sensory information during the rhythmic ball-bouncing task. The model attractor dynamics emerging from the interaction between the neuromusculoskeletal system and the environment met task requirements, environmental constraints, and human behavioral choices without relying on movement planning and explicit internal models of the environment. Copyright © 2017 the American Physiological Society.

Neuronal correlates of visual and auditory alertness in the DMT and ketamine model of psychosis.

PubMed

Daumann, J; Wagner, D; Heekeren, K; Neukirch, A; Thiel, C M; Gouzoulis-Mayfrank, E

2010-10-01

Deficits in attentional functions belong to the core cognitive symptoms in schizophrenic patients. Alertness is a nonselective attention component that refers to a state of general readiness that improves stimulus processing and response initiation. The main goal of the present study was to investigate cerebral correlates of alertness in the human 5HT(2A) agonist and N-methyl-D-aspartic acid (NMDA) antagonist model of psychosis. Fourteen healthy volunteers participated in a randomized double-blind, cross-over event-related functional magnetic resonance imaging (fMRI) study with dimethyltryptamine (DMT) and S-ketamine. A target detection task with cued and uncued trials in both the visual and the auditory modality was used. Administration of DMT led to decreased blood oxygenation level-dependent response during performance of an alertness task, particularly in extrastriate regions during visual alerting and in temporal regions during auditory alerting. In general, the effects for the visual modality were more pronounced. In contrast, administration of S-ketamine led to increased cortical activation in the left insula and precentral gyrus in the auditory modality. The results of the present study might deliver more insight into potential differences and overlapping pathomechanisms in schizophrenia. These conclusions must remain preliminary and should be explored by further fMRI studies with schizophrenic patients performing modality-specific alertness tasks.

Visual just noticeable differences

NASA Astrophysics Data System (ADS)

Nankivil, Derek; Chen, Minghan; Wooley, C. Benjamin

2018-02-01

A visual just noticeable difference (VJND) is the amount of change in either an image (e.g. a photographic print) or in vision (e.g. due to a change in refractive power of a vision correction device or visually coupled optical system) that is just noticeable when compared with the prior state. Numerous theoretical and clinical studies have been performed to determine the amount of change in various visual inputs (power, spherical aberration, astigmatism, etc.) that result in a just noticeable visual change. Each of these approaches, in defining a VJND, relies on the comparison of two visual stimuli. The first stimulus is the nominal or baseline state and the second is the perturbed state that results in a VJND. Using this commonality, we converted each result to the change in the area of the modulation transfer function (AMTF) to provide a more fundamental understanding of what results in a VJND. We performed an analysis of the wavefront criteria from basic optics, the image quality metrics, and clinical studies testing various visual inputs, showing that fractional changes in AMTF resulting in one VJND range from 0.025 to 0.075. In addition, cycloplegia appears to desensitize the human visual system so that a much larger change in the retinal image is required to give a VJND. This finding may be of great import for clinical vision tests. Finally, we present applications of the VJND model for the determination of threshold ocular aberrations and manufacturing tolerances of visually coupled optical systems.

Acceleration and Performance Modeling Workshop, Washington, DC, 14-17 May 79,

DTIC Science & Technology

1979-12-01

disturbance of the muscular systems, perhaps changes in spindle fiber output, and changes in the perceived weight of the muscle because of the acceleration...at this point either. The output models which are determining performance are essentially tied to muscular systems, through manual control (hand and...feet), and through speech, another muscular output. In normal activities the pilot, who senses changes in the visual system, the acceleration vector

Akuna: An Open Source User Environment for Managing Subsurface Simulation Workflows

NASA Astrophysics Data System (ADS)

Freedman, V. L.; Agarwal, D.; Bensema, K.; Finsterle, S.; Gable, C. W.; Keating, E. H.; Krishnan, H.; Lansing, C.; Moeglein, W.; Pau, G. S. H.; Porter, E.; Scheibe, T. D.

2014-12-01

The U.S. Department of Energy (DOE) is investing in development of a numerical modeling toolset called ASCEM (Advanced Simulation Capability for Environmental Management) to support modeling analyses at legacy waste sites. ASCEM is an open source and modular computing framework that incorporates new advances and tools for predicting contaminant fate and transport in natural and engineered systems. The ASCEM toolset includes both a Platform with Integrated Toolsets (called Akuna) and a High-Performance Computing multi-process simulator (called Amanzi). The focus of this presentation is on Akuna, an open-source user environment that manages subsurface simulation workflows and associated data and metadata. In this presentation, key elements of Akuna are demonstrated, which includes toolsets for model setup, database management, sensitivity analysis, parameter estimation, uncertainty quantification, and visualization of both model setup and simulation results. A key component of the workflow is in the automated job launching and monitoring capabilities, which allow a user to submit and monitor simulation runs on high-performance, parallel computers. Visualization of large outputs can also be performed without moving data back to local resources. These capabilities make high-performance computing accessible to the users who might not be familiar with batch queue systems and usage protocols on different supercomputers and clusters.

Behavioral, Modeling, and Electrophysiological Evidence for Supramodality in Human Metacognition.

PubMed

Faivre, Nathan; Filevich, Elisa; Solovey, Guillermo; Kühn, Simone; Blanke, Olaf

2018-01-10

Human metacognition, or the capacity to introspect on one's own mental states, has been mostly characterized through confidence reports in visual tasks. A pressing question is to what extent results from visual studies generalize to other domains. Answering this question allows determining whether metacognition operates through shared, supramodal mechanisms or through idiosyncratic, modality-specific mechanisms. Here, we report three new lines of evidence for decisional and postdecisional mechanisms arguing for the supramodality of metacognition. First, metacognitive efficiency correlated among auditory, tactile, visual, and audiovisual tasks. Second, confidence in an audiovisual task was best modeled using supramodal formats based on integrated representations of auditory and visual signals. Third, confidence in correct responses involved similar electrophysiological markers for visual and audiovisual tasks that are associated with motor preparation preceding the perceptual judgment. We conclude that the supramodality of metacognition relies on supramodal confidence estimates and decisional signals that are shared across sensory modalities. SIGNIFICANCE STATEMENT Metacognitive monitoring is the capacity to access, report, and regulate one's own mental states. In perception, this allows rating our confidence in what we have seen, heard, or touched. Although metacognitive monitoring can operate on different cognitive domains, we ignore whether it involves a single supramodal mechanism common to multiple cognitive domains or modality-specific mechanisms idiosyncratic to each domain. Here, we bring evidence in favor of the supramodality hypothesis by showing that participants with high metacognitive performance in one modality are likely to perform well in other modalities. Based on computational modeling and electrophysiology, we propose that supramodality can be explained by the existence of supramodal confidence estimates and by the influence of decisional cues on confidence estimates. Copyright © 2018 the authors 0270-6474/18/380263-15$15.00/0.

Fitts' Law in the Control of Isometric Grip Force With Naturalistic Targets.

PubMed

Thumser, Zachary C; Slifkin, Andrew B; Beckler, Dylan T; Marasco, Paul D

2018-01-01

Fitts' law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts' law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts' law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts' law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts' law (average r 2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts' law for explicit targets with vision ( r 2 = 0.96) and implicit targets ( r 2 = 0.89), but not as well-described for explicit targets without vision ( r 2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts' law to quantify the relative speed-accuracy relationship of any given grasper.

Sensitivity to gaze-contingent contrast increments in naturalistic movies: An exploratory report and model comparison

PubMed Central

Wallis, Thomas S. A.; Dorr, Michael; Bex, Peter J.

2015-01-01

Sensitivity to luminance contrast is a prerequisite for all but the simplest visual systems. To examine contrast increment detection performance in a way that approximates the natural environmental input of the human visual system, we presented contrast increments gaze-contingently within naturalistic video freely viewed by observers. A band-limited contrast increment was applied to a local region of the video relative to the observer's current gaze point, and the observer made a forced-choice response to the location of the target (≈25,000 trials across five observers). We present exploratory analyses showing that performance improved as a function of the magnitude of the increment and depended on the direction of eye movements relative to the target location, the timing of eye movements relative to target presentation, and the spatiotemporal image structure at the target location. Contrast discrimination performance can be modeled by assuming that the underlying contrast response is an accelerating nonlinearity (arising from a nonlinear transducer or gain control). We implemented one such model and examined the posterior over model parameters, estimated using Markov-chain Monte Carlo methods. The parameters were poorly constrained by our data; parameters constrained using strong priors taken from previous research showed poor cross-validated prediction performance. Atheoretical logistic regression models were better constrained and provided similar prediction performance to the nonlinear transducer model. Finally, we explored the properties of an extended logistic regression that incorporates both eye movement and image content features. Models of contrast transduction may be better constrained by incorporating data from both artificial and natural contrast perception settings. PMID:26057546

High-Performance Computing and Visualization | Energy Systems Integration

Science.gov Websites

Facility | NREL High-Performance Computing and Visualization High-Performance Computing and Visualization High-performance computing (HPC) and visualization at NREL propel technology innovation as a . Capabilities High-Performance Computing NREL is home to Peregrine-the largest high-performance computing system

Processing of visual semantic information to concrete words: temporal dynamics and neural mechanisms indicated by event-related brain potentials( ).

PubMed

van Schie, Hein T; Wijers, Albertus A; Mars, Rogier B; Benjamins, Jeroen S; Stowe, Laurie A

2005-05-01

Event-related brain potentials were used to study the retrieval of visual semantic information to concrete words, and to investigate possible structural overlap between visual object working memory and concreteness effects in word processing. Subjects performed an object working memory task that involved 5 s retention of simple 4-angled polygons (load 1), complex 10-angled polygons (load 2), and a no-load baseline condition. During the polygon retention interval subjects were presented with a lexical decision task to auditory presented concrete (imageable) and abstract (nonimageable) words, and pseudowords. ERP results are consistent with the use of object working memory for the visualisation of concrete words. Our data indicate a two-step processing model of visual semantics in which visual descriptive information of concrete words is first encoded in semantic memory (indicated by an anterior N400 and posterior occipital positivity), and is subsequently visualised via the network for object working memory (reflected by a left frontal positive slow wave and a bilateral occipital slow wave negativity). Results are discussed in the light of contemporary models of semantic memory.

Substantial adverse association of visual and vascular comorbidities on visual disability in multiple sclerosis.

PubMed

Marrie, Ruth Ann; Cutter, Gary; Tyry, Tuula

2011-12-01

Visual comorbidities are common in multiple sclerosis (MS) but the impact of visual comorbidities on visual disability is unknown. We assessed the impact of visual and vascular comorbidities on severity of visual disability in MS. In 2006, we queried participants of the North American Research Committee on Multiple Sclerosis (NARCOMS) about cataracts, glaucoma, uveitis, hypertension, hypercholesterolemia, heart disease, diabetes and peripheral vascular disease. We assessed visual disability using the Vision subscale of Performance Scales. Using Cox regression, we investigated whether visual or vascular comorbidities affected the time between MS symptom onset and the development of mild, moderate and severe visual disability. Of 8983 respondents, 1415 (15.9%) reported a visual comorbidity while 4745 (52.8%) reported a vascular comorbidity. The median (interquartile range) visual score was 1 (0-2). In a multivariable Cox model the risk of mild visual disability was higher among participants with vascular (hazard ratio [HR] 1.45; 95% confidence interval [CI]: 1.39-1.51) and visual comorbidities (HR 1.47; 95% CI: 1.37-1.59). Vascular and visual comorbidities were similarly associated with increased risks of moderate and severe visual disability. Visual and vascular comorbidities are associated with progression of visual disability in MS. Clinicians hearing reports of worsening visual symptoms in MS patients should consider visual comorbidities as contributing factors. Further study of these issues using objective, systematic neuro-ophthalmologic evaluations is warranted.

Common and Innovative Visuals: A sparsity modeling framework for video.

PubMed

Abdolhosseini Moghadam, Abdolreza; Kumar, Mrityunjay; Radha, Hayder

2014-05-02

Efficient video representation models are critical for many video analysis and processing tasks. In this paper, we present a framework based on the concept of finding the sparsest solution to model video frames. To model the spatio-temporal information, frames from one scene are decomposed into two components: (i) a common frame, which describes the visual information common to all the frames in the scene/segment, and (ii) a set of innovative frames, which depicts the dynamic behaviour of the scene. The proposed approach exploits and builds on recent results in the field of compressed sensing to jointly estimate the common frame and the innovative frames for each video segment. We refer to the proposed modeling framework by CIV (Common and Innovative Visuals). We show how the proposed model can be utilized to find scene change boundaries and extend CIV to videos from multiple scenes. Furthermore, the proposed model is robust to noise and can be used for various video processing applications without relying on motion estimation and detection or image segmentation. Results for object tracking, video editing (object removal, inpainting) and scene change detection are presented to demonstrate the efficiency and the performance of the proposed model.

IFIS Model-Plus: A Web-Based GUI for Visualization, Comparison and Evaluation of Distributed Flood Forecasts and Hindcasts

NASA Astrophysics Data System (ADS)

Krajewski, W. F.; Della Libera Zanchetta, A.; Mantilla, R.; Demir, I.

2017-12-01

This work explores the use of hydroinformatics tools to provide an user friendly and accessible interface for executing and assessing the output of realtime flood forecasts using distributed hydrological models. The main result is the implementation of a web system that uses an Iowa Flood Information System (IFIS)-based environment for graphical displays of rainfall-runoff simulation results for both real-time and past storm events. It communicates with ASYNCH ODE solver to perform large-scale distributed hydrological modeling based on segmentation of the terrain into hillslope-link hydrologic units. The cyber-platform also allows hindcast of model performance by testing multiple model configurations and assumptions of vertical flows in the soils. The scope of the currently implemented system is the entire set of contributing watersheds for the territory of the state of Iowa. The interface provides resources for visualization of animated maps for different water-related modeled states of the environment, including flood-waves propagation with classification of flood magnitude, runoff generation, surface soil moisture and total water column in the soil. Additional tools for comparing different model configurations and performing model evaluation by comparing to observed variables at monitored sites are also available. The user friendly interface has been published to the web under the URL http://ifis.iowafloodcenter.org/ifis/sc/modelplus/.

A visual salience map in the primate frontal eye field.

PubMed

Thompson, Kirk G; Bichot, Narcisse P

2005-01-01

Models of attention and saccade target selection propose that within the brain there is a topographic map of visual salience that combines bottom-up and top-down influences to identify locations for further processing. The results of a series of experiments with monkeys performing visual search tasks have identified a population of frontal eye field (FEF) visually responsive neurons that exhibit all of the characteristics of a visual salience map. The activity of these FEF neurons is not sensitive to specific features of visual stimuli; but instead, their activity evolves over time to select the target of the search array. This selective activation reflects both the bottom-up intrinsic conspicuousness of the stimuli and the top-down knowledge and goals of the viewer. The peak response within FEF specifies the target for the overt gaze shift. However, the selective activity in FEF is not in itself a motor command because the magnitude of activation reflects the relative behavioral significance of the different stimuli in the visual scene and occurs even when no saccade is made. Identifying a visual salience map in FEF validates the theoretical concept of a salience map in many models of attention. In addition, it strengthens the emerging view that FEF is not only involved in producing overt gaze shifts, but is also important for directing covert spatial attention.

Cell replacement and visual restoration by retinal sheet transplants

PubMed Central

Seiler, Magdalene J.; Aramant, Robert B.

2012-01-01

Retinal diseases such as age-related macular degeneration (ARMD) and retinitis pigmentosa (RP) affect millions of people. Replacing lost cells with new cells that connect with the still functional part of the host retina might repair a degenerating retina and restore eyesight to an unknown extent. A unique model, subretinal transplantation of freshly dissected sheets of fetal-derived retinal progenitor cells, combined with its retinal pigment epithelium (RPE), has demonstrated successful results in both animals and humans. Most other approaches are restricted to rescue endogenous retinal cells of the recipient in earlier disease stages by a ‘nursing’ role of the implanted cells and are not aimed at neural retinal cell replacement. Sheet transplants restore lost visual responses in several retinal degeneration models in the superior colliculus (SC) corresponding to the location of the transplant in the retina. They do not simply preserve visual performance – they increase visual responsiveness to light. Restoration of visual responses in the SC can be directly traced to neural cells in the transplant, demonstrating that synaptic connections between transplant and host contribute to the visual improvement. Transplant processes invade the inner plexiform layer of the host retina and form synapses with presumable host cells. In a Phase II trial of RP and ARMD patients, transplants of retina together with its RPE improved visual acuity. In summary, retinal progenitor sheet transplantation provides an excellent model to answer questions about how to repair and restore function of a degenerating retina. Supply of fetal donor tissue will always be limited but the model can set a standard and provide an informative base for optimal cell replacement therapies such as embryonic stem cell (ESC)-derived therapy. PMID:22771454

Verbal and Visual Memory Impairments in Bipolar I and II Disorder.

PubMed

Ha, Tae Hyon; Kim, Ji Sun; Chang, Jae Seung; Oh, Sung Hee; Her, Ju Young; Cho, Hyun Sang; Park, Tae Sung; Shin, Soon Young; Ha, Kyooseob

2012-12-01

To compare verbal and visual memory performances between patients with bipolar I disorder (BD I) and patients with bipolar II disorder (BD II) and to determine whether memory deficits were mediated by impaired organizational strategies. Performances on the Korean-California Verbal Learning Test (K-CVLT) and the Rey-Osterrieth Complex Figure Test (ROCF) in 37 patients with BD I, 46 patients with BD II and 42 healthy subjects were compared. Mediating effects of impaired organization strategies on poor delayed recall was tested by comparing direct and mediated models using multiple regression analysis. Both patients groups recalled fewer words and figure components and showed lower Semantic Clustering compared to controls. Verbal memory impairment was partly mediated by difficulties in Semantic Clustering in both subtypes, whereas the mediating effect of Organization deficit on the visual memory impairment was present only in BD I. In all mediated models, group differences in delayed recall remained significant. Our findings suggest that memory impairment may be one of the fundamental cognitive deficits in bipolar disorders and that executive dysfunctions can exert an additional influence on memory impairments.

Test-retest reliability of eye tracking in the visual world paradigm for the study of real-time spoken word recognition.

PubMed

Farris-Trimble, Ashley; McMurray, Bob

2013-08-01

Researchers have begun to use eye tracking in the visual world paradigm (VWP) to study clinical differences in language processing, but the reliability of such laboratory tests has rarely been assessed. In this article, the authors assess test-retest reliability of the VWP for spoken word recognition. Methods Participants performed an auditory VWP task in repeated sessions and a visual-only VWP task in a third session. The authors performed correlation and regression analyses on several parameters to determine which reflect reliable behavior and which are predictive of behavior in later sessions. Results showed that the fixation parameters most closely related to timing and degree of fixations were moderately-to-strongly correlated across days, whereas the parameters related to rate of increase or decrease of fixations to particular items were less strongly correlated. Moreover, when including factors derived from the visual-only task, the performance of the regression model was at least moderately correlated with Day 2 performance on all parameters ( R > .30). The VWP is stable enough (with some caveats) to serve as an individual measure. These findings suggest guidelines for future use of the paradigm and for areas of improvement in both methodology and analysis.

Raised visual detection thresholds depend on the level of complexity of cognitive foveal loading.

PubMed

Plainis, S; Murray, I J; Chauhan, K

2001-01-01

The objective of the study was to measure the interactions between visual thresholds for a simple light (the secondary task) presented peripherally and a simultaneously performed cognitive task (the primary task) presented foveally The primary task was highly visible but varied according to its cognitive complexity. Interactions between the tasks were determined by measuring detection thresholds for the peripheral task and accuracy of performance of the foveal task. Effects were measured for 5, 10, 20, and 30 deg eccentricity of the peripherally presented light and for three levels of cognitive complexity. Mesopic conditions (0.5 lx) were used. As expected, the concurrent presentation of the foveal cognitive task reduced peripheral sensitivity. Moreover, performance of the foveal task was adversely affected when conducting the peripheral task. Performance on both tasks was reduced as the level of complexity of the cognitive task increased. There were qualitative differences in task interactions between the central 10 deg and at greater eccentricities. Within 10 deg there was a disproportionate effect of eccentricity, previously interpreted as the 'tunnel-vision' model of visual field narrowing. Interactions outside 10 deg were less affected by eccentricity. These results are discussed in terms of the known neurophysiological characteristics of the primary visual pathway.

Helicopter simulation validation using flight data

NASA Technical Reports Server (NTRS)

Key, D. L.; Hansen, R. S.; Cleveland, W. B.; Abbott, W. Y.

1982-01-01

A joint NASA/Army effort to perform a systematic ground-based piloted simulation validation assessment is described. The best available mathematical model for the subject helicopter (UH-60A Black Hawk) was programmed for real-time operation. Flight data were obtained to validate the math model, and to develop models for the pilot control strategy while performing mission-type tasks. The validated math model is to be combined with motion and visual systems to perform ground based simulation. Comparisons of the control strategy obtained in flight with that obtained on the simulator are to be used as the basis for assessing the fidelity of the results obtained in the simulator.

Big Data Processing for a Central Texas Groundwater Case Study

NASA Astrophysics Data System (ADS)

Cantu, A.; Rivera, O.; Martínez, A.; Lewis, D. H.; Gentle, J. N., Jr.; Fuentes, G.; Pierce, S. A.

2016-12-01

As computational methods improve, scientists are able to expand the level and scale of experimental simulation and testing that is completed for case studies. This study presents a comparative analysis of multiple models for the Barton Springs segment of the Edwards aquifer. Several numerical simulations using state-mandated MODFLOW models ran on Stampede, a High Performance Computing system housed at the Texas Advanced Computing Center, were performed for multiple scenario testing. One goal of this multidisciplinary project aims to visualize and compare the output data of the groundwater model using the statistical programming language R to find revealing data patterns produced by different pumping scenarios. Presenting data in a friendly post-processing format is covered in this paper. Visualization of the data and creating workflows applicable to the management of the data are tasks performed after data extraction. Resulting analyses provide an example of how supercomputing can be used to accelerate evaluation of scientific uncertainty and geological knowledge in relation to policy and management decisions. Understanding the aquifer behavior helps policy makers avoid negative impact on the endangered species, environmental services and aids in maximizing the aquifer yield.

Adaptive Correlation Model for Visual Tracking Using Keypoints Matching and Deep Convolutional Feature.

PubMed

Li, Yuankun; Xu, Tingfa; Deng, Honggao; Shi, Guokai; Guo, Jie

2018-02-23

Although correlation filter (CF)-based visual tracking algorithms have achieved appealing results, there are still some problems to be solved. When the target object goes through long-term occlusions or scale variation, the correlation model used in existing CF-based algorithms will inevitably learn some non-target information or partial-target information. In order to avoid model contamination and enhance the adaptability of model updating, we introduce the keypoints matching strategy and adjust the model learning rate dynamically according to the matching score. Moreover, the proposed approach extracts convolutional features from a deep convolutional neural network (DCNN) to accurately estimate the position and scale of the target. Experimental results demonstrate that the proposed tracker has achieved satisfactory performance in a wide range of challenging tracking scenarios.

Performance drifts in two-finger cyclical force production tasks performed by one and two actors.

PubMed

Hasanbarani, Fariba; Reschechtko, Sasha; Latash, Mark L

2018-03-01

We explored changes in the cyclical two-finger force performance task caused by turning visual feedback off performed either by the index and middle fingers of the dominant hand or by two index fingers of two persons. Based on an earlier study, we expected drifts in finger force amplitude and midpoint without a drift in relative phase. The subjects performed two rhythmical tasks at 1 Hz while paced by an auditory metronome. One of the tasks required cyclical changes in total force magnitude without changes in the sharing of the force between the two fingers. The other task required cyclical changes in the force sharing without changing total force magnitude. Subjects were provided with visual feedback, which showed total force magnitude and force sharing via cursor motion along the vertical and horizontal axes, respectively. Further, visual feedback was turned off, first on the variable that was not required to change and then on both variables. Turning visual feedback off led to a mean force drift toward lower magnitudes while force amplitude increased. There was a consistent drift in the relative phase in the one-hand task with the index finger leading the middle finger. No consistent relative phase drift was seen in the two-person tasks. The shape of the force cycle changed without visual feedback reflected in the lower similarity to a perfect cosine shape and in the higher time spent at lower force magnitudes. The data confirm findings of earlier studies regarding force amplitude and midpoint changes, but falsify predictions of an earlier proposed model with respect to the relative phase changes. We discuss factors that could contribute to the observed relative phase drift in the one-hand tasks including the leader-follower pattern generalized for two-effector tasks performed by one person.

Visual Saliency Detection Based on Multiscale Deep CNN Features.

PubMed

Guanbin Li; Yizhou Yu

2016-11-01

Visual saliency is a fundamental problem in both cognitive and computational sciences, including computer vision. In this paper, we discover that a high-quality visual saliency model can be learned from multiscale features extracted using deep convolutional neural networks (CNNs), which have had many successes in visual recognition tasks. For learning such saliency models, we introduce a neural network architecture, which has fully connected layers on top of CNNs responsible for feature extraction at three different scales. The penultimate layer of our neural network has been confirmed to be a discriminative high-level feature vector for saliency detection, which we call deep contrast feature. To generate a more robust feature, we integrate handcrafted low-level features with our deep contrast feature. To promote further research and evaluation of visual saliency models, we also construct a new large database of 4447 challenging images and their pixelwise saliency annotations. Experimental results demonstrate that our proposed method is capable of achieving the state-of-the-art performance on all public benchmarks, improving the F-measure by 6.12% and 10%, respectively, on the DUT-OMRON data set and our new data set (HKU-IS), and lowering the mean absolute error by 9% and 35.3%, respectively, on these two data sets.

Helping students revise disruptive experientially supported ideas about thermodynamics: Computer visualizations and tactile models

NASA Astrophysics Data System (ADS)

Clark, Douglas; Jorde, Doris

2004-01-01

This study analyzes the impact of an integrated sensory model within a thermal equilibrium visualization. We hypothesized that this intervention would not only help students revise their disruptive experientially supported ideas about why objects feel hot or cold, but also increase their understanding of thermal equilibrium. The analysis synthesizes test data and interviews to measure the impact of this strategy. Results show that students in the experimental tactile group significantly outperform their control group counterparts on posttests and delayed posttests, not only on tactile explanations, but also on thermal equilibrium explanations. Interview transcripts of experimental and control group students corroborate these findings. Discussion addresses improving the tactile model as well as application of the strategy to other science topics. The discussion also considers possible incorporation of actual kinetic or thermal haptic feedback to reinforce the current audio and visual feedback of the visualization. This research builds on the conceptual change literature about the nature and role of students' experientially supported ideas as well as our understanding of curriculum and visualization design to support students in learning about thermodynamics, a science topic on which students perform poorly as shown by the National Assessment of Educational Progress (NAEP) and Third International Mathematics and Science Study (TIMSS) studies.

Visual field differences in visual word recognition can emerge purely from perceptual learning: evidence from modeling Chinese character pronunciation.

PubMed

Hsiao, Janet Hui-Wen

2011-11-01

In Chinese orthography, a dominant character structure exists in which a semantic radical appears on the left and a phonetic radical on the right (SP characters); a minority opposite arrangement also exists (PS characters). As the number of phonetic radical types is much greater than semantic radical types, in SP characters the information is skewed to the right, whereas in PS characters it is skewed to the left. Through training a computational model for SP and PS character recognition that takes into account of the locations in which the characters appear in the visual field during learning, but does not assume any fundamental hemispheric processing difference, we show that visual field differences can emerge as a consequence of the fundamental structural differences in information between SP and PS characters, as opposed to the fundamental processing differences between the two hemispheres. This modeling result is also consistent with behavioral naming performance. This work provides strong evidence that perceptual learning, i.e., the information structure of word stimuli to which the readers have long been exposed, is one of the factors that accounts for hemispheric asymmetry effects in visual word recognition. Copyright © 2011 Elsevier Inc. All rights reserved.

Virtual skeletal complex model- and landmark-guided orthognathic surgery system.

PubMed

Lee, Sang-Jeong; Woo, Sang-Yoon; Huh, Kyung-Hoe; Lee, Sam-Sun; Heo, Min-Suk; Choi, Soon-Chul; Han, Jeong Joon; Yang, Hoon Joo; Hwang, Soon Jung; Yi, Won-Jin

2016-05-01

In this study, correction of the maxillofacial deformities was performed by repositioning bone segments to an appropriate location according to the preoperative planning in orthognathic surgery. The surgery was planned using the patient's virtual skeletal models fused with optically scanned three-dimensional dentition. The virtual maxillomandibular complex (MMC) model of the patient's final occlusal relationship was generated by fusion of the maxillary and mandibular models with scanned occlusion. The final position of the MMC was simulated preoperatively by planning and was used as a goal model for guidance. During surgery, the intraoperative registration was finished immediately using only software processing. For accurate repositioning, the intraoperative MMC model was visualized on the monitor with respect to the simulated MMC model, and the intraoperative positions of multiple landmarks were also visualized on the MMC surface model. The deviation errors between the intraoperative and the final positions of each landmark were visualized quantitatively. As a result, the surgeon could easily recognize the three-dimensional deviation of the intraoperative MMC state from the final goal model without manually applying a pointing tool, and could also quickly determine the amount and direction of further MMC movements needed to reach the goal position. The surgeon could also perform various osteotomies and remove bone interference conveniently, as the maxillary tracking tool could be separated from the MMC. The root mean square (RMS) difference between the preoperative planning and the intraoperative guidance was 1.16 ± 0.34 mm immediately after repositioning. After surgery, the RMS differences between the planning and the postoperative computed tomographic model were 1.31 ± 0.28 mm and 1.74 ± 0.73 mm for the maxillary and mandibular landmarks, respectively. Our method provides accurate and flexible guidance for bimaxillary orthognathic surgery based on intraoperative visualization and quantification of deviations for simulated postoperative MMC and landmarks. The guidance using simulated skeletal models and landmarks can complement and improve conventional navigational surgery for bone repositioning in the craniomaxillofacial area. Copyright © 2016 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Focal activation of primary visual cortex following supra-choroidal electrical stimulation of the retina: Intrinsic signal imaging and linear model analysis.

PubMed

Cloherty, Shaun L; Hietanen, Markus A; Suaning, Gregg J; Ibbotson, Michael R

2010-01-01

We performed optical intrinsic signal imaging of cat primary visual cortex (Area 17 and 18) while delivering bipolar electrical stimulation to the retina by way of a supra-choroidal electrode array. Using a general linear model (GLM) analysis we identified statistically significant (p < 0.01) activation in a localized region of cortex following supra-threshold electrical stimulation at a single retinal locus. (1) demonstrate that intrinsic signal imaging combined with linear model analysis provides a powerful tool for assessing cortical responses to prosthetic stimulation, and (2) confirm that supra-choroidal electrical stimulation can achieve localized activation of the cortex consistent with focal activation of the retina.

Decoding natural images from evoked brain activities using encoding models with invertible mapping.

PubMed

Li, Chao; Xu, Junhai; Liu, Baolin

2018-05-21

Recent studies have built encoding models in the early visual cortex, and reliable mappings have been made between the low-level visual features of stimuli and brain activities. However, these mappings are irreversible, so that the features cannot be directly decoded. To solve this problem, we designed a sparse framework-based encoding model that predicted brain activities from a complete feature representation. Moreover, according to the distribution and activation rules of neurons in the primary visual cortex (V1), three key transformations were introduced into the basic feature to improve the model performance. In this setting, the mapping was simple enough that it could be inverted using a closed-form formula. Using this mapping, we designed a hybrid identification method based on the support vector machine (SVM), and tested it on a published functional magnetic resonance imaging (fMRI) dataset. The experiments confirmed the rationality of our encoding model, and the identification accuracies for 2 subjects increased from 92% and 72% to 98% and 92% with the chance level only 0.8%. Copyright © 2018 Elsevier Ltd. All rights reserved.

Evidence for a Global Sampling Process in Extraction of Summary Statistics of Item Sizes in a Set.

PubMed

Tokita, Midori; Ueda, Sachiyo; Ishiguchi, Akira

2016-01-01

Several studies have shown that our visual system may construct a "summary statistical representation" over groups of visual objects. Although there is a general understanding that human observers can accurately represent sets of a variety of features, many questions on how summary statistics, such as an average, are computed remain unanswered. This study investigated sampling properties of visual information used by human observers to extract two types of summary statistics of item sets, average and variance. We presented three models of ideal observers to extract the summary statistics: a global sampling model without sampling noise, global sampling model with sampling noise, and limited sampling model. We compared the performance of an ideal observer of each model with that of human observers using statistical efficiency analysis. Results suggest that summary statistics of items in a set may be computed without representing individual items, which makes it possible to discard the limited sampling account. Moreover, the extraction of summary statistics may not necessarily require the representation of individual objects with focused attention when the sets of items are larger than 4.

Bioplausible multiscale filtering in retino-cortical processing as a mechanism in perceptual grouping.

PubMed

Nematzadeh, Nasim; Powers, David M W; Lewis, Trent W

2017-12-01

Why does our visual system fail to reconstruct reality, when we look at certain patterns? Where do Geometrical illusions start to emerge in the visual pathway? How far should we take computational models of vision with the same visual ability to detect illusions as we do? This study addresses these questions, by focusing on a specific underlying neural mechanism involved in our visual experiences that affects our final perception. Among many types of visual illusion, 'Geometrical' and, in particular, 'Tilt Illusions' are rather important, being characterized by misperception of geometric patterns involving lines and tiles in combination with contrasting orientation, size or position. Over the last decade, many new neurophysiological experiments have led to new insights as to how, when and where retinal processing takes place, and the encoding nature of the retinal representation that is sent to the cortex for further processing. Based on these neurobiological discoveries, we provide computer simulation evidence from modelling retinal ganglion cells responses to some complex Tilt Illusions, suggesting that the emergence of tilt in these illusions is partially related to the interaction of multiscale visual processing performed in the retina. The output of our low-level filtering model is presented for several types of Tilt Illusion, predicting that the final tilt percept arises from multiple-scale processing of the Differences of Gaussians and the perceptual interaction of foreground and background elements. The model is a variation of classical receptive field implementation for simple cells in early stages of vision with the scales tuned to the object/texture sizes in the pattern. Our results suggest that this model has a high potential in revealing the underlying mechanism connecting low-level filtering approaches to mid- and high-level explanations such as 'Anchoring theory' and 'Perceptual grouping'.

The prevalence of visual hallucinations in non-affective psychosis, and the role of perception and attention.

PubMed

van Ommen, M M; van Beilen, M; Cornelissen, F W; Smid, H G O M; Knegtering, H; Aleman, A; van Laar, T

2016-06-01

Little is known about visual hallucinations (VH) in psychosis. We investigated the prevalence and the role of bottom-up and top-down processing in VH. The prevailing view is that VH are probably related to altered top-down processing, rather than to distorted bottom-up processing. Conversely, VH in Parkinson's disease are associated with impaired visual perception and attention, as proposed by the Perception and Attention Deficit (PAD) model. Auditory hallucinations (AH) in psychosis, however, are thought to be related to increased attention. Our retrospective database study included 1119 patients with non-affective psychosis and 586 controls. The Community Assessment of Psychic Experiences established the VH rate. Scores on visual perception tests [Degraded Facial Affect Recognition (DFAR), Benton Facial Recognition Task] and attention tests [Response Set-shifting Task, Continuous Performance Test-HQ (CPT-HQ)] were compared between 75 VH patients, 706 non-VH patients and 485 non-VH controls. The lifetime VH rate was 37%. The patient groups performed similarly on cognitive tasks; both groups showed worse perception (DFAR) than controls. Non-VH patients showed worse attention (CPT-HQ) than controls, whereas VH patients did not perform differently. We did not find significant VH-related impairments in bottom-up processing or direct top-down alterations. However, the results suggest a relatively spared attentional performance in VH patients, whereas face perception and processing speed were equally impaired in both patient groups relative to controls. This would match better with the increased attention hypothesis than with the PAD model. Our finding that VH frequently co-occur with AH may support an increased attention-induced 'hallucination proneness'.

Development of internal models and predictive abilities for visual tracking during childhood

PubMed Central

Ego, Caroline; Yüksel, Demet

2015-01-01

The prediction of the consequences of our own actions through internal models is an essential component of motor control. Previous studies showed improvement of anticipatory behaviors with age for grasping, drawing, and postural control. Since these actions require visual and proprioceptive feedback, these improvements might reflect both the development of internal models and the feedback control. In contrast, visual tracking of a temporarily invisible target gives specific markers of prediction and internal models for eye movements. Therefore, we recorded eye movements in 50 children (aged 5–19 yr) and in 10 adults, who were asked to pursue a visual target that is temporarily blanked. Results show that the youngest children (5–7 yr) have a general oculomotor behavior in this task, qualitatively similar to the one observed in adults. However, the overall performance of older subjects in terms of accuracy at target reappearance and variability in their behavior was much better than the youngest children. This late maturation of predictive mechanisms with age was reflected into the development of the accuracy of the internal models governing the synergy between the saccadic and pursuit systems with age. Altogether, we hypothesize that the maturation of the interaction between smooth pursuit and saccades that relies on internal models of the eye and target displacement is related to the continuous maturation of the cerebellum. PMID:26510757

Development of internal models and predictive abilities for visual tracking during childhood.

PubMed

Ego, Caroline; Yüksel, Demet; Orban de Xivry, Jean-Jacques; Lefèvre, Philippe

2016-01-01

The prediction of the consequences of our own actions through internal models is an essential component of motor control. Previous studies showed improvement of anticipatory behaviors with age for grasping, drawing, and postural control. Since these actions require visual and proprioceptive feedback, these improvements might reflect both the development of internal models and the feedback control. In contrast, visual tracking of a temporarily invisible target gives specific markers of prediction and internal models for eye movements. Therefore, we recorded eye movements in 50 children (aged 5-19 yr) and in 10 adults, who were asked to pursue a visual target that is temporarily blanked. Results show that the youngest children (5-7 yr) have a general oculomotor behavior in this task, qualitatively similar to the one observed in adults. However, the overall performance of older subjects in terms of accuracy at target reappearance and variability in their behavior was much better than the youngest children. This late maturation of predictive mechanisms with age was reflected into the development of the accuracy of the internal models governing the synergy between the saccadic and pursuit systems with age. Altogether, we hypothesize that the maturation of the interaction between smooth pursuit and saccades that relies on internal models of the eye and target displacement is related to the continuous maturation of the cerebellum. Copyright © 2016 the American Physiological Society.

Vision loss among diabetics in a group model Health Maintenance Organization (HMO).

PubMed

Fong, Donald S; Sharza, Mohktar; Chen, Wansu; Paschal, John F; Ariyasu, Reginald G; Lee, Paul P

2002-02-01

To report the management of diabetic retinopathy in one group model health maintenance organization and assess the quality of care. Cross-sectional study. A chart review of 1200 randomly identified patients with diabetes mellitus, continuously enrolled for 3 years in Kaiser Permanente (KP) Southern California, the largest provider of managed care in Southern California, was performed. A total of 1047 patients were included in the analyses. Patient characteristics as well as information from the last eye examination were abstracted. Charts from patients with visual acuity less than 20/200 in their better eye (legal blindness) were selected for extensive chart review to determine the cause of visual loss and the antecedent process of care. T tests or the Wilcoxon rank sum test was used to compare continuous variables. The chi(2) test or the Fisher exact test was used to compare categorical variables. All analyses were performed on the Statistical Analyses System (SAS Institute, North Carolina). Our study population of 1047 diabetic patients was 51.7% male, had a mean age of 60.4 years, a mean duration of diabetes of 9.6 years, and a mean hemoglobin A1c of 8.3%. During the study period, 77.5% of patients received a screening eye examination with examination by an ophthalmologist, an optometrist, or review of a retinal photograph. Of those with a visual acuity assessment (n = 687, 65.6% of 1047), 1.5% had visual acuity of 20/200 or worse (legally blind) in the better eye, while 8.2% had this level of visual acuity in the worse eye. Of eyes with new onset clinically significant macular edema and visual acuity < 20/40, 40% had documentation of focal laser performed within 1 month of diagnosis. Of eyes with vitreous hemorrhage and visual acuity < 20/40, 50% had documentation of vitrectomy. Among eyes that had vitrectomy, over 80% had this procedure within 1 year of diagnosis of vitreous hemorrhage. The current report is the largest study of diabetic retinopathy outcomes among patients enrolled in a prepaid health plan. Further research is necessary to investigate the impact of managed care on health outcomes.

A Novel Active Imaging Model to Design Visual Systems: A Case of Inspection System for Specular Surfaces

PubMed Central

Azorin-Lopez, Jorge; Fuster-Guillo, Andres; Saval-Calvo, Marcelo; Mora-Mora, Higinio; Garcia-Chamizo, Juan Manuel

2017-01-01

The use of visual information is a very well known input from different kinds of sensors. However, most of the perception problems are individually modeled and tackled. It is necessary to provide a general imaging model that allows us to parametrize different input systems as well as their problems and possible solutions. In this paper, we present an active vision model considering the imaging system as a whole (including camera, lighting system, object to be perceived) in order to propose solutions to automated visual systems that present problems that we perceive. As a concrete case study, we instantiate the model in a real application and still challenging problem: automated visual inspection. It is one of the most used quality control systems to detect defects on manufactured objects. However, it presents problems for specular products. We model these perception problems taking into account environmental conditions and camera parameters that allow a system to properly perceive the specific object characteristics to determine defects on surfaces. The validation of the model has been carried out using simulations providing an efficient way to perform a large set of tests (different environment conditions and camera parameters) as a previous step of experimentation in real manufacturing environments, which more complex in terms of instrumentation and more expensive. Results prove the success of the model application adjusting scale, viewpoint and lighting conditions to detect structural and color defects on specular surfaces. PMID:28640211

Modeling the impact of common noise inputs on the network activity of retinal ganglion cells

PubMed Central

Ahmadian, Yashar; Shlens, Jonathon; Pillow, Jonathan W.; Kulkarni, Jayant; Litke, Alan M.; Chichilnisky, E. J.; Simoncelli, Eero; Paninski, Liam

2013-01-01

Synchronized spontaneous firing among retinal ganglion cells (RGCs), on timescales faster than visual responses, has been reported in many studies. Two candidate mechanisms of synchronized firing include direct coupling and shared noisy inputs. In neighboring parasol cells of primate retina, which exhibit rapid synchronized firing that has been studied extensively, recent experimental work indicates that direct electrical or synaptic coupling is weak, but shared synaptic input in the absence of modulated stimuli is strong. However, previous modeling efforts have not accounted for this aspect of firing in the parasol cell population. Here we develop a new model that incorporates the effects of common noise, and apply it to analyze the light responses and synchronized firing of a large, densely-sampled network of over 250 simultaneously recorded parasol cells. We use a generalized linear model in which the spike rate in each cell is determined by the linear combination of the spatio-temporally filtered visual input, the temporally filtered prior spikes of that cell, and unobserved sources representing common noise. The model accurately captures the statistical structure of the spike trains and the encoding of the visual stimulus, without the direct coupling assumption present in previous modeling work. Finally, we examined the problem of decoding the visual stimulus from the spike train given the estimated parameters. The common-noise model produces Bayesian decoding performance as accurate as that of a model with direct coupling, but with significantly more robustness to spike timing perturbations. PMID:22203465

Prestimulus neural oscillations inhibit visual perception via modulation of response gain.

PubMed

Chaumon, Maximilien; Busch, Niko A

2014-11-01

The ongoing state of the brain radically affects how it processes sensory information. How does this ongoing brain activity interact with the processing of external stimuli? Spontaneous oscillations in the alpha range are thought to inhibit sensory processing, but little is known about the psychophysical mechanisms of this inhibition. We recorded ongoing brain activity with EEG while human observers performed a visual detection task with stimuli of different contrast intensities. To move beyond qualitative description, we formally compared psychometric functions obtained under different levels of ongoing alpha power and evaluated the inhibitory effect of ongoing alpha oscillations in terms of contrast or response gain models. This procedure opens the way to understanding the actual functional mechanisms by which ongoing brain activity affects visual performance. We found that strong prestimulus occipital alpha oscillations-but not more anterior mu oscillations-reduce performance most strongly for stimuli of the highest intensities tested. This inhibitory effect is best explained by a divisive reduction of response gain. Ongoing occipital alpha oscillations thus reflect changes in the visual system's input/output transformation that are independent of the sensory input to the system. They selectively scale the system's response, rather than change its sensitivity to sensory information.

A novel medical image data-based multi-physics simulation platform for computational life sciences.

PubMed

Neufeld, Esra; Szczerba, Dominik; Chavannes, Nicolas; Kuster, Niels

2013-04-06

Simulating and modelling complex biological systems in computational life sciences requires specialized software tools that can perform medical image data-based modelling, jointly visualize the data and computational results, and handle large, complex, realistic and often noisy anatomical models. The required novel solvers must provide the power to model the physics, biology and physiology of living tissue within the full complexity of the human anatomy (e.g. neuronal activity, perfusion and ultrasound propagation). A multi-physics simulation platform satisfying these requirements has been developed for applications including device development and optimization, safety assessment, basic research, and treatment planning. This simulation platform consists of detailed, parametrized anatomical models, a segmentation and meshing tool, a wide range of solvers and optimizers, a framework for the rapid development of specialized and parallelized finite element method solvers, a visualization toolkit-based visualization engine, a Python scripting interface for customized applications, a coupling framework, and more. Core components are cross-platform compatible and use open formats. Several examples of applications are presented: hyperthermia cancer treatment planning, tumour growth modelling, evaluating the magneto-haemodynamic effect as a biomarker and physics-based morphing of anatomical models.

PSF and MTF comparison of two different surface ablation techniques for laser visual correction

NASA Astrophysics Data System (ADS)

Cruz Félix, Angel Sinue; López Olazagasti, Estela; Rosales, Marco A.; Ibarra, Jorge; Tepichín Rodríguez, Eduardo

2009-08-01

It is well known that the Zernike expansion of the wavefront aberrations has been extensively used to evaluate the performance of image forming optical systems. Recently, these techniques were adopted in the field of Ophthalmology to evaluate the objective performance of the human ocular system. We have been working in the characterization and evaluation of the performance of normal human eyes; i.e., eyes which do not require any refractive correction (20/20 visual acuity). These data provide us a reference model to analyze Pre- and Post-Operated results from eyes that have been subjected to laser refractive surgery. Two different ablation techniques are analyzed in this work. These techniques were designed to correct the typical refractive errors known as myopia, hyperopia, and presbyopia. When applied to the corneal surface, these techniques provide a focal shift and, in principle, an improvement of the visual performance. These features can be suitably described in terms of the PSF and MTF of the corresponding Pre- and Post-Operated wavefront aberrations. We show the preliminary results of our comparison.

Reward modulates the effect of visual cortical microstimulation on perceptual decisions

PubMed Central

Cicmil, Nela; Cumming, Bruce G; Parker, Andrew J; Krug, Kristine

2015-01-01

Effective perceptual decisions rely upon combining sensory information with knowledge of the rewards available for different choices. However, it is not known where reward signals interact with the multiple stages of the perceptual decision-making pathway and by what mechanisms this may occur. We combined electrical microstimulation of functionally specific groups of neurons in visual area V5/MT with performance-contingent reward manipulation, while monkeys performed a visual discrimination task. Microstimulation was less effective in shifting perceptual choices towards the stimulus preferences of the stimulated neurons when available reward was larger. Psychophysical control experiments showed this result was not explained by a selective change in response strategy on microstimulated trials. A bounded accumulation decision model, applied to analyse behavioural performance, revealed that the interaction of expected reward with microstimulation can be explained if expected reward modulates a sensory representation stage of perceptual decision-making, in addition to the better-known effects at the integration stage. DOI: http://dx.doi.org/10.7554/eLife.07832.001 PMID:26402458

Human postural responses to motion of real and virtual visual environments under different support base conditions.

PubMed

Mergner, T; Schweigart, G; Maurer, C; Blümle, A

2005-12-01

The role of visual orientation cues for human control of upright stance is still not well understood. We, therefore, investigated stance control during motion of a visual scene as stimulus, varying the stimulus parameters and the contribution from other senses (vestibular and leg proprioceptive cues present or absent). Eight normal subjects and three patients with chronic bilateral loss of vestibular function participated. They stood on a motion platform inside a cabin with an optokinetic pattern on its interior walls. The cabin was sinusoidally rotated in anterior-posterior (a-p) direction with the horizontal rotation axis through the ankle joints (f=0.05-0.4 Hz; A (max)=0.25 degrees -4 degrees ; v (max)=0.08-10 degrees /s). The subjects' centre of mass (COM) angular position was calculated from opto-electronically measured body sway parameters. The platform was either kept stationary or moved by coupling its position 1:1 to a-p hip position ('body sway referenced', BSR, platform condition), by which proprioceptive feedback of ankle joint angle became inactivated. The visual stimulus evoked in-phase COM excursions (visual responses) in all subjects. (1) In normal subjects on a stationary platform, the visual responses showed saturation with both increasing velocity and displacement of the visual stimulus. The saturation showed up abruptly when visually evoked COM velocity and displacement reached approximately 0.1 degrees /s and 0.1 degrees , respectively. (2) In normal subjects on a BSR platform (proprioceptive feedback disabled), the visual responses showed similar saturation characteristics, but at clearly higher COM velocity and displacement values ( approximately 1 degrees /s and 1 degrees , respectively). (3) In patients on a stationary platform (no vestibular cues), the visual responses were basically similar to those of the normal subjects, apart from somewhat higher gain values and less-pronounced saturation effects. (4) In patients on a BSR platform (no vestibular and proprioceptive cues, presumably only somatosensory graviceptive and visual cues), the visual responses showed an abnormal increase in gain with increasing stimulus frequency in addition to a displacement saturation. On the normal subjects we performed additional experiments in which we varied the gain of the visual response by using a 'virtual reality' visual stimulus or by applying small lateral platform tilts. This did not affect the saturation characteristics of the visual response to a considerable degree. We compared the present results to previous psychophysical findings on motion perception, noting similarities of the saturation characteristics in (1) with leg proprioceptive detection thresholds of approximately 0.1 degrees /s and 0.1 degrees and those in (2) with vestibular detection thresholds of 1 degrees /s and 1 degrees , respectively. From the psychophysical data one might hypothesise that a proprioceptive postural mechanism limits the visually evoked body excursions if these excursions exceed 0.1 degrees /s and 0.1 degrees in condition (1) and that a vestibular mechanism is doing so at 1 degrees /s and 1 degrees in (2). To better understand this, we performed computer simulations using a posture control model with multiple sensory feedbacks. We had recently designed the model to describe postural responses to body pull and platform tilt stimuli. Here, we added a visual input and adjusted its gain to fit the simulated data to the experimental data. The saturation characteristics of the visual responses of the normals were well mimicked by the simulations. They were caused by central thresholds of proprioceptive, vestibular and somatosensory signals in the model, which, however, differed from the psychophysical thresholds. Yet, we demonstrate in a theoretical approach that for condition (1) the model can be made monomodal proprioceptive with the psychophysical 0.1 degrees /s and 0.1 degrees thresholds, and for (2) monomodal vestibular with the psychophysical 1 degrees /s and 1 degrees thresholds, and still shows the corresponding saturation characteristics (whereas our original model covers both conditions without adjustments). The model simulations also predicted the almost normal visual responses of patients on a stationary platform and their clearly abnormal responses on a BSR platform.

Semantic congruency but not temporal synchrony enhances long-term memory performance for audio-visual scenes.

PubMed

Meyerhoff, Hauke S; Huff, Markus

2016-04-01

Human long-term memory for visual objects and scenes is tremendous. Here, we test how auditory information contributes to long-term memory performance for realistic scenes. In a total of six experiments, we manipulated the presentation modality (auditory, visual, audio-visual) as well as semantic congruency and temporal synchrony between auditory and visual information of brief filmic clips. Our results show that audio-visual clips generally elicit more accurate memory performance than unimodal clips. This advantage even increases with congruent visual and auditory information. However, violations of audio-visual synchrony hardly have any influence on memory performance. Memory performance remained intact even with a sequential presentation of auditory and visual information, but finally declined when the matching tracks of one scene were presented separately with intervening tracks during learning. With respect to memory performance, our results therefore show that audio-visual integration is sensitive to semantic congruency but remarkably robust against asymmetries between different modalities.

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

PubMed

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges according to associated data values. We demonstrated the advantages of these new capabilities through three biological network visualization case studies: human disease association network, drug-target interaction network and protein-peptide mapping network. The architectural design of ProteoLens makes it suitable for bioinformatics expert data analysts who are experienced with relational database management to perform large-scale integrated network visual explorations. ProteoLens is a promising visual analytic platform that will facilitate knowledge discoveries in future network and systems biology studies.

Timing, timing, timing: Fast decoding of object information from intracranial field potentials in human visual cortex

PubMed Central

Liu, Hesheng; Agam, Yigal; Madsen, Joseph R.; Kreiman, Gabriel

2010-01-01

Summary The difficulty of visual recognition stems from the need to achieve high selectivity while maintaining robustness to object transformations within hundreds of milliseconds. Theories of visual recognition differ in whether the neuronal circuits invoke recurrent feedback connections or not. The timing of neurophysiological responses in visual cortex plays a key role in distinguishing between bottom-up and top-down theories. Here we quantified at millisecond resolution the amount of visual information conveyed by intracranial field potentials from 912 electrodes in 11 human subjects. We could decode object category information from human visual cortex in single trials as early as 100 ms post-stimulus. Decoding performance was robust to depth rotation and scale changes. The results suggest that physiological activity in the temporal lobe can account for key properties of visual recognition. The fast decoding in single trials is compatible with feed-forward theories and provides strong constraints for computational models of human vision. PMID:19409272

Grid-texture mechanisms in human vision: Contrast detection of regular sparse micro-patterns requires specialist templates.

PubMed

Baker, Daniel H; Meese, Tim S

2016-07-27

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50-100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures.

Advances in Engineering Software for Lift Transportation Systems

NASA Astrophysics Data System (ADS)

Kazakoff, Alexander Borisoff

2012-03-01

In this paper an attempt is performed at computer modelling of ropeway ski lift systems. The logic in these systems is based on a travel form between the two terminals, which operates with high capacity cabins, chairs, gondolas or draw-bars. Computer codes AUTOCAD, MATLAB and Compaq-Visual Fortran - version 6.6 are used in the computer modelling. The rope systems computer modelling is organized in two stages in this paper. The first stage is organization of the ground relief profile and a design of the lift system as a whole, according to the terrain profile and the climatic and atmospheric conditions. The ground profile is prepared by the geodesists and is presented in an AUTOCAD view. The next step is the design of the lift itself which is performed by programmes using the computer code MATLAB. The second stage of the computer modelling is performed after the optimization of the co-ordinates and the lift profile using the computer code MATLAB. Then the co-ordinates and the parameters are inserted into a program written in Compaq Visual Fortran - version 6.6., which calculates 171 lift parameters, organized in 42 tables. The objective of the work presented in this paper is an attempt at computer modelling of the design and parameters derivation of the rope way systems and their computer variation and optimization.

Grid-texture mechanisms in human vision: Contrast detection of regular sparse micro-patterns requires specialist templates

PubMed Central

Baker, Daniel H.; Meese, Tim S.

2016-01-01

Previous work has shown that human vision performs spatial integration of luminance contrast energy, where signals are squared and summed (with internal noise) over area at detection threshold. We tested that model here in an experiment using arrays of micro-pattern textures that varied in overall stimulus area and sparseness of their target elements, where the contrast of each element was normalised for sensitivity across the visual field. We found a power-law improvement in performance with stimulus area, and a decrease in sensitivity with sparseness. While the contrast integrator model performed well when target elements constituted 50–100% of the target area (replicating previous results), observers outperformed the model when texture elements were sparser than this. This result required the inclusion of further templates in our model, selective for grids of various regular texture densities. By assuming a MAX operation across these noisy mechanisms the model also accounted for the increase in the slope of the psychometric function that occurred as texture density decreased. Thus, for the first time, mechanisms that are selective for texture density have been revealed at contrast detection threshold. We suggest that these mechanisms have a role to play in the perception of visual textures. PMID:27460430

Space-Based Telescopes for the Actionable Refinement of Ephemeris Systems and Test Engineering

DTIC Science & Technology

2011-12-01

Space Surveillance Network STARE Space-based Telescopes for the Actionable Refinement of Ephemeris STK Satellite Toolkit SV Space Vehicle TAMU...vacuum bake out and visual inspection. Additionally, it is prescribed that these tests be performed in accordance with GSFC-STD-7000, more commonly...environment that a FV will see in orbit. Tools such as Solid Works and NX-Ideas can be used to build CAD models to visually validate engineering

Web-Based Model Visualization Tools to Aid in Model Optimization and Uncertainty Analysis

NASA Astrophysics Data System (ADS)

Alder, J.; van Griensven, A.; Meixner, T.

2003-12-01

Individuals applying hydrologic models have a need for a quick easy to use visualization tools to permit them to assess and understand model performance. We present here the Interactive Hydrologic Modeling (IHM) visualization toolbox. The IHM utilizes high-speed Internet access, the portability of the web and the increasing power of modern computers to provide an online toolbox for quick and easy model result visualization. This visualization interface allows for the interpretation and analysis of Monte-Carlo and batch model simulation results. Often times a given project will generate several thousands or even hundreds of thousands simulations. This large number of simulations creates a challenge for post-simulation analysis. IHM's goal is to try to solve this problem by loading all of the data into a database with a web interface that can dynamically generate graphs for the user according to their needs. IHM currently supports: a global samples statistics table (e.g. sum of squares error, sum of absolute differences etc.), top ten simulations table and graphs, graphs of an individual simulation using time step data, objective based dotty plots, threshold based parameter cumulative density function graphs (as used in the regional sensitivity analysis of Spear and Hornberger) and 2D error surface graphs of the parameter space. IHM is ideal for the simplest bucket model to the largest set of Monte-Carlo model simulations with a multi-dimensional parameter and model output space. By using a web interface, IHM offers the user complete flexibility in the sense that they can be anywhere in the world using any operating system. IHM can be a time saving and money saving alternative to spending time producing graphs or conducting analysis that may not be informative or being forced to purchase or use expensive and proprietary software. IHM is a simple, free, method of interpreting and analyzing batch model results, and is suitable for novice to expert hydrologic modelers.

Slycat™ User Manual

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crossno, Patricia J.; Gittinger, Jaxon; Hunt, Warren L.

Slycat™ is a web-based system for performing data analysis and visualization of potentially large quantities of remote, high-dimensional data. Slycat™ specializes in working with ensemble data. An ensemble is a group of related data sets, which typically consists of a set of simulation runs exploring the same problem space. An ensemble can be thought of as a set of samples within a multi-variate domain, where each sample is a vector whose value defines a point in high-dimensional space. To understand and describe the underlying problem being modeled in the simulations, ensemble analysis looks for shared behaviors and common features acrossmore » the group of runs. Additionally, ensemble analysis tries to quantify differences found in any members that deviate from the rest of the group. The Slycat™ system integrates data management, scalable analysis, and visualization. Results are viewed remotely on a user’s desktop via commodity web clients using a multi-tiered hierarchy of computation and data storage, as shown in Figure 1. Our goal is to operate on data as close to the source as possible, thereby reducing time and storage costs associated with data movement. Consequently, we are working to develop parallel analysis capabilities that operate on High Performance Computing (HPC) platforms, to explore approaches for reducing data size, and to implement strategies for staging computation across the Slycat™ hierarchy. Within Slycat™, data and visual analysis are organized around projects, which are shared by a project team. Project members are explicitly added, each with a designated set of permissions. Although users sign-in to access Slycat™, individual accounts are not maintained. Instead, authentication is used to determine project access. Within projects, Slycat™ models capture analysis results and enable data exploration through various visual representations. Although for scientists each simulation run is a model of real-world phenomena given certain conditions, we use the term model to refer to our modeling of the ensemble data, not the physics. Different model types often provide complementary perspectives on data features when analyzing the same data set. Each model visualizes data at several levels of abstraction, allowing the user to range from viewing the ensemble holistically to accessing numeric parameter values for a single run. Bookmarks provide a mechanism for sharing results, enabling interesting model states to be labeled and saved.« less

Extracting heading and temporal range from optic flow: Human performance issues

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Perrone, John A.; Stone, Leland; Banks, Martin S.; Crowell, James A.

1993-01-01

Pilots are able to extract information about their vehicle motion and environmental structure from dynamic transformations in the out-the-window scene. In this presentation, we focus on the information in the optic flow which specifies vehicle heading and distance to objects in the environment, scaled to a temporal metric. In particular, we are concerned with modeling how the human operators extract the necessary information, and what factors impact their ability to utilize the critical information. In general, the psychophysical data suggest that the human visual system is fairly robust to degradations in the visual display, e.g., reduced contrast and resolution or restricted field of view. However, extraneous motion flow, i.e., introduced by sensor rotation, greatly compromises human performance. The implications of these models and data for enhanced/synthetic vision systems are discussed.

Model-based analysis of pattern motion processing in mouse primary visual cortex

PubMed Central

Muir, Dylan R.; Roth, Morgane M.; Helmchen, Fritjof; Kampa, Björn M.

2015-01-01

Neurons in sensory areas of neocortex exhibit responses tuned to specific features of the environment. In visual cortex, information about features such as edges or textures with particular orientations must be integrated to recognize a visual scene or object. Connectivity studies in rodent cortex have revealed that neurons make specific connections within sub-networks sharing common input tuning. In principle, this sub-network architecture enables local cortical circuits to integrate sensory information. However, whether feature integration indeed occurs locally in rodent primary sensory areas has not been examined directly. We studied local integration of sensory features in primary visual cortex (V1) of the mouse by presenting drifting grating and plaid stimuli, while recording the activity of neuronal populations with two-photon calcium imaging. Using a Bayesian model-based analysis framework, we classified single-cell responses as being selective for either individual grating components or for moving plaid patterns. Rather than relying on trial-averaged responses, our model-based framework takes into account single-trial responses and can easily be extended to consider any number of arbitrary predictive models. Our analysis method was able to successfully classify significantly more responses than traditional partial correlation (PC) analysis, and provides a rigorous statistical framework to rank any number of models and reject poorly performing models. We also found a large proportion of cells that respond strongly to only one stimulus class. In addition, a quarter of selectively responding neurons had more complex responses that could not be explained by any simple integration model. Our results show that a broad range of pattern integration processes already take place at the level of V1. This diversity of integration is consistent with processing of visual inputs by local sub-networks within V1 that are tuned to combinations of sensory features. PMID:26300738

Visualizing speciation in artificial cichlid fish.

PubMed

Clement, Ross

2006-01-01

The Cichlid Speciation Project (CSP) is an ALife simulation system for investigating open problems in the speciation of African cichlid fish. The CSP can be used to perform a wide range of experiments that show that speciation is a natural consequence of certain biological systems. A visualization system capable of extracting the history of speciation from low-level trace data and creating a phylogenetic tree has been implemented. Unlike previous approaches, this visualization system presents a concrete trace of speciation, rather than a summary of low-level information from which the viewer can make subjective decisions on how speciation progressed. The phylogenetic trees are a more objective visualization of speciation, and enable automated collection and summarization of the results of experiments. The visualization system is used to create a phylogenetic tree from an experiment that models sympatric speciation.

High performance visual display for HENP detectors

NASA Astrophysics Data System (ADS)

McGuigan, Michael; Smith, Gordon; Spiletic, John; Fine, Valeri; Nevski, Pavel

2001-08-01

A high end visual display for High Energy Nuclear Physics (HENP) detectors is necessary because of the sheer size and complexity of the detector. For BNL this display will be of special interest because of STAR and ATLAS. To load, rotate, query, and debug simulation code with a modern detector simply takes too long even on a powerful work station. To visualize the HENP detectors with maximal performance we have developed software with the following characteristics. We develop a visual display of HENP detectors on BNL multiprocessor visualization server at multiple level of detail. We work with general and generic detector framework consistent with ROOT, GAUDI etc, to avoid conflicting with the many graphic development groups associated with specific detectors like STAR and ATLAS. We develop advanced OpenGL features such as transparency and polarized stereoscopy. We enable collaborative viewing of detector and events by directly running the analysis in BNL stereoscopic theatre. We construct enhanced interactive control, including the ability to slice, search and mark areas of the detector. We incorporate the ability to make a high quality still image of a view of the detector and the ability to generate animations and a fly through of the detector and output these to MPEG or VRML models. We develop data compression hardware and software so that remote interactive visualization will be possible among dispersed collaborators. We obtain real time visual display for events accumulated during simulations.

Matching voice and face identity from static images.

PubMed

Mavica, Lauren W; Barenholtz, Elan

2013-04-01

Previous research has suggested that people are unable to correctly choose which unfamiliar voice and static image of a face belong to the same person. Here, we present evidence that people can perform this task with greater than chance accuracy. In Experiment 1, participants saw photographs of two, same-gender models, while simultaneously listening to a voice recording of one of the models pictured in the photographs and chose which of the two faces they thought belonged to the same model as the recorded voice. We included three conditions: (a) the visual stimuli were frontal headshots (including the neck and shoulders) and the auditory stimuli were recordings of spoken sentences; (b) the visual stimuli only contained cropped faces and the auditory stimuli were full sentences; (c) we used the same pictures as Condition 1 but the auditory stimuli were recordings of a single word. In Experiment 2, participants performed the same task as in Condition 1 of Experiment 1 but with the stimuli presented in sequence. Participants also rated the model's faces and voices along multiple "physical" dimensions (e.g., weight,) or "personality" dimensions (e.g., extroversion); the degree of agreement between the ratings for each model's face and voice was compared to performance for that model in the matching task. In all three conditions, we found that participants chose, at better than chance levels, which faces and voices belonged to the same person. Performance in the matching task was not correlated with the degree of agreement on any of the rated dimensions.

Spatial transformations between superior colliculus visual and motor response fields during head-unrestrained gaze shifts.

PubMed

Sadeh, Morteza; Sajad, Amirsaman; Wang, Hongying; Yan, Xiaogang; Crawford, John Douglas

2015-12-01

We previously reported that visuomotor activity in the superior colliculus (SC)--a key midbrain structure for the generation of rapid eye movements--preferentially encodes target position relative to the eye (Te) during low-latency head-unrestrained gaze shifts (DeSouza et al., 2011). Here, we trained two monkeys to perform head-unrestrained gaze shifts after a variable post-stimulus delay (400-700 ms), to test whether temporally separated SC visual and motor responses show different spatial codes. Target positions, final gaze positions and various frames of reference (eye, head, and space) were dissociated through natural (untrained) trial-to-trial variations in behaviour. 3D eye and head orientations were recorded, and 2D response field data were fitted against multiple models by use of a statistical method reported previously (Keith et al., 2009). Of 60 neurons, 17 showed a visual response, 12 showed a motor response, and 31 showed both visual and motor responses. The combined visual response field population (n = 48) showed a significant preference for Te, which was also preferred in each visual subpopulation. In contrast, the motor response field population (n = 43) showed a preference for final (relative to initial) gaze position models, and the Te model was statistically eliminated in the motor-only population. There was also a significant shift of coding from the visual to motor response within visuomotor neurons. These data confirm that SC response fields are gaze-centred, and show a target-to-gaze transformation between visual and motor responses. Thus, visuomotor transformations can occur between, and even within, neurons within a single frame of reference and brain structure. © 2015 Federation of European Neuroscience Societies and John Wiley & Sons Ltd.

Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia).

PubMed

Azizi, Amir Hossein; Pusch, Roland; Koenen, Charlotte; Klatt, Sebastian; Bröcker, Franziska; Thiele, Samuel; Kellermann, Janosch; Güntürkün, Onur; Cheng, Sen

2018-06-06

Recognizing and categorizing visual stimuli are cognitive functions vital for survival, and an important feature of visual systems in primates as well as in birds. Visual stimuli are processed along the ventral visual pathway. At every stage in the hierarchy, neurons respond selectively to more complex features, transforming the population representation of the stimuli. It is therefore easier to read-out category information in higher visual areas. While explicit category representations have been observed in the primate brain, less is known on equivalent processes in the avian brain. Even though their brain anatomies are radically different, it has been hypothesized that visual object representations are comparable across mammals and birds. In the present study, we investigated category representations in the pigeon visual forebrain using recordings from single cells responding to photographs of real-world objects. Using a linear classifier, we found that the population activity in the visual associative area mesopallium ventrolaterale (MVL) distinguishes between animate and inanimate objects, although this distinction is not required by the task. By contrast, a population of cells in the entopallium, a region that is lower in the hierarchy of visual areas and that is related to the primate extrastriate cortex, lacked this information. A model that pools responses of simple cells, which function as edge detectors, can account for the animate vs. inanimate categorization in the MVL, but performance in the model is based on different features than in MVL. Therefore, processing in MVL cells is very likely more abstract than simple computations on the output of edge detectors. Copyright © 2018. Published by Elsevier B.V.

XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Geveci, Berk; Maynard, Robert

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respectivemore » features into a new visualization toolkit called VTK-m.« less

The relation of object naming and other visual speech production tasks: a large scale voxel-based morphometric study.

PubMed

Lau, Johnny King L; Humphreys, Glyn W; Douis, Hassan; Balani, Alex; Bickerton, Wai-Ling; Rotshtein, Pia

2015-01-01

We report a lesion-symptom mapping analysis of visual speech production deficits in a large group (280) of stroke patients at the sub-acute stage (<120 days post-stroke). Performance on object naming was evaluated alongside three other tests of visual speech production, namely sentence production to a picture, sentence reading and nonword reading. A principal component analysis was performed on all these tests' scores and revealed a 'shared' component that loaded across all the visual speech production tasks and a 'unique' component that isolated object naming from the other three tasks. Regions for the shared component were observed in the left fronto-temporal cortices, fusiform gyrus and bilateral visual cortices. Lesions in these regions linked to both poor object naming and impairment in general visual-speech production. On the other hand, the unique naming component was potentially associated with the bilateral anterior temporal poles, hippocampus and cerebellar areas. This is in line with the models proposing that object naming relies on a left-lateralised language dominant system that interacts with a bilateral anterior temporal network. Neuropsychological deficits in object naming can reflect both the increased demands specific to the task and the more general difficulties in language processing.

Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.

PubMed

Stein, Manuel; Janetzko, Halldor; Lamprecht, Andreas; Breitkreutz, Thorsten; Zimmermann, Philipp; Goldlucke, Bastian; Schreck, Tobias; Andrienko, Gennady; Grossniklaus, Michael; Keim, Daniel A

2018-01-01

Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.

Superior Intraparietal Sulcus Controls the Variability of Visual Working Memory Precision.

PubMed

Galeano Weber, Elena M; Peters, Benjamin; Hahn, Tim; Bledowski, Christoph; Fiebach, Christian J

2016-05-18

Limitations of working memory (WM) capacity depend strongly on the cognitive resources that are available for maintaining WM contents in an activated state. Increasing the number of items to be maintained in WM was shown to reduce the precision of WM and to increase the variability of WM precision over time. Although WM precision was recently associated with neural codes particularly in early sensory cortex, we have so far no understanding of the neural bases underlying the variability of WM precision, and how WM precision is preserved under high load. To fill this gap, we combined human fMRI with computational modeling of behavioral performance in a delayed color-estimation WM task. Behavioral results replicate a reduction of WM precision and an increase of precision variability under high loads (5 > 3 > 1 colors). Load-dependent BOLD signals in primary visual cortex (V1) and superior intraparietal sulcus (IPS), measured during the WM task at 2-4 s after sample onset, were modulated by individual differences in load-related changes in the variability of WM precision. Although stronger load-related BOLD increase in superior IPS was related to lower increases in precision variability, thus stabilizing WM performance, the reverse was observed for V1. Finally, the detrimental effect of load on behavioral precision and precision variability was accompanied by a load-related decline in the accuracy of decoding the memory stimuli (colors) from left superior IPS. We suggest that the superior IPS may contribute to stabilizing visual WM performance by reducing the variability of memory precision in the face of higher load. This study investigates the neural bases of capacity limitations in visual working memory by combining fMRI with cognitive modeling of behavioral performance, in human participants. It provides evidence that the superior intraparietal sulcus (IPS) is a critical brain region that influences the variability of visual working memory precision between and within individuals (Fougnie et al., 2012; van den Berg et al., 2012) under increased memory load, possibly in cooperation with perceptual systems of the occipital cortex. These findings substantially extend our understanding of the nature of capacity limitations in visual working memory and their neural bases. Our work underlines the importance of integrating cognitive modeling with univariate and multivariate methods in fMRI research, thus improving our knowledge of brain-behavior relationships. Copyright © 2016 the authors 0270-6474/16/365623-13$15.00/0.

Visual Performance Manual.

ERIC Educational Resources Information Center

Chaikin, Rosalind B.; And Others

Intended for classroom teachers, the manual provides an approach to observation, assessment, record keeping, and remediation of students' visual performance. A list of clues for detecting visual performance difficulties and nine laws applicable to visual performance development tasks are given. Described in two sections are the materials, steps,…

cellPACK: A Virtual Mesoscope to Model and Visualize Structural Systems Biology

PubMed Central

Johnson, Graham T.; Autin, Ludovic; Al-Alusi, Mostafa; Goodsell, David S.; Sanner, Michel F.; Olson, Arthur J.

2014-01-01

cellPACK assembles computational models of the biological mesoscale, an intermediate scale (10−7–10−8m) between molecular and cellular biology. cellPACK’s modular architecture unites existing and novel packing algorithms to generate, visualize and analyze comprehensive 3D models of complex biological environments that integrate data from multiple experimental systems biology and structural biology sources. cellPACK is currently available as open source code, with tools for validation of models and with recipes and models for five biological systems: blood plasma, cytoplasm, synaptic vesicles, HIV and a mycoplasma cell. We have applied cellPACK to model distributions of HIV envelope protein to test several hypotheses for consistency with experimental observations. Biologists, educators, and outreach specialists can interact with cellPACK models, develop new recipes and perform packing experiments through scripting and graphical user interfaces at http://cellPACK.org. PMID:25437435

Models of Speed Discrimination

NASA Technical Reports Server (NTRS)

1997-01-01

The prime purpose of this project was to investigate various theoretical issues concerning the integration of information across visual space. To date, most of the research efforts in the study of the visual system seem to have been focused in two almost non-overlaping directions. One research focus has been the low level perception as studied by psychophysics. The other focus has been the study of high level vision exemplified by the study of object perception. Most of the effort in psychophysics has been devoted to the search for the fundamental "features" of perception. The general idea is that the most peripheral processes of the visual system decompose the input into features that are then used for classification and recognition. The experimental and theoretical focus has been on finding and describing these analyzers that decompose images into useful components. Various models are then compared to the physiological measurements performed on neurons in the sensory systems. In the study of higher level perception, the work has been focused on the representation of objects and on the connections between various physical effects and object perception. In this category we find the perception of 3D from a variety of physical measurements including motion, shading and other physical phenomena. With few exceptions, there seem to be very limited development of theories describing how the visual system might combine the output of the analyzers to form the representation of visual objects. Therefore, the processes underlying the integration of information over space represent critical aspects of vision system. The understanding of these processes will have implications on our expectations for the underlying physiological mechanisms, as well as for our models of the internal representation for visual percepts. In this project, we explored several mechanisms related to spatial summation, attention, and eye movements. The project comprised three components: 1. Modeling visual search for the detection of speed deviation. 2. Perception of moving objects. 3. Exploring the role of eye movements in various visual tasks.

Do the Details Matter? Comparing Performance Forecasts from Two Computational Theories of Fatigue

DTIC Science & Technology

2009-12-01

Bulletin & Review , 9(1), 3-25. Dinges, D. F., & Powell, J. W. (1985). Microcomputer analyses of performance on a portable, simple visual RT task during...Force Office of Scientific Research (AFOSR). References Estes, W. K. (2002). Traps in the route to models of memory and decision. Psychonomic

Individual Differences in Visual Word Recognition: Insights from the English Lexicon Project

PubMed Central

Yap, Melvin J.; Balota, David A.; Sibley, Daragh E.; Ratcliff, Roger

2011-01-01

Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences between individuals who contributed to the English Lexicon Project (http://elexicon.wustl.edu), an online behavioral database containing nearly four million word recognition (speeded pronunciation and lexical decision) trials from over 1,200 participants. We observed considerable within- and between-session reliability across distinct sets of items, in terms of overall mean response time (RT), RT distributional characteristics, diffusion model parameters (Ratcliff, Gomez, & McKoon, 2004), and sensitivity to underlying lexical dimensions. This indicates reliably detectable individual differences in word recognition performance. In addition, higher vocabulary knowledge was associated with faster, more accurate word recognition performance, attenuated sensitivity to stimuli characteristics, and more efficient accumulation of information. Finally, in contrast to suggestions in the literature, we did not find evidence that individuals were trading-off in their utilization of lexical and nonlexical information. PMID:21728459

Visual Working Memory Cannot Trade Quantity for Quality.

PubMed

Ramaty, Ayelet; Luria, Roy

2018-01-01

Two main models have been proposed to describe how visual working memory (WM) allocates its capacity: the slot-model and the continuous resource-model. The purpose of the current study was to test a direct prediction of the resource model suggesting that WM can trade-off between the quantity and quality of the encoded information. Previous research reported equivocal results, with studies that failed to find such a trade-off and other studies that reported a trade-off. Following the design of previous studies, in Experiment 1 we replicated this trade-off, by presenting the memory array for 1200 ms. Experiment 2 failed to observe a trade-off between quantity and quality using a memory array interval of 300 ms (a standard interval for visual WM). Experiment 3 again failed to find this trade-off, when reinstating the 1200 ms memory array interval but adding an articulatory suppression manipulation. We argue that while participants can trade quantity for quality, this pattern depends on verbal encoding and transfer to long-term memory processes that were possible to perform only during the long retention interval. When these processes were eliminated, the trade-off disappeared. Thus, we didn't find any evidence that the trade-off between quantity for quality can occur within visual WM.

Driving and off-road impairments underlying failure on road testing in Parkinson's disease.

PubMed

Devos, Hannes; Vandenberghe, Wim; Tant, Mark; Akinwuntan, Abiodun E; De Weerdt, Willy; Nieuwboer, Alice; Uc, Ergun Y

2013-12-01

Parkinson's disease (PD) affects driving ability. We aimed to determine the most critical impairments in specific road skills and in clinical characteristics leading to failure on a road test in PD. In this cross-sectional study, certified driving assessment experts evaluated specific driving skills in 104 active, licensed drivers with PD using a standardized, on-road checklist and issued a global decision of pass/fail. Participants also completed an off-road evaluation assessing demographic features, disease characteristics, motor function, vision, and cognition. The most important driving skills and off-road predictors of the pass/fail outcome were identified using multivariate stepwise regression analyses. Eighty-six (65%) passed and 36 (35%) failed the on-road driving evaluation. Persons who failed performed worse on all on-road items. When adjusted for age and gender, poor performances on lateral positioning at low speed, speed adaptations at high speed, and left turning maneuvers yielded the best model that determined the pass/fail decision (R(2) = 0.56). The fail group performed poorer on all motor, visual, and cognitive tests. Measures of visual scanning, motor severity, PD subtype, visual acuity, executive functions, and divided attention were independent predictors of pass/fail decisions in the multivariate model (R(2) = 0.60). Our study demonstrated that failure on a road test in PD is determined by impairments in specific driving skills and associated with deficits in motor, visual, executive, and visuospatial functions. These findings point to specific driving and off-road impairments that can be targeted in multimodal rehabilitation programs for drivers with PD. © 2013 Movement Disorder Society.

Secondary visual workload capability with primary visual and kinesthetic-tactual displays

NASA Technical Reports Server (NTRS)

Gilson, R. D.; Burke, M. W.; Jagacinski, R. J.

1978-01-01

Subjects performed a cross-adaptive tracking task with a visual secondary display and either a visual or a quickened kinesthetic-tactual (K-T) primary display. The quickened K-T display resulted in superior secondary task performance. Comparisons of secondary workload capability with integrated and separated visual displays indicated that the superiority of the quickened K-T display was not simply due to the elimination of visual scanning. When subjects did not have to perform a secondary task, there was no significant difference between visual and quickened K-T displays in performing a critical tracking task.

Model My Watershed: A high-performance cloud application for public engagement, watershed modeling and conservation decision support

NASA Astrophysics Data System (ADS)

Aufdenkampe, A. K.; Tarboton, D. G.; Horsburgh, J. S.; Mayorga, E.; McFarland, M.; Robbins, A.; Haag, S.; Shokoufandeh, A.; Evans, B. M.; Arscott, D. B.

2017-12-01

The Model My Watershed Web app (https://app.wikiwatershed.org/) and the BiG-CZ Data Portal (http://portal.bigcz.org/) and are web applications that share a common codebase and a common goal to deliver high-performance discovery, visualization and analysis of geospatial data in an intuitive user interface in web browser. Model My Watershed (MMW) was designed as a decision support system for watershed conservation implementation. BiG CZ Data Portal was designed to provide context and background data for research sites. Users begin by creating an Area of Interest, via an automated watershed delineation tool, a free draw tool, selection of a predefined area such as a county or USGS Hydrological Unit (HUC), or uploading a custom polygon. Both Web apps visualize and provide summary statistics of land use, soil groups, streams, climate and other geospatial information. MMW then allows users to run a watershed model to simulate different scenarios of human impacts on stormwater runoff and water-quality. BiG CZ Data Portal allows users to search for scientific and monitoring data within the Area of Interest, which also serves as a prototype for the upcoming Monitor My Watershed web app. Both systems integrate with CUAHSI cyberinfrastructure, including visualizing observational data from CUAHSI Water Data Center and storing user data via CUAHSI HydroShare. Both systems also integrate with the new EnviroDIY Water Quality Data Portal (http://data.envirodiy.org/), a system for crowd-sourcing environmental monitoring data using open-source sensor stations (http://envirodiy.org/mayfly/) and based on the Observations Data Model v2.

An Exemplar-Familiarity Model Predicts Short-Term and Long-Term Probe Recognition across Diverse Forms of Memory Search

ERIC Educational Resources Information Center

Nosofsky, Robert M.; Cox, Gregory E.; Cao, Rui; Shiffrin, Richard M.

2014-01-01

Experiments were conducted to test a modern exemplar-familiarity model on its ability to account for both short-term and long-term probe recognition within the same memory-search paradigm. Also, making connections to the literature on attention and visual search, the model was used to interpret differences in probe-recognition performance across…

Image processing, geometric modeling and data management for development of a virtual bone surgery system.

PubMed

Niu, Qiang; Chi, Xiaoyi; Leu, Ming C; Ochoa, Jorge

2008-01-01

This paper describes image processing, geometric modeling and data management techniques for the development of a virtual bone surgery system. Image segmentation is used to divide CT scan data into different segments representing various regions of the bone. A region-growing algorithm is used to extract cortical bone and trabecular bone structures systematically and efficiently. Volume modeling is then used to represent the bone geometry based on the CT scan data. Material removal simulation is achieved by continuously performing Boolean subtraction of the surgical tool model from the bone model. A quadtree-based adaptive subdivision technique is developed to handle the large set of data in order to achieve the real-time simulation and visualization required for virtual bone surgery. A Marching Cubes algorithm is used to generate polygonal faces from the volumetric data. Rendering of the generated polygons is performed with the publicly available VTK (Visualization Tool Kit) software. Implementation of the developed techniques consists of developing a virtual bone-drilling software program, which allows the user to manipulate a virtual drill to make holes with the use of a PHANToM device on a bone model derived from real CT scan data.

Performance characteristics of a visual-search human-model observer with sparse PET image data

NASA Astrophysics Data System (ADS)

Gifford, Howard C.

2012-02-01

As predictors of human performance in detection-localization tasks, statistical model observers can have problems with tasks that are primarily limited by target contrast or structural noise. Model observers with a visual-search (VS) framework may provide a more reliable alternative. This framework provides for an initial holistic search that identifies suspicious locations for analysis by a statistical observer. A basic VS observer for emission tomography focuses on hot "blobs" in an image and uses a channelized nonprewhitening (CNPW) observer for analysis. In [1], we investigated this model for a contrast-limited task with SPECT images; herein, a statisticalnoise limited task involving PET images is considered. An LROC study used 2D image slices with liver, lung and soft-tissue tumors. Human and model observers read the images in coronal, sagittal and transverse display formats. The study thus measured the detectability of tumors in a given organ as a function of display format. The model observers were applied under several task variants that tested their response to structural noise both at the organ boundaries alone and over the organs as a whole. As measured by correlation with the human data, the VS observer outperformed the CNPW scanning observer.

Adolescent fluoxetine exposure produces enduring, sex-specific alterations of visual discrimination and attention in rats.

PubMed

LaRoche, Ronee B; Morgan, Russell E

2007-01-01

Over the past two decades the use of selective serotonin reuptake inhibitors (SSRIs) to treat behavioral disorders in children has grown rapidly, despite little evidence regarding the safety and efficacy of these drugs for use in children. Utilizing a rat model, this study investigated whether post-weaning exposure to a prototype SSRI, fluoxetine (FLX), influenced performance on visual tasks designed to measure discrimination learning, sustained attention, inhibitory control, and reaction time. Additionally, sex differences in response to varying doses of fluoxetine were examined. In Experiment 1, female rats were administered (P.O.) fluoxetine (10 mg/kg ) or vehicle (apple juice) from PND 25 thru PND 49. After a 14 day washout period, subjects were trained to perform a simultaneous visual discrimination task. Subjects were then tested for 20 sessions on a visual attention task that consisted of varied stimulus delays (0, 3, 6, or 9 s) and cue durations (200, 400, or 700 ms). In Experiment 2, both male and female Long-Evans rats (24 F, 24 M) were administered fluoxetine (0, 5, 10, or 15 mg/kg) then tested in the same visual tasks used in Experiment 1, with the addition of open-field and elevated plus-maze testing. Few FLX-related differences were seen in the visual discrimination, open field, or plus-maze tasks. However, results from the visual attention task indicated a dose-dependent reduction in the performance of fluoxetine-treated males, whereas fluoxetine-treated females tended to improve over baseline. These findings indicate that enduring, behaviorally-relevant alterations of the CNS can occur following pharmacological manipulation of the serotonin system during postnatal development.

On the flow through the normal fetal aortic arc at late gestation

NASA Astrophysics Data System (ADS)

Pekkan, Kerem; Nourparvar, Paymon; Yerneni, Srinivasu; Dasi, Lakshmi; de Zelicourt, Diane; Fogel, Mark; Yoganathan, Ajit

2006-11-01

During the fetal stage, the aortic arc is a complex junction of great vessels (right and left ventricular outflow tracks (RVOT, LVOT), pulmonary arteries (PA), ductus, head-neck vessels, decending aorta (Dao)) delicately distributing the oxygenated blood flow to the lungs and the body -preferential to the brain. Experimental and computational studies are performed in idealized models of the fetal aorta to understand and visualize the unsteady hemodynamics. Unsteady in vitro flow, generated by two peristaltic pumps (RVOT and LVOT) is visualized with two colored dyes and a red laser in a rigid glass model with physiological diameters. Helical flow patterns at the PA's and ductal shunting to the Dao are visualized. Computational fluid dynamics of the same geometry is modeled using the commercial code Fidap with porous boundary conditions representing systemic and pulmonary resistances (˜400000 tetrahedral elements). Combined (RVOT+LVOT) average flow rates ranging from 1.9 to 2.1-L/min for 34 to 38-weeks gestation were simulated with the Reynolds and Womersly numbers (Dao) of 500 and 8. Computational results are compared qualitatively with the flow visualizations at this target flow condition. Understanding fetal hemodynamics is critical for congenital heart defects, tissue engineering, fetal cardiac MRI and surgeries.

Integration of real-time 3D capture, reconstruction, and light-field display

NASA Astrophysics Data System (ADS)

Zhang, Zhaoxing; Geng, Zheng; Li, Tuotuo; Pei, Renjing; Liu, Yongchun; Zhang, Xiao

2015-03-01

Effective integration of 3D acquisition, reconstruction (modeling) and display technologies into a seamless systems provides augmented experience of visualizing and analyzing real objects and scenes with realistic 3D sensation. Applications can be found in medical imaging, gaming, virtual or augmented reality and hybrid simulations. Although 3D acquisition, reconstruction, and display technologies have gained significant momentum in recent years, there seems a lack of attention on synergistically combining these components into a "end-to-end" 3D visualization system. We designed, built and tested an integrated 3D visualization system that is able to capture in real-time 3D light-field images, perform 3D reconstruction to build 3D model of the objects, and display the 3D model on a large autostereoscopic screen. In this article, we will present our system architecture and component designs, hardware/software implementations, and experimental results. We will elaborate on our recent progress on sparse camera array light-field 3D acquisition, real-time dense 3D reconstruction, and autostereoscopic multi-view 3D display. A prototype is finally presented with test results to illustrate the effectiveness of our proposed integrated 3D visualization system.

Fixation and saliency during search of natural scenes: the case of visual agnosia.

PubMed

Foulsham, Tom; Barton, Jason J S; Kingstone, Alan; Dewhurst, Richard; Underwood, Geoffrey

2009-07-01

Models of eye movement control in natural scenes often distinguish between stimulus-driven processes (which guide the eyes to visually salient regions) and those based on task and object knowledge (which depend on expectations or identification of objects and scene gist). In the present investigation, the eye movements of a patient with visual agnosia were recorded while she searched for objects within photographs of natural scenes and compared to those made by students and age-matched controls. Agnosia is assumed to disrupt the top-down knowledge available in this task, and so may increase the reliance on bottom-up cues. The patient's deficit in object recognition was seen in poor search performance and inefficient scanning. The low-level saliency of target objects had an effect on responses in visual agnosia, and the most salient region in the scene was more likely to be fixated by the patient than by controls. An analysis of model-predicted saliency at fixation locations indicated a closer match between fixations and low-level saliency in agnosia than in controls. These findings are discussed in relation to saliency-map models and the balance between high and low-level factors in eye guidance.

When Kinesthesia Becomes Visual: A Theoretical Justification for Executing Motor Tasks in Visual Space

PubMed Central

Tagliabue, Michele; McIntyre, Joseph

2013-01-01

Several experimental studies in the literature have shown that even when performing purely kinesthetic tasks, such as reaching for a kinesthetically felt target with a hidden hand, the brain reconstructs a visual representation of the movement. In our previous studies, however, we did not observe any role of a visual representation of the movement in a purely kinesthetic task. This apparent contradiction could be related to a fundamental difference between the studied tasks. In our study subjects used the same hand to both feel the target and to perform the movement, whereas in most other studies, pointing to a kinesthetic target consisted of pointing with one hand to the finger of the other, or to some other body part. We hypothesize, therefore, that it is the necessity of performing inter-limb transformations that induces a visual representation of purely kinesthetic tasks. To test this hypothesis we asked subjects to perform the same purely kinesthetic task in two conditions: INTRA and INTER. In the former they used the right hand to both perceive the target and to reproduce its orientation. In the latter, subjects perceived the target with the left hand and responded with the right. To quantify the use of a visual representation of the movement we measured deviations induced by an imperceptible conflict that was generated between visual and kinesthetic reference frames. Our hypothesis was confirmed by the observed deviations of responses due to the conflict in the INTER, but not in the INTRA, condition. To reconcile these observations with recent theories of sensori-motor integration based on maximum likelihood estimation, we propose here a new model formulation that explicitly considers the effects of covariance between sensory signals that are directly available and internal representations that are ‘reconstructed’ from those inputs through sensori-motor transformations. PMID:23861903

Parametric estimation for reinforced concrete relief shelter for Aceh cases

NASA Astrophysics Data System (ADS)

Atthaillah; Saputra, Eri; Iqbal, Muhammad

2018-05-01

This paper was a work in progress (WIP) to discover a rapid parametric framework for post-disaster permanent shelter’s materials estimation. The intended shelters were reinforced concrete construction with bricks as its wall. Inevitably, in post-disaster cases, design variations were needed to help suited victims condition. It seemed impossible to satisfy a beneficiary with a satisfactory design utilizing the conventional method. This study offered a parametric framework to overcome slow construction-materials estimation issue against design variations. Further, this work integrated parametric tool, which was Grasshopper to establish algorithms that simultaneously model, visualize, calculate and write the calculated data to a spreadsheet in a real-time. Some customized Grasshopper components were created using GHPython scripting for a more optimized algorithm. The result from this study was a partial framework that successfully performed modeling, visualization, calculation and writing the calculated data simultaneously. It meant design alterations did not escalate time needed for modeling, visualization, and material estimation. Further, the future development of the parametric framework will be made open source.

Comparing Motor Skills in Autism Spectrum Individuals With and Without Speech Delay

PubMed Central

Barbeau, Elise B.; Meilleur, Andrée‐Anne S.; Zeffiro, Thomas A.

2015-01-01

Movement atypicalities in speed, coordination, posture, and gait have been observed across the autism spectrum (AS) and atypicalities in coordination are more commonly observed in AS individuals without delayed speech (DSM‐IV Asperger) than in those with atypical or delayed speech onset. However, few studies have provided quantitative data to support these mostly clinical observations. Here, we compared perceptual and motor performance between 30 typically developing and AS individuals (21 with speech delay and 18 without speech delay) to examine the associations between limb movement control and atypical speech development. Groups were matched for age, intelligence, and sex. The experimental design included: an inspection time task, which measures visual processing speed; the Purdue Pegboard, which measures finger dexterity, bimanual performance, and hand‐eye coordination; the Annett Peg Moving Task, which measures unimanual goal‐directed arm movement; and a simple reaction time task. We used analysis of covariance to investigate group differences in task performance and linear regression models to explore potential associations between intelligence, language skills, simple reaction time, and visually guided movement performance. AS participants without speech delay performed slower than typical participants in the Purdue Pegboard subtests. AS participants without speech delay showed poorer bimanual coordination than those with speech delay. Visual processing speed was slightly faster in both AS groups than in the typical group. Altogether, these results suggest that AS individuals with and without speech delay differ in visually guided and visually triggered behavior and show that early language skills are associated with slower movement in simple and complex motor tasks. Autism Res 2015, 8: 682–693. © 2015 The Authors Autism Research published by Wiley Periodicals, Inc. on behalf of International Society for Autism Research PMID:25820662

Visual Data-Analytics of Large-Scale Parallel Discrete-Event Simulations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ross, Caitlin; Carothers, Christopher D.; Mubarak, Misbah

Parallel discrete-event simulation (PDES) is an important tool in the codesign of extreme-scale systems because PDES provides a cost-effective way to evaluate designs of highperformance computing systems. Optimistic synchronization algorithms for PDES, such as Time Warp, allow events to be processed without global synchronization among the processing elements. A rollback mechanism is provided when events are processed out of timestamp order. Although optimistic synchronization protocols enable the scalability of large-scale PDES, the performance of the simulations must be tuned to reduce the number of rollbacks and provide an improved simulation runtime. To enable efficient large-scale optimistic simulations, one has tomore » gain insight into the factors that affect the rollback behavior and simulation performance. We developed a tool for ROSS model developers that gives them detailed metrics on the performance of their large-scale optimistic simulations at varying levels of simulation granularity. Model developers can use this information for parameter tuning of optimistic simulations in order to achieve better runtime and fewer rollbacks. In this work, we instrument the ROSS optimistic PDES framework to gather detailed statistics about the simulation engine. We have also developed an interactive visualization interface that uses the data collected by the ROSS instrumentation to understand the underlying behavior of the simulation engine. The interface connects real time to virtual time in the simulation and provides the ability to view simulation data at different granularities. We demonstrate the usefulness of our framework by performing a visual analysis of the dragonfly network topology model provided by the CODES simulation framework built on top of ROSS. The instrumentation needs to minimize overhead in order to accurately collect data about the simulation performance. To ensure that the instrumentation does not introduce unnecessary overhead, we perform a scaling study that compares instrumented ROSS simulations with their noninstrumented counterparts in order to determine the amount of perturbation when running at different simulation scales.« less

Improved Intraoperative Visualization of Nerves through a Myelin-Binding Fluorophore and Dual-Mode Laparoscopic Imaging.

PubMed

Cotero, Victoria E; Kimm, Simon Y; Siclovan, Tiberiu M; Zhang, Rong; Kim, Evgenia M; Matsumoto, Kazuhiro; Gondo, Tatsuo; Scardino, Peter T; Yazdanfar, Siavash; Laudone, Vincent P; Tan Hehir, Cristina A

2015-01-01

The ability to visualize and spare nerves during surgery is critical for avoiding chronic morbidity, pain, and loss of function. Visualization of such critical anatomic structures is even more challenging during minimal access procedures because the small incisions limit visibility. In this study, we focus on improving imaging of nerves through the use of a new small molecule fluorophore, GE3126, used in conjunction with our dual-mode (color and fluorescence) laparoscopic imaging instrument. GE3126 has higher aqueous solubility, improved pharmacokinetics, and reduced non-specific adipose tissue fluorescence compared to previous myelin-binding fluorophores. Dosing and kinetics were initially optimized in mice. A non-clinical modified Irwin study in rats, performed to assess the potential of GE3126 to induce nervous system injuries, showed the absence of major adverse reactions. Real-time intraoperative imaging was performed in a porcine model. Compared to white light imaging, nerve visibility was enhanced under fluorescence guidance, especially for small diameter nerves obscured by fascia, blood vessels, or adipose tissue. In the porcine model, nerve visualization was observed rapidly, within 5 to 10 minutes post-intravenous injection and the nerve fluorescence signal was maintained for up to 80 minutes. The use of GE3126, coupled with practical implementation of an imaging instrument may be an important step forward in preventing nerve damage in the operating room.

Evidence of a Heterogeneous Tissue Oxygenation: Renal Ischemia/Reperfusion Injury in a Large Animal Model

DTIC Science & Technology

2013-03-01

operation. 2.1.2 Canine model The canine experiment (n ¼ 1) was performed as a validation of the correlation of visible reflectance imaging measurements...http://spiedl.org/terms with actual blood oxygenation. The canine laparotomy, as part of an animal protocol approved by the Institutional Animal Care and...All data analysis was performed using algorithms and software written in-house using the programming languages Matlab and IDL/ ENVI (ITT Visual

Consequences of seasonal variation in reservoir water level for predatory fishes: linking visual foraging and prey densities

USGS Publications Warehouse

Klobucar, Stephen L.; Budy, Phaedra

2016-01-01

In reservoirs, seasonal drawdown can alter the physical environment and may influence predatory fish performance. We investigated the performance of lake trout (Salvelinus namaycush) in a western reservoir by coupling field measurements with visual foraging and bioenergetic models at four distinct states (early summer, mid-summer, late summer, and fall). The models suggested that lake trout prey, juvenile kokanee (Oncorhynchus nerka), are limited seasonally by suitable temperature and dissolved oxygen. Accordingly, prey densities were greatest in late summer when reservoir volume was lowest and fish were concentrated by stratification. Prey encounter rates (up to 68 fish·day−1) and predator consumption are also predicted to be greatest during late summer. However, our models suggested that turbidity negatively correlates with prey detection and consumption across reservoir states. Under the most turbid conditions, lake trout did not meet physiological demands; however, during less turbid periods, predator consumption reached maximum bioenergetic efficiency. Overall, our findings demonstrate that rapid reservoir fluctuations and associated abiotic conditions can influence predator–prey interactions, and our models describe the potential impacts of water level fluctuation on valuable sport fishes.

Study on the transverse chromatic aberration of the individual eye model after LASIK refractive surgery

NASA Astrophysics Data System (ADS)

Zhang, Mei; Wang, Zhao-Qi; Wang, Yan; Zuo, Tong

2010-10-01

The aim of this research is to study the properties of the transverse chromatic aberration (TCA) after the LASIK refractive surgery based on the individual eye model involving the angle between visual axis and optical axis. According to the measurements of the corneal surfaces, the optical axis lengths and the wavefront aberrations, the individual eye models before and after LASIK refractive surgery are constructed for 15 eyes by using ZEMAX optic design software, while the angle between the visual axis and optical axis is calculated from the data of the anterior corneal surface. The constructed eye models are then used to investigate the variation of the TCA after the surgery. The statistical distributions of the magnitude of the foveal TCA for 15 eyes over the visible spectrum are provided. Finally, we investigate the influence of the TCA on the visual quality and compare the results with previous research. The TCA is an indispensable criterion to evaluate the performance of the refractive surgery. This research is very meaningful for the studies of not only foveal vision but also the peripheral vision.

Digital fabrication of multi-material biomedical objects.

PubMed

Cheung, H H; Choi, S H

2009-12-01

This paper describes a multi-material virtual prototyping (MMVP) system for modelling and digital fabrication of discrete and functionally graded multi-material objects for biomedical applications. The MMVP system consists of a DMMVP module, an FGMVP module and a virtual reality (VR) simulation module. The DMMVP module is used to model discrete multi-material (DMM) objects, while the FGMVP module is for functionally graded multi-material (FGM) objects. The VR simulation module integrates these two modules to perform digital fabrication of multi-material objects, which can be subsequently visualized and analysed in a virtual environment to optimize MMLM processes for fabrication of product prototypes. Using the MMVP system, two biomedical objects, including a DMM human spine and an FGM intervertebral disc spacer are modelled and digitally fabricated for visualization and analysis in a VR environment. These studies show that the MMVP system is a practical tool for modelling, visualization, and subsequent fabrication of biomedical objects of discrete and functionally graded multi-materials for biomedical applications. The system may be adapted to control MMLM machines with appropriate hardware for physical fabrication of biomedical objects.

Expeditious illustration of layer-cake models on and above a tactile surface

NASA Astrophysics Data System (ADS)

Lopes, Daniel Simões; Mendes, Daniel; Sousa, Maurício; Jorge, Joaquim

2016-05-01

Too often illustrating and visualizing 3D geological concepts are performed by sketching in 2D mediums, which may limit drawing performance of initial concepts. Here, the potential of expeditious geological modeling brought by hand gestures is explored. A spatial interaction system was developed to enable rapid modeling, editing, and exploration of 3D layer-cake objects. User interactions are acquired with motion capture and touch screen technologies. Virtual immersion is guaranteed by using stereoscopic technology. The novelty consists of performing expeditious modeling of coarse geological features with only a limited set of hand gestures. Results from usability-studies show that the proposed system is more efficient when compared to a windows-icon-menu-pointer modeling application.

To speak or not to speak - A multiple resource perspective

NASA Technical Reports Server (NTRS)

Tsang, P. S.; Hartzell, E. J.; Rothschild, R. A.

1985-01-01

The desirability of employing speech response in a dynamic dual task situation was discussed from a multiple resource perspective. A secondary task technique was employed to examine the time-sharing performance of five dual tasks with various degrees of resource overlap according to the structure-specific resource model of Wickens (1980). The primary task was a visual/manual tracking task which required spatial processing. The secondary task was either another tracking task or a spatial transformation task with one of four input (visual or auditory) and output (manual or speech) configurations. The results show that the dual task performance was best when the primary tracking task was paired with the visual/speech transformation task. This finding was explained by an interaction of the stimulus-central processing-response compatibility of the transformation task and the degree of resource competition between the time-shared tasks. Implications on the utility of speech response were discussed.

Complex scenes and situations visualization in hierarchical learning algorithm with dynamic 3D NeoAxis engine

NASA Astrophysics Data System (ADS)

Graham, James; Ternovskiy, Igor V.

2013-06-01

We applied a two stage unsupervised hierarchical learning system to model complex dynamic surveillance and cyber space monitoring systems using a non-commercial version of the NeoAxis visualization software. The hierarchical scene learning and recognition approach is based on hierarchical expectation maximization, and was linked to a 3D graphics engine for validation of learning and classification results and understanding the human - autonomous system relationship. Scene recognition is performed by taking synthetically generated data and feeding it to a dynamic logic algorithm. The algorithm performs hierarchical recognition of the scene by first examining the features of the objects to determine which objects are present, and then determines the scene based on the objects present. This paper presents a framework within which low level data linked to higher-level visualization can provide support to a human operator and be evaluated in a detailed and systematic way.

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks

PubMed Central

Ruiz-Rizzo, Adriana L.; Neitzel, Julia; Müller, Hermann J.; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's “theory of visual attention” (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity. PMID:29662444

Distinctive Correspondence Between Separable Visual Attention Functions and Intrinsic Brain Networks.

PubMed

Ruiz-Rizzo, Adriana L; Neitzel, Julia; Müller, Hermann J; Sorg, Christian; Finke, Kathrin

2018-01-01

Separable visual attention functions are assumed to rely on distinct but interacting neural mechanisms. Bundesen's "theory of visual attention" (TVA) allows the mathematical estimation of independent parameters that characterize individuals' visual attentional capacity (i.e., visual processing speed and visual short-term memory storage capacity) and selectivity functions (i.e., top-down control and spatial laterality). However, it is unclear whether these parameters distinctively map onto different brain networks obtained from intrinsic functional connectivity, which organizes slowly fluctuating ongoing brain activity. In our study, 31 demographically homogeneous healthy young participants performed whole- and partial-report tasks and underwent resting-state functional magnetic resonance imaging (rs-fMRI). Report accuracy was modeled using TVA to estimate, individually, the four TVA parameters. Networks encompassing cortical areas relevant for visual attention were derived from independent component analysis of rs-fMRI data: visual, executive control, right and left frontoparietal, and ventral and dorsal attention networks. Two TVA parameters were mapped on particular functional networks. First, participants with higher (vs. lower) visual processing speed showed lower functional connectivity within the ventral attention network. Second, participants with more (vs. less) efficient top-down control showed higher functional connectivity within the dorsal attention network and lower functional connectivity within the visual network. Additionally, higher performance was associated with higher functional connectivity between networks: specifically, between the ventral attention and right frontoparietal networks for visual processing speed, and between the visual and executive control networks for top-down control. The higher inter-network functional connectivity was related to lower intra-network connectivity. These results demonstrate that separable visual attention parameters that are assumed to constitute relatively stable traits correspond distinctly to the functional connectivity both within and between particular functional networks. This implies that individual differences in basic attention functions are represented by differences in the coherence of slowly fluctuating brain activity.

Water surface modeling from a single viewpoint video.

PubMed

Li, Chuan; Pickup, David; Saunders, Thomas; Cosker, Darren; Marshall, David; Hall, Peter; Willis, Philip

2013-07-01

We introduce a video-based approach for producing water surface models. Recent advances in this field output high-quality results but require dedicated capturing devices and only work in limited conditions. In contrast, our method achieves a good tradeoff between the visual quality and the production cost: It automatically produces a visually plausible animation using a single viewpoint video as the input. Our approach is based on two discoveries: first, shape from shading (SFS) is adequate to capture the appearance and dynamic behavior of the example water; second, shallow water model can be used to estimate a velocity field that produces complex surface dynamics. We will provide qualitative evaluation of our method and demonstrate its good performance across a wide range of scenes.

A physiologically-based model for simulation of color vision deficiency.

PubMed

Machado, Gustavo M; Oliveira, Manuel M; Fernandes, Leandro A F

2009-01-01

Color vision deficiency (CVD) affects approximately 200 million people worldwide, compromising the ability of these individuals to effectively perform color and visualization-related tasks. This has a significant impact on their private and professional lives. We present a physiologically-based model for simulating color vision. Our model is based on the stage theory of human color vision and is derived from data reported in electrophysiological studies. It is the first model to consistently handle normal color vision, anomalous trichromacy, and dichromacy in a unified way. We have validated the proposed model through an experimental evaluation involving groups of color vision deficient individuals and normal color vision ones. Our model can provide insights and feedback on how to improve visualization experiences for individuals with CVD. It also provides a framework for testing hypotheses about some aspects of the retinal photoreceptors in color vision deficient individuals.

Evaluating Nextgen Closely Spaced Parallel Operations Concepts with Validated Human Performance Models: Flight Deck Guidelines

NASA Technical Reports Server (NTRS)

Hooey, Becky Lee; Gore, Brian Francis; Mahlstedt, Eric; Foyle, David C.

2013-01-01

The objectives of the current research were to develop valid human performance models (HPMs) of approach and land operations; use these models to evaluate the impact of NextGen Closely Spaced Parallel Operations (CSPO) on pilot performance; and draw conclusions regarding flight deck display design and pilot-ATC roles and responsibilities for NextGen CSPO concepts. This document presents guidelines and implications for flight deck display designs and candidate roles and responsibilities. A companion document (Gore, Hooey, Mahlstedt, & Foyle, 2013) provides complete scenario descriptions and results including predictions of pilot workload, visual attention and time to detect off-nominal events.

Ionospheric Simulation System for Satellite Observations and Global Assimilative Modeling Experiments (ISOGAME)

NASA Technical Reports Server (NTRS)

Pi, Xiaoqing; Mannucci, Anthony J.; Verkhoglyadova, Olga P.; Stephens, Philip; Wilson, Brian D.; Akopian, Vardan; Komjathy, Attila; Lijima, Byron A.

2013-01-01

ISOGAME is designed and developed to assess quantitatively the impact of new observation systems on the capability of imaging and modeling the ionosphere. With ISOGAME, one can perform observation system simulation experiments (OSSEs). A typical OSSE using ISOGAME would involve: (1) simulating various ionospheric conditions on global scales; (2) simulating ionospheric measurements made from a constellation of low-Earth-orbiters (LEOs), particularly Global Navigation Satellite System (GNSS) radio occultation data, and from ground-based global GNSS networks; (3) conducting ionospheric data assimilation experiments with the Global Assimilative Ionospheric Model (GAIM); and (4) analyzing modeling results with visualization tools. ISOGAME can provide quantitative assessment of the accuracy of assimilative modeling with the interested observation system. Other observation systems besides those based on GNSS are also possible to analyze. The system is composed of a suite of software that combines the GAIM, including a 4D first-principles ionospheric model and data assimilation modules, an Internal Reference Ionosphere (IRI) model that has been developed by international ionospheric research communities, observation simulator, visualization software, and orbit design, simulation, and optimization software. The core GAIM model used in ISOGAME is based on the GAIM++ code (written in C++) that includes a new high-fidelity geomagnetic field representation (multi-dipole). New visualization tools and analysis algorithms for the OSSEs are now part of ISOGAME.

Poorer Visual Acuity Is Associated with Declines in Cognitive Performance Across Multiple Cognitive Domains: The Maine-Syracuse Longitudinal Study.

PubMed

Dearborn, Peter J; Elias, Merrill F; Sullivan, Kevin J; Sullivan, Cara E; Robbins, Michael A

2018-06-21

Prior studies have found associations between visual acuity (VA) and cognitive function. However, these studies used a limited range of cognitive measures and did not control for cardiovascular disease risk factors (CVD-RFs) and baseline function. The primary objective of this study was to analyze the associations of VA and cognitive performance using a thorough neuropsychological test battery. This study used community-dwelling sample data across the sixth (2001-2006) and seventh (2006-2010) waves of the Maine-Syracuse Longitudinal Study (n=655). Wave 6 VA as measured by the Snellen Eye Test was the primary predictor of wave 6 and wave 7 Global cognitive performance, Visual-Spatial Organization and Memory, Verbal Episodic Memory, Working Memory, Scanning and Tracking, and Executive Function. Additionally, VA was used to predict longitudinal changes in wave 7 cognitive performance (wave 6 performance adjusted). We analyzed these relationships with multiple linear and logistic regression models adjusted for age, sex, education, ethnicity, depressive symptoms, physical function deficits in addition to CVD-RFs, chronic kidney disease, homocysteine, continuous systolic blood pressure, and hypertension status. Adjusted for demographic covariates and CVD-RFs, poorer VA was associated with concurrent and approximate 5-year declines in Global cognitive function, Visual-Spatial Organization and Memory, and Verbal Episodic Memory. VA may be used in combination with other screening measures to determine risk for cognitive decline. (JINS, 2018, 24, 1-9).

Visual Working Memory Capacity Can Be Increased by Training on Distractor Filtering Efficiency.

PubMed

Li, Cui-Hong; He, Xu; Wang, Yu-Juan; Hu, Zhe; Guo, Chun-Yan

2017-01-01

It is generally considered that working memory (WM) capacity is limited and that WM capacity affects cognitive processes. Distractor filtering efficiency has been suggested to be an important factor in determining the visual working memory (VWM) capacity of individuals. In the present study, we investigated whether training in visual filtering efficiency (FE) could improve VWM capacity, as measured by performance on the change detection task (CDT) and changes of contralateral delay activity (CDA) (contralateral delay activity) of different conditions, and evaluated the transfer effect of visual FE training on verbal WM and fluid intelligence, as indexed by performance on the verbal WM span task and Raven's Standard Progressive Matrices (RSPM) test, respectively. Participants were divided into high- and low-capacity groups based on their performance in a CDT designed to test VWM capacity, and then the low-capacity individuals received 20 days of FE training. The training significantly improved the group's performance in the CDT, and their CDA models of different conditions became more similar with high capacity group, and the effect generalized to improve verbal WM span. These gains were maintained at a 3-month follow-up test. Participants' RSPM scores were not changed by the training. These findings support the notion that WM capacity is determined, at least in part, by distractor FE and can be enhanced through training.

Evaluation of perception performance in neck dissection planning using eye tracking and attention landscapes

NASA Astrophysics Data System (ADS)

Burgert, Oliver; Örn, Veronika; Velichkovsky, Boris M.; Gessat, Michael; Joos, Markus; Strauß, Gero; Tietjen, Christian; Preim, Bernhard; Hertel, Ilka

2007-03-01

Neck dissection is a surgical intervention at which cervical lymph node metastases are removed. Accurate surgical planning is of high importance because wrong judgment of the situation causes severe harm for the patient. Diagnostic perception of radiological images by a surgeon is an acquired skill that can be enhanced by training and experience. To improve accuracy in detecting pathological lymph nodes by newcomers and less experienced professionals, it is essential to understand how surgical experts solve relevant visual and recognition tasks. By using eye tracking and especially the newly-developed attention landscapes visualizations, it could be determined whether visualization options, for example 3D models instead of CT data, help in increasing accuracy and speed of neck dissection planning. Thirteen ORL surgeons with different levels of expertise participated in this study. They inspected different visualizations of 3D models and original CT datasets of patients. Among others, we used scanpath analysis and attention landscapes to interpret the inspection strategies. It was possible to distinguish different patterns of visual exploratory activity. The experienced surgeons exhibited a higher concentration of attention on the limited number of areas of interest and demonstrated less saccadic eye movements indicating a better orientation.

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

DOE Office of Scientific and Technical Information (OSTI.GOV)

William J. Schroeder

2011-11-13

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannotmore » be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally-intensive problem important to the nations scientific progress as described shortly. Further, SLAC researchers routinely generate massive amounts of data, and frequently collaborate with other researchers located around the world. Thus SLAC is an ideal teammate through which to develop, test and deploy this technology. The nature of the datasets generated by simulations performed at SLAC presented unique visualization challenges especially when dealing with higher-order elements that were addressed during this Phase II. During this Phase II, we have developed a strong platform for collaborative visualization based on ParaView. We have developed and deployed a ParaView Web Visualization framework that can be used for effective collaboration over the Web. Collaborating and visualizing over the Web presents the community with unique opportunities for sharing and accessing visualization and HPC resources that hitherto with either inaccessible or difficult to use. The technology we developed in here will alleviate both these issues as it becomes widely deployed and adopted.« less

Using Modeling and Simulation to Predict Operator Performance and Automation-Induced Complacency With Robotic Automation: A Case Study and Empirical Validation.

PubMed

Wickens, Christopher D; Sebok, Angelia; Li, Huiyang; Sarter, Nadine; Gacy, Andrew M

2015-09-01

The aim of this study was to develop and validate a computational model of the automation complacency effect, as operators work on a robotic arm task, supported by three different degrees of automation. Some computational models of complacency in human-automation interaction exist, but those are formed and validated within the context of fairly simplified monitoring failures. This research extends model validation to a much more complex task, so that system designers can establish, without need for human-in-the-loop (HITL) experimentation, merits and shortcomings of different automation degrees. We developed a realistic simulation of a space-based robotic arm task that could be carried out with three different levels of trajectory visualization and execution automation support. Using this simulation, we performed HITL testing. Complacency was induced via several trials of correctly performing automation and then was assessed on trials when automation failed. Following a cognitive task analysis of the robotic arm operation, we developed a multicomponent model of the robotic operator and his or her reliance on automation, based in part on visual scanning. The comparison of model predictions with empirical results revealed that the model accurately predicted routine performance and predicted the responses to these failures after complacency developed. However, the scanning models do not account for the entire attention allocation effects of complacency. Complacency modeling can provide a useful tool for predicting the effects of different types of imperfect automation. The results from this research suggest that focus should be given to supporting situation awareness in automation development. © 2015, Human Factors and Ergonomics Society.

Gestalt Effects in Visual Working Memory.

PubMed

Kałamała, Patrycja; Sadowska, Aleksandra; Ordziniak, Wawrzyniec; Chuderski, Adam

2017-01-01

Four experiments investigated whether conforming to Gestalt principles, well known to drive visual perception, also facilitates the active maintenance of information in visual working memory (VWM). We used the change detection task, which required the memorization of visual patterns composed of several shapes. We observed no effects of symmetry of visual patterns on VWM performance. However, there was a moderate positive effect when a particular shape that was probed matched the shape of the whole pattern (the whole-part similarity effect). Data support the models assuming that VWM encodes not only particular objects of the perceptual scene but also the spatial relations between them (the ensemble representation). The ensemble representation may prime objects similar to its shape and thereby boost access to them. In contrast, the null effect of symmetry relates the fact that this very feature of an ensemble does not yield any useful additional information for VWM.

Hierarchical representation of shapes in visual cortex—from localized features to figural shape segregation

PubMed Central

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1–V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy. PMID:25157228

Hierarchical representation of shapes in visual cortex-from localized features to figural shape segregation.

PubMed

Tschechne, Stephan; Neumann, Heiko

2014-01-01

Visual structures in the environment are segmented into image regions and those combined to a representation of surfaces and prototypical objects. Such a perceptual organization is performed by complex neural mechanisms in the visual cortex of primates. Multiple mutually connected areas in the ventral cortical pathway receive visual input and extract local form features that are subsequently grouped into increasingly complex, more meaningful image elements. Such a distributed network of processing must be capable to make accessible highly articulated changes in shape boundary as well as very subtle curvature changes that contribute to the perception of an object. We propose a recurrent computational network architecture that utilizes hierarchical distributed representations of shape features to encode surface and object boundary over different scales of resolution. Our model makes use of neural mechanisms that model the processing capabilities of early and intermediate stages in visual cortex, namely areas V1-V4 and IT. We suggest that multiple specialized component representations interact by feedforward hierarchical processing that is combined with feedback signals driven by representations generated at higher stages. Based on this, global configurational as well as local information is made available to distinguish changes in the object's contour. Once the outline of a shape has been established, contextual contour configurations are used to assign border ownership directions and thus achieve segregation of figure and ground. The model, thus, proposes how separate mechanisms contribute to distributed hierarchical cortical shape representation and combine with processes of figure-ground segregation. Our model is probed with a selection of stimuli to illustrate processing results at different processing stages. We especially highlight how modulatory feedback connections contribute to the processing of visual input at various stages in the processing hierarchy.

Peripheral Processing Facilitates Optic Flow-Based Depth Perception

PubMed Central

Li, Jinglin; Lindemann, Jens P.; Egelhaaf, Martin

2016-01-01

Flying insects, such as flies or bees, rely on consistent information regarding the depth structure of the environment when performing their flight maneuvers in cluttered natural environments. These behaviors include avoiding collisions, approaching targets or spatial navigation. Insects are thought to obtain depth information visually from the retinal image displacements (“optic flow”) during translational ego-motion. Optic flow in the insect visual system is processed by a mechanism that can be modeled by correlation-type elementary motion detectors (EMDs). However, it is still an open question how spatial information can be extracted reliably from the responses of the highly contrast- and pattern-dependent EMD responses, especially if the vast range of light intensities encountered in natural environments is taken into account. This question will be addressed here by systematically modeling the peripheral visual system of flies, including various adaptive mechanisms. Different model variants of the peripheral visual system were stimulated with image sequences that mimic the panoramic visual input during translational ego-motion in various natural environments, and the resulting peripheral signals were fed into an array of EMDs. We characterized the influence of each peripheral computational unit on the representation of spatial information in the EMD responses. Our model simulations reveal that information about the overall light level needs to be eliminated from the EMD input as is accomplished under light-adapted conditions in the insect peripheral visual system. The response characteristics of large monopolar cells (LMCs) resemble that of a band-pass filter, which reduces the contrast dependency of EMDs strongly, effectively enhancing the representation of the nearness of objects and, especially, of their contours. We furthermore show that local brightness adaptation of photoreceptors allows for spatial vision under a wide range of dynamic light conditions. PMID:27818631

Visual Search Performance in Patients with Vision Impairment: A Systematic Review.

PubMed

Senger, Cassia; Margarido, Maria Rita Rodrigues Alves; De Moraes, Carlos Gustavo; De Fendi, Ligia Issa; Messias, André; Paula, Jayter Silva

2017-11-01

Patients with visual impairment are constantly facing challenges to achieve an independent and productive life, which depends upon both a good visual discrimination and search capacities. Given that visual search is a critical skill for several daily tasks and could be used as an index of the overall visual function, we investigated the relationship between vision impairment and visual search performance. A comprehensive search was undertaken using electronic PubMed, EMBASE, LILACS, and Cochrane databases from January 1980 to December 2016, applying the following terms: "visual search", "visual search performance", "visual impairment", "visual exploration", "visual field", "hemianopia", "search time", "vision lost", "visual loss", and "low vision". Two hundred seventy six studies from 12,059 electronic database files were selected, and 40 of them were included in this review. Studies included participants of all ages, both sexes, and the sample sizes ranged from 5 to 199 participants. Visual impairment was associated with worse visual search performance in several ophthalmologic conditions, which were either artificially induced, or related to specific eye and neurological diseases. This systematic review details all the described circumstances interfering with visual search tasks, highlights the need for developing technical standards, and outlines patterns for diagnosis and therapy using visual search capabilities.

Evolution of new reflective materials for overhead highway signage

DOT National Transportation Integrated Search

2008-07-01

Unlighted highway signs using newly developed retroreflective materials were installed along the Gowanus Expressway. Photometric measurements of the signs were used to assess the visibility of the signs using the relative visual performance model. Th...

Factors influencing visual search in complex driving environments.

DOT National Transportation Integrated Search

2016-10-01

The objective of this study was to describe and model the effects of varied roadway environment factors on drivers perceived complexity, with the goal of further understanding conditions for optimal driver behavior and performance. This was invest...

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

PubMed

Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

2015-09-30

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

The Classroom Check-up: A Classwide Teacher Consultation Model for Increasing Praise and Decreasing Disruptive Behavior

PubMed Central

Reinke, Wendy M.; Lewis-Palmer, Teri; Merrell, Kenneth

2008-01-01

School-based consultation typically focuses on individual student problems and on a small number of students rather than on changing the classroom system. The Classroom Check-up (CCU) was developed as a classwide consultation model to address the need for classroom level support while minimizing treatment integrity problems common to school-based consultation. The purpose of the study was to evaluate the effects of the CCU and Visual Performance Feedback on teacher and student behavior. Results indicated that implementation of the CCU plus Visual Performance Feedback increased teacher implementation of classroom management strategies, including increased use of praise, use of behavior specific praise, and decreased use of reprimands. Further, these changes in teacher behavior contributed to decreases in classroom disruptive behavior. The results are encouraging because they suggest that consultation at the classroom level can create meaningful teacher and student behavior change. PMID:19122805

Early Experiences Porting the NAMD and VMD Molecular Simulation and Analysis Software to GPU-Accelerated OpenPOWER Platforms

PubMed Central

Stone, John E.; Hynninen, Antti-Pekka; Phillips, James C.; Schulten, Klaus

2017-01-01

All-atom molecular dynamics simulations of biomolecules provide a powerful tool for exploring the structure and dynamics of large protein complexes within realistic cellular environments. Unfortunately, such simulations are extremely demanding in terms of their computational requirements, and they present many challenges in terms of preparation, simulation methodology, and analysis and visualization of results. We describe our early experiences porting the popular molecular dynamics simulation program NAMD and the simulation preparation, analysis, and visualization tool VMD to GPU-accelerated OpenPOWER hardware platforms. We report our experiences with compiler-provided autovectorization and compare with hand-coded vector intrinsics for the POWER8 CPU. We explore the performance benefits obtained from unique POWER8 architectural features such as 8-way SMT and its value for particular molecular modeling tasks. Finally, we evaluate the performance of several GPU-accelerated molecular modeling kernels and relate them to other hardware platforms. PMID:29202130

Human Factors Assessment of Vibration Effects on Visual Performance During Launch

NASA Technical Reports Server (NTRS)

Holden, Kritina

2009-01-01

The Human Factors Assessment of Vibration Effects on Visual Performance During Launch (Visual Performance) investigation will determine visual performance limits during operational vibration and g-loads on the Space Shuttle, specifically through the determination of minimum readable font size during ascent using planned Orion display formats. Research Summary: The aim of the Human Factors Assessment of Vibration Effects on Visual Performance during Launch (Visual Performance) investigation is to provide supplementary data to that collected by the Thrust Oscillation Seat Detailed Technical Objective (DTO) 695 (Crew Seat DTO) which will measure seat acceleration and vibration from one flight deck and two middeck seats during ascent. While the Crew Seat DTO data alone are important in terms of providing a measure of vibration and g-loading, human performance data are required to fully interpret the operational consequences of the vibration values collected during Space Shuttle ascent. During launch, crewmembers will be requested to view placards with varying font sizes and indicate the minimum readable size. In combination with the Crew Seat DTO, the Visual Performance investigation will: Provide flight-validated evidence that will be used to establish vibration limits for visual performance during combined vibration and linear g-loading. o Provide flight data as inputs to ongoing ground-based simulations, which will further validate crew visual performance under vibration loading in a controlled environment. o Provide vibration and performance metrics to help validate procedures for ground tests and analyses of seats, suits, displays and controls, and human-in-the-loop performance.

Celeris: A GPU-accelerated open source software with a Boussinesq-type wave solver for real-time interactive simulation and visualization

NASA Astrophysics Data System (ADS)

Tavakkol, Sasan; Lynett, Patrick

2017-08-01

In this paper, we introduce an interactive coastal wave simulation and visualization software, called Celeris. Celeris is an open source software which needs minimum preparation to run on a Windows machine. The software solves the extended Boussinesq equations using a hybrid finite volume-finite difference method and supports moving shoreline boundaries. The simulation and visualization are performed on the GPU using Direct3D libraries, which enables the software to run faster than real-time. Celeris provides a first-of-its-kind interactive modeling platform for coastal wave applications and it supports simultaneous visualization with both photorealistic and colormapped rendering capabilities. We validate our software through comparison with three standard benchmarks for non-breaking and breaking waves.

Oculometric Assessment of Dynamic Visual Processing

NASA Technical Reports Server (NTRS)

Liston, Dorion Bryce; Stone, Lee

2014-01-01

Eye movements are the most frequent (3 per second), shortest-latency (150-250 ms), and biomechanically simplest (1 joint, no inertial complexities) voluntary motor behavior in primates, providing a model system to assess sensorimotor disturbances arising from trauma, fatigue, aging, or disease states (e.g., Diefendorf and Dodge, 1908). We developed a 15-minute behavioral tracking protocol consisting of randomized stepramp radial target motion to assess several aspects of the behavioral response to dynamic visual motion, including pursuit initiation, steadystate tracking, direction-tuning, and speed-tuning thresholds. This set of oculomotor metrics provide valid and reliable measures of dynamic visual performance (Stone and Krauzlis, 2003; Krukowski and Stone, 2005; Stone et al, 2009; Liston and Stone, 2014), and may prove to be a useful assessment tool for functional impairments of dynamic visual processing.

Aminergic neuromodulation of associative visual learning in harnessed honey bees.

PubMed

Mancini, Nino; Giurfa, Martin; Sandoz, Jean-Christophe; Avarguès-Weber, Aurore

2018-05-21

The honey bee Apis mellifera is a major insect model for studying visual cognition. Free-flying honey bees learn to associate different visual cues with a sucrose reward and may deploy sophisticated cognitive strategies to this end. Yet, the neural bases of these capacities cannot be studied in flying insects. Conversely, immobilized bees are accessible to neurobiological investigation but training them to respond appetitively to visual stimuli paired with sucrose reward is difficult. Here we succeeded in coupling visual conditioning in harnessed bees with pharmacological analyses on the role of octopamine (OA), dopamine (DA) and serotonin (5-HT) in visual learning. We also studied if and how these biogenic amines modulate sucrose responsiveness and phototaxis behaviour as intact reward and visual perception are essential prerequisites for appetitive visual learning. Our results suggest that both octopaminergic and dopaminergic signaling mediate either the appetitive sucrose signaling or the association between color and sucrose reward in the bee brain. Enhancing and inhibiting serotonergic signaling both compromised learning performances, probably via an impairment of visual perception. We thus provide a first analysis of the role of aminergic signaling in visual learning and retention in the honey bee and discuss further research trends necessary to understand the neural bases of visual cognition in this insect. Copyright © 2018 Elsevier Inc. All rights reserved.

Visual determinants of reduced performance on the Stroop color-word test in normal aging individuals.

PubMed

van Boxtel, M P; ten Tusscher, M P; Metsemakers, J F; Willems, B; Jolles, J

2001-10-01

It is unknown to what extent the performance on the Stroop color-word test is affected by reduced visual function in older individuals. We tested the impact of common deficiencies in visual function (reduced distant and close acuity, reduced contrast sensitivity, and color weakness) on Stroop performance among 821 normal individuals aged 53 and older. After adjustment for age, sex, and educational level, low contrast sensitivity was associated with more time needed on card I (word naming), red/green color weakness with slower card 2 performance (color naming), and reduced distant acuity with slower performance on card 3 (interference). Half of the age-related variance in speed performance was shared with visual function. The actual impact of reduced visual function may be underestimated in this study when some of this age-related variance in Stroop performance is mediated by visual function decrements. It is suggested that reduced visual function has differential effects on Stroop performance which need to be accounted for when the Stroop test is used both in research and in clinical settings. Stroop performance measured from older individuals with unknown visual status should be interpreted with caution.

Visual tracking using neuromorphic asynchronous event-based cameras.

PubMed

Ni, Zhenjiang; Ieng, Sio-Hoi; Posch, Christoph; Régnier, Stéphane; Benosman, Ryad

2015-04-01

This letter presents a novel computationally efficient and robust pattern tracking method based on a time-encoded, frame-free visual data. Recent interdisciplinary developments, combining inputs from engineering and biology, have yielded a novel type of camera that encodes visual information into a continuous stream of asynchronous, temporal events. These events encode temporal contrast and intensity locally in space and time. We show that the sparse yet accurately timed information is well suited as a computational input for object tracking. In this letter, visual data processing is performed for each incoming event at the time it arrives. The method provides a continuous and iterative estimation of the geometric transformation between the model and the events representing the tracked object. It can handle isometry, similarities, and affine distortions and allows for unprecedented real-time performance at equivalent frame rates in the kilohertz range on a standard PC. Furthermore, by using the dimension of time that is currently underexploited by most artificial vision systems, the method we present is able to solve ambiguous cases of object occlusions that classical frame-based techniques handle poorly.

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Analytical Judgment Using Visualizations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

Scientists working in a particular domain often adhere to conventional data analysis and presentation methods and this leads to familiarity with these methods over time. But does high familiarity always lead to better analytical judgment? This question is especially relevant when visualizations are used in scientific tasks, as there can be discrepancies between visualization best practices and domain conventions. However, there is little empirical evidence of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their effect on scientific judgment. To address this gap and to study these factors, we focus on the climatemore » science domain, specifically on visualizations used for comparison of model performance. We present a comprehensive user study with 47 climate scientists where we explored the following factors: i) relationships between scientists’ familiarity, their perceived levels of com- fort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

Visual processing speed in old age.

PubMed

Habekost, Thomas; Vogel, Asmus; Rostrup, Egill; Bundesen, Claus; Kyllingsbaek, Søren; Garde, Ellen; Ryberg, Charlotte; Waldemar, Gunhild

2013-04-01

Mental speed is a common concept in theories of cognitive aging, but it is difficult to get measures of the speed of a particular psychological process that are not confounded by the speed of other processes. We used Bundesen's (1990) Theory of Visual Attention (TVA) to obtain specific estimates of processing speed in the visual system controlled for the influence of response latency and individual variations of the perception threshold. A total of 33 non-demented old people (69-87 years) were tested for the ability to recognize briefly presented letters. Performance was analyzed by the TVA model. Visual processing speed decreased approximately linearly with age and was on average halved from 70 to 85 years. Less dramatic aging effects were found for the perception threshold and the visual apprehension span. In the visual domain, cognitive aging seems to be most clearly related to reductions in processing speed. © 2012 The Authors. Scandinavian Journal of Psychology © 2012 The Scandinavian Psychological Associations.

Empirical Analysis of the Subjective Impressions and Objective Measures of Domain Scientists’ Visual Analytic Judgments

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dasgupta, Aritra; Burrows, Susannah M.; Han, Kyungsik

2017-05-08

Scientists often use specific data analysis and presentation methods familiar within their domain. But does high familiarity drive better analytical judgment? This question is especially relevant when familiar methods themselves can have shortcomings: many visualizations used conventionally for scientific data analysis and presentation do not follow established best practices. This necessitates new methods that might be unfamiliar yet prove to be more effective. But there is little empirical understanding of the relationships between scientists’ subjective impressions about familiar and unfamiliar visualizations and objective measures of their visual analytic judgments. To address this gap and to study these factors, we focusmore » on visualizations used for comparison of climate model performance. We report on a comprehensive survey-based user study with 47 climate scientists and present an analysis of : i) relationships among scientists’ familiarity, their perceived lev- els of comfort, confidence, accuracy, and objective measures of accuracy, and ii) relationships among domain experience, visualization familiarity, and post-study preference.« less

A Microsaccadic Account of Attentional Capture and Inhibition of Return in Posner Cueing

PubMed Central

Tian, Xiaoguang; Yoshida, Masatoshi; Hafed, Ziad M.

2016-01-01

Microsaccades exhibit systematic oscillations in direction after spatial cueing, and these oscillations correlate with facilitatory and inhibitory changes in behavioral performance in the same tasks. However, independent of cueing, facilitatory and inhibitory changes in visual sensitivity also arise pre-microsaccadically. Given such pre-microsaccadic modulation, an imperative question to ask becomes: how much of task performance in spatial cueing may be attributable to these peri-movement changes in visual sensitivity? To investigate this question, we adopted a theoretical approach. We developed a minimalist model in which: (1) microsaccades are repetitively generated using a rise-to-threshold mechanism, and (2) pre-microsaccadic target onset is associated with direction-dependent modulation of visual sensitivity, as found experimentally. We asked whether such a model alone is sufficient to account for performance dynamics in spatial cueing. Our model not only explained fine-scale microsaccade frequency and direction modulations after spatial cueing, but it also generated classic facilitatory (i.e., attentional capture) and inhibitory [i.e., inhibition of return (IOR)] effects of the cue on behavioral performance. According to the model, cues reflexively reset the oculomotor system, which unmasks oscillatory processes underlying microsaccade generation; once these oscillatory processes are unmasked, “attentional capture” and “IOR” become direct outcomes of pre-microsaccadic enhancement or suppression, respectively. Interestingly, our model predicted that facilitatory and inhibitory effects on behavior should appear as a function of target onset relative to microsaccades even without prior cues. We experimentally validated this prediction for both saccadic and manual responses. We also established a potential causal mechanism for the microsaccadic oscillatory processes hypothesized by our model. We used retinal-image stabilization to experimentally control instantaneous foveal motor error during the presentation of peripheral cues, and we found that post-cue microsaccadic oscillations were severely disrupted. This suggests that microsaccades in spatial cueing tasks reflect active oculomotor correction of foveal motor error, rather than presumed oscillatory covert attentional processes. Taken together, our results demonstrate that peri-microsaccadic changes in vision can go a long way in accounting for some classic behavioral phenomena. PMID:27013991

A Vision-Based Self-Calibration Method for Robotic Visual Inspection Systems

PubMed Central

Yin, Shibin; Ren, Yongjie; Zhu, Jigui; Yang, Shourui; Ye, Shenghua

2013-01-01

A vision-based robot self-calibration method is proposed in this paper to evaluate the kinematic parameter errors of a robot using a visual sensor mounted on its end-effector. This approach could be performed in the industrial field without external, expensive apparatus or an elaborate setup. A robot Tool Center Point (TCP) is defined in the structural model of a line-structured laser sensor, and aligned to a reference point fixed in the robot workspace. A mathematical model is established to formulate the misalignment errors with kinematic parameter errors and TCP position errors. Based on the fixed point constraints, the kinematic parameter errors and TCP position errors are identified with an iterative algorithm. Compared to the conventional methods, this proposed method eliminates the need for a robot-based-frame and hand-to-eye calibrations, shortens the error propagation chain, and makes the calibration process more accurate and convenient. A validation experiment is performed on an ABB IRB2400 robot. An optimal configuration on the number and distribution of fixed points in the robot workspace is obtained based on the experimental results. Comparative experiments reveal that there is a significant improvement of the measuring accuracy of the robotic visual inspection system. PMID:24300597

Visual abilities distinguish pitchers from hitters in professional baseball.

PubMed

Klemish, David; Ramger, Benjamin; Vittetoe, Kelly; Reiter, Jerome P; Tokdar, Surya T; Appelbaum, Lawrence Gregory

2018-01-01

This study aimed to evaluate the possibility that differences in sensorimotor abilities exist between hitters and pitchers in a large cohort of baseball players of varying levels of experience. Secondary data analysis was performed on 9 sensorimotor tasks comprising the Nike Sensory Station assessment battery. Bayesian hierarchical regression modelling was applied to test for differences between pitchers and hitters in data from 566 baseball players (112 high school, 85 college, 369 professional) collected at 20 testing centres. Explanatory variables including height, handedness, eye dominance, concussion history, and player position were modelled along with age curves using basis regression splines. Regression analyses revealed better performance for hitters relative to pitchers at the professional level in the visual clarity and depth perception tasks, but these differences did not exist at the high school or college levels. No significant differences were observed in the other 7 measures of sensorimotor capabilities included in the test battery, and no systematic biases were found between the testing centres. These findings, indicating that professional-level hitters have better visual acuity and depth perception than professional-level pitchers, affirm the notion that highly experienced athletes have differing perceptual skills. Findings are discussed in relation to deliberate practice theory.

A neurally plausible parallel distributed processing model of event-related potential word reading data.

PubMed

Laszlo, Sarah; Plaut, David C

2012-03-01

The Parallel Distributed Processing (PDP) framework has significant potential for producing models of cognitive tasks that approximate how the brain performs the same tasks. To date, however, there has been relatively little contact between PDP modeling and data from cognitive neuroscience. In an attempt to advance the relationship between explicit, computational models and physiological data collected during the performance of cognitive tasks, we developed a PDP model of visual word recognition which simulates key results from the ERP reading literature, while simultaneously being able to successfully perform lexical decision-a benchmark task for reading models. Simulations reveal that the model's success depends on the implementation of several neurally plausible features in its architecture which are sufficiently domain-general to be relevant to cognitive modeling more generally. Copyright © 2011 Elsevier Inc. All rights reserved.

Comparing masked target transform volume (MTTV) clutter metric to human observer evaluation of visual clutter

NASA Astrophysics Data System (ADS)

Camp, H. A.; Moyer, Steven; Moore, Richard K.

2010-04-01

The Night Vision and Electronic Sensors Directorate's current time-limited search (TLS) model, which makes use of the targeting task performance (TTP) metric to describe image quality, does not explicitly account for the effects of visual clutter on observer performance. The TLS model is currently based on empirical fits to describe human performance for a time of day, spectrum and environment. Incorporating a clutter metric into the TLS model may reduce the number of these empirical fits needed. The masked target transform volume (MTTV) clutter metric has been previously presented and compared to other clutter metrics. Using real infrared imagery of rural images with varying levels of clutter, NVESD is currently evaluating the appropriateness of the MTTV metric. NVESD had twenty subject matter experts (SME) rank the amount of clutter in each scene in a series of pair-wise comparisons. MTTV metric values were calculated and then compared to the SME observers rankings. The MTTV metric ranked the clutter in a similar manner to the SME evaluation, suggesting that the MTTV metric may emulate SME response. This paper is a first step in quantifying clutter and measuring the agreement to subjective human evaluation.

Auditory Working Memory Load Impairs Visual Ventral Stream Processing: Toward a Unified Model of Attentional Load

ERIC Educational Resources Information Center

Klemen, Jane; Buchel, Christian; Buhler, Mira; Menz, Mareike M.; Rose, Michael

2010-01-01

Attentional interference between tasks performed in parallel is known to have strong and often undesired effects. As yet, however, the mechanisms by which interference operates remain elusive. A better knowledge of these processes may facilitate our understanding of the effects of attention on human performance and the debilitating consequences…

Multiclass fMRI data decoding and visualization using supervised self-organizing maps.

PubMed

Hausfeld, Lars; Valente, Giancarlo; Formisano, Elia

2014-08-01

When multivariate pattern decoding is applied to fMRI studies entailing more than two experimental conditions, a most common approach is to transform the multiclass classification problem into a series of binary problems. Furthermore, for decoding analyses, classification accuracy is often the only outcome reported although the topology of activation patterns in the high-dimensional features space may provide additional insights into underlying brain representations. Here we propose to decode and visualize voxel patterns of fMRI datasets consisting of multiple conditions with a supervised variant of self-organizing maps (SSOMs). Using simulations and real fMRI data, we evaluated the performance of our SSOM-based approach. Specifically, the analysis of simulated fMRI data with varying signal-to-noise and contrast-to-noise ratio suggested that SSOMs perform better than a k-nearest-neighbor classifier for medium and large numbers of features (i.e. 250 to 1000 or more voxels) and similar to support vector machines (SVMs) for small and medium numbers of features (i.e. 100 to 600voxels). However, for a larger number of features (>800voxels), SSOMs performed worse than SVMs. When applied to a challenging 3-class fMRI classification problem with datasets collected to examine the neural representation of three human voices at individual speaker level, the SSOM-based algorithm was able to decode speaker identity from auditory cortical activation patterns. Classification performances were similar between SSOMs and other decoding algorithms; however, the ability to visualize decoding models and underlying data topology of SSOMs promotes a more comprehensive understanding of classification outcomes. We further illustrated this visualization ability of SSOMs with a re-analysis of a dataset examining the representation of visual categories in the ventral visual cortex (Haxby et al., 2001). This analysis showed that SSOMs could retrieve and visualize topography and neighborhood relations of the brain representation of eight visual categories. We conclude that SSOMs are particularly suited for decoding datasets consisting of more than two classes and are optimally combined with approaches that reduce the number of voxels used for classification (e.g. region-of-interest or searchlight approaches). Copyright © 2014. Published by Elsevier Inc.