Modeling and evaluating user behavior in exploratory visual analysis

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

Reda, Khairi; Johnson, Andrew E.; Papka, Michael E.

Empirical evaluation methods for visualizations have traditionally focused on assessing the outcome of the visual analytic process as opposed to characterizing how that process unfolds. There are only a handful of methods that can be used to systematically study how people use visualizations, making it difficult for researchers to capture and characterize the subtlety of cognitive and interaction behaviors users exhibit during visual analysis. To validate and improve visualization design, however, it is important for researchers to be able to assess and understand how users interact with visualization systems under realistic scenarios. This paper presents a methodology for modeling andmore » evaluating the behavior of users in exploratory visual analysis. We model visual exploration using a Markov chain process comprising transitions between mental, interaction, and computational states. These states and the transitions between them can be deduced from a variety of sources, including verbal transcripts, videos and audio recordings, and log files. This model enables the evaluator to characterize the cognitive and computational processes that are essential to insight acquisition in exploratory visual analysis, and reconstruct the dynamics of interaction between the user and the visualization system. We illustrate this model with two exemplar user studies, and demonstrate the qualitative and quantitative analytical tools it affords.« less

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.

Visual attention based bag-of-words model for image classification

NASA Astrophysics Data System (ADS)

Wang, Qiwei; Wan, Shouhong; Yue, Lihua; Wang, Che

2014-04-01

Bag-of-words is a classical method for image classification. The core problem is how to count the frequency of the visual words and what visual words to select. In this paper, we propose a visual attention based bag-of-words model (VABOW model) for image classification task. The VABOW model utilizes visual attention method to generate a saliency map, and uses the saliency map as a weighted matrix to instruct the statistic process for the frequency of the visual words. On the other hand, the VABOW model combines shape, color and texture cues and uses L1 regularization logistic regression method to select the most relevant and most efficient features. We compare our approach with traditional bag-of-words based method on two datasets, and the result shows that our VABOW model outperforms the state-of-the-art method for image classification.

An introduction to Space Weather Integrated Modeling

NASA Astrophysics Data System (ADS)

Zhong, D.; Feng, X.

2012-12-01

The need for a software toolkit that integrates space weather models and data is one of many challenges we are facing with when applying the models to space weather forecasting. To meet this challenge, we have developed Space Weather Integrated Modeling (SWIM) that is capable of analysis and visualizations of the results from a diverse set of space weather models. SWIM has a modular design and is written in Python, by using NumPy, matplotlib, and the Visualization ToolKit (VTK). SWIM provides data management module to read a variety of spacecraft data products and a specific data format of Solar-Interplanetary Conservation Element/Solution Element MHD model (SIP-CESE MHD model) for the study of solar-terrestrial phenomena. Data analysis, visualization and graphic user interface modules are also presented in a user-friendly way to run the integrated models and visualize the 2-D and 3-D data sets interactively. With these tools we can locally or remotely analysis the model result rapidly, such as extraction of data on specific location in time-sequence data sets, plotting interplanetary magnetic field lines, multi-slicing of solar wind speed, volume rendering of solar wind density, animation of time-sequence data sets, comparing between model result and observational data. To speed-up the analysis, an in-situ visualization interface is used to support visualizing the data 'on-the-fly'. We also modified some critical time-consuming analysis and visualization methods with the aid of GPU and multi-core CPU. We have used this tool to visualize the data of SIP-CESE MHD model in real time, and integrated the Database Model of shock arrival, Shock Propagation Model, Dst forecasting model and SIP-CESE MHD model developed by SIGMA Weather Group at State Key Laboratory of Space Weather/CAS.

Invariant visual object recognition: a model, with lighting invariance.

PubMed

Rolls, Edmund T; Stringer, Simon M

2006-01-01

How are invariant representations of objects formed in the visual cortex? We describe a neurophysiological and computational approach which focusses on a feature hierarchy model in which invariant representations can be built by self-organizing learning based on the statistics of the visual input. The model can use temporal continuity in an associative synaptic learning rule with a short term memory trace, and/or it can use spatial continuity in Continuous Transformation learning. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and in this paper we show also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in for example spatial and object search tasks. The model has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene.

Toward Model Building for Visual Aesthetic Perception

PubMed Central

Lughofer, Edwin; Zeng, Xianyi

2017-01-01

Several models of visual aesthetic perception have been proposed in recent years. Such models have drawn on investigations into the neural underpinnings of visual aesthetics, utilizing neurophysiological techniques and brain imaging techniques including functional magnetic resonance imaging, magnetoencephalography, and electroencephalography. The neural mechanisms underlying the aesthetic perception of the visual arts have been explained from the perspectives of neuropsychology, brain and cognitive science, informatics, and statistics. Although corresponding models have been constructed, the majority of these models contain elements that are difficult to be simulated or quantified using simple mathematical functions. In this review, we discuss the hypotheses, conceptions, and structures of six typical models for human aesthetic appreciation in the visual domain: the neuropsychological, information processing, mirror, quartet, and two hierarchical feed-forward layered models. Additionally, the neural foundation of aesthetic perception, appreciation, or judgement for each model is summarized. The development of a unified framework for the neurobiological mechanisms underlying the aesthetic perception of visual art and the validation of this framework via mathematical simulation is an interesting challenge in neuroaesthetics research. This review aims to provide information regarding the most promising proposals for bridging the gap between visual information processing and brain activity involved in aesthetic appreciation. PMID:29270194

Effect of microgravity on visual contrast threshold during STS Shuttle missions: Visual Function Tester-Model 2 (VFT-2)

NASA Technical Reports Server (NTRS)

Oneal, Melvin R.; Task, H. Lee; Genco, Louis V.

1992-01-01

Viewgraphs on effect of microgravity on visual contrast threshold during STS shuttle missions are presented. The purpose, methods, and results are discussed. The visual function tester model 2 is used.

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

Visualization and dissemination of global crustal models on virtual globes

NASA Astrophysics Data System (ADS)

Zhu, Liang-feng; Pan, Xin; Sun, Jian-zhong

2016-05-01

Global crustal models, such as CRUST 5.1 and its descendants, are very useful in a broad range of geoscience applications. The current method for representing the existing global crustal models relies heavily on dedicated computer programs to read and work with those models. Therefore, it is not suited to visualize and disseminate global crustal information to non-geological users. This shortcoming is becoming obvious as more and more people from both academic and non-academic institutions are interested in understanding the structure and composition of the crust. There is a pressing need to provide a modern, universal and user-friendly method to represent and visualize the existing global crustal models. In this paper, we present a systematic framework to easily visualize and disseminate the global crustal structure on virtual globes. Based on crustal information exported from the existing global crustal models, we first create a variety of KML-formatted crustal models with different levels of detail (LODs). And then the KML-formatted models can be loaded into a virtual globe for 3D visualization and model dissemination. A Keyhole Markup Language (KML) generator (Crust2KML) is developed to automatically convert crustal information obtained from the CRUST 1.0 model into KML-formatted global crustal models, and a web application (VisualCrust) is designed to disseminate and visualize those models over the Internet. The presented framework and associated implementations can be conveniently exported to other applications to support visualizing and analyzing the Earth's internal structure on both regional and global scales in a 3D virtual-globe environment.

Visual Cortical Entrainment to Motion and Categorical Speech Features during Silent Lipreading

PubMed Central

O’Sullivan, Aisling E.; Crosse, Michael J.; Di Liberto, Giovanni M.; Lalor, Edmund C.

2017-01-01

Speech is a multisensory percept, comprising an auditory and visual component. While the content and processing pathways of audio speech have been well characterized, the visual component is less well understood. In this work, we expand current methodologies using system identification to introduce a framework that facilitates the study of visual speech in its natural, continuous form. Specifically, we use models based on the unheard acoustic envelope (E), the motion signal (M) and categorical visual speech features (V) to predict EEG activity during silent lipreading. Our results show that each of these models performs similarly at predicting EEG in visual regions and that respective combinations of the individual models (EV, MV, EM and EMV) provide an improved prediction of the neural activity over their constituent models. In comparing these different combinations, we find that the model incorporating all three types of features (EMV) outperforms the individual models, as well as both the EV and MV models, while it performs similarly to the EM model. Importantly, EM does not outperform EV and MV, which, considering the higher dimensionality of the V model, suggests that more data is needed to clarify this finding. Nevertheless, the performance of EMV, and comparisons of the subject performances for the three individual models, provides further evidence to suggest that visual regions are involved in both low-level processing of stimulus dynamics and categorical speech perception. This framework may prove useful for investigating modality-specific processing of visual speech under naturalistic conditions. PMID:28123363

Reading visually embodied meaning from the brain: Visually grounded computational models decode visual-object mental imagery induced by written text.

PubMed

Anderson, Andrew James; Bruni, Elia; Lopopolo, Alessandro; Poesio, Massimo; Baroni, Marco

2015-10-15

Embodiment theory predicts that mental imagery of object words recruits neural circuits involved in object perception. The degree of visual imagery present in routine thought and how it is encoded in the brain is largely unknown. We test whether fMRI activity patterns elicited by participants reading objects' names include embodied visual-object representations, and whether we can decode the representations using novel computational image-based semantic models. We first apply the image models in conjunction with text-based semantic models to test predictions of visual-specificity of semantic representations in different brain regions. Representational similarity analysis confirms that fMRI structure within ventral-temporal and lateral-occipital regions correlates most strongly with the image models and conversely text models correlate better with posterior-parietal/lateral-temporal/inferior-frontal regions. We use an unsupervised decoding algorithm that exploits commonalities in representational similarity structure found within both image model and brain data sets to classify embodied visual representations with high accuracy (8/10) and then extend it to exploit model combinations to robustly decode different brain regions in parallel. By capturing latent visual-semantic structure our models provide a route into analyzing neural representations derived from past perceptual experience rather than stimulus-driven brain activity. Our results also verify the benefit of combining multimodal data to model human-like semantic representations. Copyright © 2015 Elsevier Inc. All rights reserved.

Testing the generality of the zoom-lens model: Evidence for visual-pathway specific effects of attended-region size on perception.

PubMed

Goodhew, Stephanie C; Lawrence, Rebecca K; Edwards, Mark

2017-05-01

There are volumes of information available to process in visual scenes. Visual spatial attention is a critically important selection mechanism that prevents these volumes from overwhelming our visual system's limited-capacity processing resources. We were interested in understanding the effect of the size of the attended area on visual perception. The prevailing model of attended-region size across cognition, perception, and neuroscience is the zoom-lens model. This model stipulates that the magnitude of perceptual processing enhancement is inversely related to the size of the attended region, such that a narrow attended-region facilitates greater perceptual enhancement than a wider region. Yet visual processing is subserved by two major visual pathways (magnocellular and parvocellular) that operate with a degree of independence in early visual processing and encode contrasting visual information. Historically, testing of the zoom-lens has used measures of spatial acuity ideally suited to parvocellular processing. This, therefore, raises questions about the generality of the zoom-lens model to different aspects of visual perception. We found that while a narrow attended-region facilitated spatial acuity and the perception of high spatial frequency targets, it had no impact on either temporal acuity or the perception of low spatial frequency targets. This pattern also held up when targets were not presented centrally. This supports the notion that visual attended-region size has dissociable effects on magnocellular versus parvocellular mediated visual processing.

Visual word ambiguity.

PubMed

van Gemert, Jan C; Veenman, Cor J; Smeulders, Arnold W M; Geusebroek, Jan-Mark

2010-07-01

This paper studies automatic image classification by modeling soft assignment in the popular codebook model. The codebook model describes an image as a bag of discrete visual words selected from a vocabulary, where the frequency distributions of visual words in an image allow classification. One inherent component of the codebook model is the assignment of discrete visual words to continuous image features. Despite the clear mismatch of this hard assignment with the nature of continuous features, the approach has been successfully applied for some years. In this paper, we investigate four types of soft assignment of visual words to image features. We demonstrate that explicitly modeling visual word assignment ambiguity improves classification performance compared to the hard assignment of the traditional codebook model. The traditional codebook model is compared against our method for five well-known data sets: 15 natural scenes, Caltech-101, Caltech-256, and Pascal VOC 2007/2008. We demonstrate that large codebook vocabulary sizes completely deteriorate the performance of the traditional model, whereas the proposed model performs consistently. Moreover, we show that our method profits in high-dimensional feature spaces and reaps higher benefits when increasing the number of image categories.

The practice of agent-based model visualization.

PubMed

Dorin, Alan; Geard, Nicholas

2014-01-01

We discuss approaches to agent-based model visualization. Agent-based modeling has its own requirements for visualization, some shared with other forms of simulation software, and some unique to this approach. In particular, agent-based models are typified by complexity, dynamism, nonequilibrium and transient behavior, heterogeneity, and a researcher's interest in both individual- and aggregate-level behavior. These are all traits requiring careful consideration in the design, experimentation, and communication of results. In the case of all but final communication for dissemination, researchers may not make their visualizations public. Hence, the knowledge of how to visualize during these earlier stages is unavailable to the research community in a readily accessible form. Here we explore means by which all phases of agent-based modeling can benefit from visualization, and we provide examples from the available literature and online sources to illustrate key stages and techniques.

Illustrative visualization of 3D city models

NASA Astrophysics Data System (ADS)

Doellner, Juergen; Buchholz, Henrik; Nienhaus, Marc; Kirsch, Florian

2005-03-01

This paper presents an illustrative visualization technique that provides expressive representations of large-scale 3D city models, inspired by the tradition of artistic and cartographic visualizations typically found in bird"s-eye view and panoramic maps. We define a collection of city model components and a real-time multi-pass rendering algorithm that achieves comprehensible, abstract 3D city model depictions based on edge enhancement, color-based and shadow-based depth cues, and procedural facade texturing. Illustrative visualization provides an effective visual interface to urban spatial information and associated thematic information complementing visual interfaces based on the Virtual Reality paradigm, offering a huge potential for graphics design. Primary application areas include city and landscape planning, cartoon worlds in computer games, and tourist information systems.

Effect of Microgravity on Several Visual Functions During STS Shuttle Missions: Visual Function Tester-model 1 (VFT-1)

NASA Technical Reports Server (NTRS)

Oneal, Melvin R.; Task, H. Lee; Genco, Louis V.

1992-01-01

Viewgraphs on the effect of microgravity on several visual functions during STS shuttle missions are presented. The purpose, methods, results, and discussion are discussed. The visual function tester model 1 is used.

Spatial and Feature-Based Attention in a Layered Cortical Microcircuit Model

PubMed Central

Wagatsuma, Nobuhiko; Potjans, Tobias C.; Diesmann, Markus; Sakai, Ko; Fukai, Tomoki

2013-01-01

Directing attention to the spatial location or the distinguishing feature of a visual object modulates neuronal responses in the visual cortex and the stimulus discriminability of subjects. However, the spatial and feature-based modes of attention differently influence visual processing by changing the tuning properties of neurons. Intriguingly, neurons' tuning curves are modulated similarly across different visual areas under both these modes of attention. Here, we explored the mechanism underlying the effects of these two modes of visual attention on the orientation selectivity of visual cortical neurons. To do this, we developed a layered microcircuit model. This model describes multiple orientation-specific microcircuits sharing their receptive fields and consisting of layers 2/3, 4, 5, and 6. These microcircuits represent a functional grouping of cortical neurons and mutually interact via lateral inhibition and excitatory connections between groups with similar selectivity. The individual microcircuits receive bottom-up visual stimuli and top-down attention in different layers. A crucial assumption of the model is that feature-based attention activates orientation-specific microcircuits for the relevant feature selectively, whereas spatial attention activates all microcircuits homogeneously, irrespective of their orientation selectivity. Consequently, our model simultaneously accounts for the multiplicative scaling of neuronal responses in spatial attention and the additive modulations of orientation tuning curves in feature-based attention, which have been observed widely in various visual cortical areas. Simulations of the model predict contrasting differences between excitatory and inhibitory neurons in the two modes of attentional modulations. Furthermore, the model replicates the modulation of the psychophysical discriminability of visual stimuli in the presence of external noise. Our layered model with a biologically suggested laminar structure describes the basic circuit mechanism underlying the attention-mode specific modulations of neuronal responses and visual perception. PMID:24324628

How do People Make Sense of Unfamiliar Visualizations?: A Grounded Model of Novice's Information Visualization Sensemaking.

PubMed

Lee, Sukwon; Kim, Sung-Hee; Hung, Ya-Hsin; Lam, Heidi; Kang, Youn-ah; Yi, Ji Soo

2016-01-01

In this paper, we would like to investigate how people make sense of unfamiliar information visualizations. In order to achieve the research goal, we conducted a qualitative study by observing 13 participants when they endeavored to make sense of three unfamiliar visualizations (i.e., a parallel-coordinates plot, a chord diagram, and a treemap) that they encountered for the first time. We collected data including audio/video record of think-aloud sessions and semi-structured interview; and analyzed the data using the grounded theory method. The primary result of this study is a grounded model of NOvice's information Vlsualization Sensemaking (NOVIS model), which consists of the five major cognitive activities: 1 encountering visualization, 2 constructing a frame, 3 exploring visualization, 4 questioning the frame, and 5 floundering on visualization. We introduce the NOVIS model by explaining the five activities with representative quotes from our participants. We also explore the dynamics in the model. Lastly, we compare with other existing models and share further research directions that arose from our observations.

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.

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.

Cortical dynamics of feature binding and reset: control of visual persistence.

PubMed

Francis, G; Grossberg, S; Mingolla, E

1994-04-01

An analysis of the reset of visual cortical circuits responsible for the binding or segmentation of visual features into coherent visual forms yields a model that explains properties of visual persistence. The reset mechanisms prevent massive smearing of visual percepts in response to rapidly moving images. The model simulates relationships among psychophysical data showing inverse relations of persistence to flash luminance and duration, greater persistence of illusory contours than real contours, a U-shaped temporal function for persistence of illusory contours, a reduction of persistence due to adaptation with a stimulus of like orientation, an increase of persistence with spatial separation of a masking stimulus. The model suggests that a combination of habituative, opponent, and endstopping mechanisms prevent smearing and limit persistence. Earlier work with the model has analyzed data about boundary formation, texture segregation, shape-from-shading, and figure-ground separation. Thus, several types of data support each model mechanism and new predictions are made.

Promoting Visualization Skills through Deconstruction Using Physical Models and a Visualization Activity Intervention

NASA Astrophysics Data System (ADS)

Schiltz, Holly Kristine

Visualization skills are important in learning chemistry, as these skills have been shown to correlate to high ability in problem solving. Students' understanding of visual information and their problem-solving processes may only ever be accessed indirectly: verbalization, gestures, drawings, etc. In this research, deconstruction of complex visual concepts was aligned with the promotion of students' verbalization of visualized ideas to teach students to solve complex visual tasks independently. All instructional tools and teaching methods were developed in accordance with the principles of the theoretical framework, the Modeling Theory of Learning: deconstruction of visual representations into model components, comparisons to reality, and recognition of students' their problemsolving strategies. Three physical model systems were designed to provide students with visual and tangible representations of chemical concepts. The Permanent Reflection Plane Demonstration provided visual indicators that students used to support or invalidate the presence of a reflection plane. The 3-D Coordinate Axis system provided an environment that allowed students to visualize and physically enact symmetry operations in a relevant molecular context. The Proper Rotation Axis system was designed to provide a physical and visual frame of reference to showcase multiple symmetry elements that students must identify in a molecular model. Focus groups of students taking Inorganic chemistry working with the physical model systems demonstrated difficulty documenting and verbalizing processes and descriptions of visual concepts. Frequently asked student questions were classified, but students also interacted with visual information through gestures and model manipulations. In an effort to characterize how much students used visualization during lecture or recitation, we developed observation rubrics to gather information about students' visualization artifacts and examined the effect instructors' modeled visualization artifacts had on students. No patterns emerged from the passive observation of visualization artifacts in lecture or recitation, but the need to elicit visual information from students was made clear. Deconstruction proved to be a valuable method for instruction and assessment of visual information. Three strategies for using deconstruction in teaching were distilled from the lessons and observations of the student focus groups: begin with observations of what is given in an image and what it's composed of, identify the relationships between components to find additional operations in different environments about the molecule, and deconstructing steps of challenging questions can reveal mistakes. An intervention was developed to teach students to use deconstruction and verbalization to analyze complex visualization tasks and employ the principles of the theoretical framework. The activities were scaffolded to introduce increasingly challenging concepts to students, but also support them as they learned visually demanding chemistry concepts. Several themes were observed in the analysis of the visualization activities. Students used deconstruction by documenting which parts of the images were useful for interpretation of the visual. Students identified valid patterns and rules within the images, which signified understanding of arrangement of information presented in the representation. Successful strategy communication was identified when students documented personal strategies that allowed them to complete the activity tasks. Finally, students demonstrated the ability to extend symmetry skills to advanced applications they had not previously seen. This work shows how the use of deconstruction and verbalization may have a great impact on how students master difficult topics and combined, they offer students a powerful strategy to approach visually demanding chemistry problems and to the instructor a unique insight to mentally constructed strategies.

Toward semantic-based retrieval of visual information: a model-based approach

NASA Astrophysics Data System (ADS)

Park, Youngchoon; Golshani, Forouzan; Panchanathan, Sethuraman

2002-07-01

This paper center around the problem of automated visual content classification. To enable classification based image or visual object retrieval, we propose a new image representation scheme called visual context descriptor (VCD) that is a multidimensional vector in which each element represents the frequency of a unique visual property of an image or a region. VCD utilizes the predetermined quality dimensions (i.e., types of features and quantization level) and semantic model templates mined in priori. Not only observed visual cues, but also contextually relevant visual features are proportionally incorporated in VCD. Contextual relevance of a visual cue to a semantic class is determined by using correlation analysis of ground truth samples. Such co-occurrence analysis of visual cues requires transformation of a real-valued visual feature vector (e.g., color histogram, Gabor texture, etc.,) into a discrete event (e.g., terms in text). Good-feature to track, rule of thirds, iterative k-means clustering and TSVQ are involved in transformation of feature vectors into unified symbolic representations called visual terms. Similarity-based visual cue frequency estimation is also proposed and used for ensuring the correctness of model learning and matching since sparseness of sample data causes the unstable results of frequency estimation of visual cues. The proposed method naturally allows integration of heterogeneous visual or temporal or spatial cues in a single classification or matching framework, and can be easily integrated into a semantic knowledge base such as thesaurus, and ontology. Robust semantic visual model template creation and object based image retrieval are demonstrated based on the proposed content description scheme.

Modeling human comprehension of data visualizations

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

Matzen, Laura E.; Haass, Michael Joseph; Divis, Kristin Marie

This project was inspired by two needs. The first is a need for tools to help scientists and engineers to design effective data visualizations for communicating information, whether to the user of a system, an analyst who must make decisions based on complex data, or in the context of a technical report or publication. Most scientists and engineers are not trained in visualization design, and they could benefit from simple metrics to assess how well their visualization's design conveys the intended message. In other words, will the most important information draw the viewer's attention? The second is the need formore » cognition-based metrics for evaluating new types of visualizations created by researchers in the information visualization and visual analytics communities. Evaluating visualizations is difficult even for experts. However, all visualization methods and techniques are intended to exploit the properties of the human visual system to convey information efficiently to a viewer. Thus, developing evaluation methods that are rooted in the scientific knowledge of the human visual system could be a useful approach. In this project, we conducted fundamental research on how humans make sense of abstract data visualizations, and how this process is influenced by their goals and prior experience. We then used that research to develop a new model, the Data Visualization Saliency Model, that can make accurate predictions about which features in an abstract visualization will draw a viewer's attention. The model is an evaluation tool that can address both of the needs described above, supporting both visualization research and Sandia mission needs.« less

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.

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…

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

A Computational Model of Spatial Visualization Capacity

ERIC Educational Resources Information Center

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

2008-01-01

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…

Physical Models that Provide Guidance in Visualization Deconstruction in an Inorganic Context

ERIC Educational Resources Information Center

Schiltz, Holly K.; Oliver-Hoyo, Maria T.

2012-01-01

Three physical model systems have been developed to help students deconstruct the visualization needed when learning symmetry and group theory. The systems provide students with physical and visual frames of reference to facilitate the complex visualization involved in symmetry concepts. The permanent reflection plane demonstration presents an…

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

Jiang, Like; Kang, Jian, E-mail: j.kang@sheffield.ac.uk; Schroth, Olaf

Large scale transportation projects can adversely affect the visual perception of environmental quality and require adequate visual impact assessment. In this study, we investigated the effects of the characteristics of the road project and the character of the existing landscape on the perceived visual impact of motorways, and developed a GIS-based prediction model based on the findings. An online survey using computer-visualised scenes of different motorway and landscape scenarios was carried out to obtain perception-based judgements on the visual impact. Motorway scenarios simulated included the baseline scenario without road, original motorway, motorways with timber noise barriers, transparent noise barriers andmore » tree screen; different landscape scenarios were created by changing land cover of buildings and trees in three distance zones. The landscape content of each scene was measured in GIS. The result shows that presence of a motorway especially with the timber barrier significantly decreases the visual quality of the view. The resulted visual impact tends to be lower where it is less visually pleasant with more buildings in the view, and can be slightly reduced by the visual absorption effect of the scattered trees between the motorway and the viewpoint. Based on the survey result, eleven predictors were identified for the visual impact prediction model which was applied in GIS to generate maps of visual impact of motorways in different scenarios. The proposed prediction model can be used to achieve efficient and reliable assessment of visual impact of motorways. - Highlights: • Motorways induce significant visual impact especially with timber noise barriers. • Visual impact is negatively correlated with amount of buildings in the view. • Visual impact is positively correlated with percentage of trees in the view. • Perception-based motorway visual impact prediction model using mapped predictors • Predicted visual impacts in different scenarios are mapped in GIS.« less

Model-Based Reasoning: Using Visual Tools to Reveal Student Learning

ERIC Educational Resources Information Center

Luckie, Douglas; Harrison, Scott H.; Ebert-May, Diane

2011-01-01

Using visual models is common in science and should become more common in classrooms. Our research group has developed and completed studies on the use of a visual modeling tool, the Concept Connector. This modeling tool consists of an online concept mapping Java applet that has automatic scoring functions we refer to as Robograder. The Concept…

Modeling and measuring the visual detection of ecologically relevant motion by an Anolis lizard.

PubMed

Pallus, Adam C; Fleishman, Leo J; Castonguay, Philip M

2010-01-01

Motion in the visual periphery of lizards, and other animals, often causes a shift of visual attention toward the moving object. This behavioral response must be more responsive to relevant motion (predators, prey, conspecifics) than to irrelevant motion (windblown vegetation). Early stages of visual motion detection rely on simple local circuits known as elementary motion detectors (EMDs). We presented a computer model consisting of a grid of correlation-type EMDs, with videos of natural motion patterns, including prey, predators and windblown vegetation. We systematically varied the model parameters and quantified the relative response to the different classes of motion. We carried out behavioral experiments with the lizard Anolis sagrei and determined that their visual response could be modeled with a grid of correlation-type EMDs with a spacing parameter of 0.3 degrees visual angle, and a time constant of 0.1 s. The model with these parameters gave substantially stronger responses to relevant motion patterns than to windblown vegetation under equivalent conditions. However, the model is sensitive to local contrast and viewer-object distance. Therefore, additional neural processing is probably required for the visual system to reliably distinguish relevant from irrelevant motion under a full range of natural conditions.

A Hierarchical Visualization Analysis Model of Power Big Data

NASA Astrophysics Data System (ADS)

Li, Yongjie; Wang, Zheng; Hao, Yang

2018-01-01

Based on the conception of integrating VR scene and power big data analysis, a hierarchical visualization analysis model of power big data is proposed, in which levels are designed, targeting at different abstract modules like transaction, engine, computation, control and store. The regularly departed modules of power data storing, data mining and analysis, data visualization are integrated into one platform by this model. It provides a visual analysis solution for the power big data.

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.

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.

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).

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.

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

Automated visualization of rule-based models

PubMed Central

Tapia, Jose-Juan; Faeder, James R.

2017-01-01

Frameworks such as BioNetGen, Kappa and Simmune use “reaction rules” to specify biochemical interactions compactly, where each rule specifies a mechanism such as binding or phosphorylation and its structural requirements. Current rule-based models of signaling pathways have tens to hundreds of rules, and these numbers are expected to increase as more molecule types and pathways are added. Visual representations are critical for conveying rule-based models, but current approaches to show rules and interactions between rules scale poorly with model size. Also, inferring design motifs that emerge from biochemical interactions is an open problem, so current approaches to visualize model architecture rely on manual interpretation of the model. Here, we present three new visualization tools that constitute an automated visualization framework for rule-based models: (i) a compact rule visualization that efficiently displays each rule, (ii) the atom-rule graph that conveys regulatory interactions in the model as a bipartite network, and (iii) a tunable compression pipeline that incorporates expert knowledge and produces compact diagrams of model architecture when applied to the atom-rule graph. The compressed graphs convey network motifs and architectural features useful for understanding both small and large rule-based models, as we show by application to specific examples. Our tools also produce more readable diagrams than current approaches, as we show by comparing visualizations of 27 published models using standard graph metrics. We provide an implementation in the open source and freely available BioNetGen framework, but the underlying methods are general and can be applied to rule-based models from the Kappa and Simmune frameworks also. We expect that these tools will promote communication and analysis of rule-based models and their eventual integration into comprehensive whole-cell models. PMID:29131816

Towards the quantitative evaluation of visual attention models.

PubMed

Bylinskii, Z; DeGennaro, E M; Rajalingham, R; Ruda, H; Zhang, J; Tsotsos, J K

2015-11-01

Scores of visual attention models have been developed over the past several decades of research. Differences in implementation, assumptions, and evaluations have made comparison of these models very difficult. Taxonomies have been constructed in an attempt at the organization and classification of models, but are not sufficient at quantifying which classes of models are most capable of explaining available data. At the same time, a multitude of physiological and behavioral findings have been published, measuring various aspects of human and non-human primate visual attention. All of these elements highlight the need to integrate the computational models with the data by (1) operationalizing the definitions of visual attention tasks and (2) designing benchmark datasets to measure success on specific tasks, under these definitions. In this paper, we provide some examples of operationalizing and benchmarking different visual attention tasks, along with the relevant design considerations. Copyright © 2015 Elsevier Ltd. All rights reserved.

Terminology model discovery using natural language processing and visualization techniques.

PubMed

Zhou, Li; Tao, Ying; Cimino, James J; Chen, Elizabeth S; Liu, Hongfang; Lussier, Yves A; Hripcsak, George; Friedman, Carol

2006-12-01

Medical terminologies are important for unambiguous encoding and exchange of clinical information. The traditional manual method of developing terminology models is time-consuming and limited in the number of phrases that a human developer can examine. In this paper, we present an automated method for developing medical terminology models based on natural language processing (NLP) and information visualization techniques. Surgical pathology reports were selected as the testing corpus for developing a pathology procedure terminology model. The use of a general NLP processor for the medical domain, MedLEE, provides an automated method for acquiring semantic structures from a free text corpus and sheds light on a new high-throughput method of medical terminology model development. The use of an information visualization technique supports the summarization and visualization of the large quantity of semantic structures generated from medical documents. We believe that a general method based on NLP and information visualization will facilitate the modeling of medical terminologies.

Research on metallic material defect detection based on bionic sensing of human visual properties

NASA Astrophysics Data System (ADS)

Zhang, Pei Jiang; Cheng, Tao

2018-05-01

Due to the fact that human visual system can quickly lock the areas of interest in complex natural environment and focus on it, this paper proposes an eye-based visual attention mechanism by simulating human visual imaging features based on human visual attention mechanism Bionic Sensing Visual Inspection Model Method to Detect Defects of Metallic Materials in the Mechanical Field. First of all, according to the biologically visually significant low-level features, the mark of defect experience marking is used as the intermediate feature of simulated visual perception. Afterwards, SVM method was used to train the advanced features of visual defects of metal material. According to the weight of each party, the biometrics detection model of metal material defect, which simulates human visual characteristics, is obtained.

Choosing colors for map display icons using models of visual search.

PubMed

Shive, Joshua; Francis, Gregory

2013-04-01

We show how to choose colors for icons on maps to minimize search time using predictions of a model of visual search. The model analyzes digital images of a search target (an icon on a map) and a search display (the map containing the icon) and predicts search time as a function of target-distractor color distinctiveness and target eccentricity. We parameterized the model using data from a visual search task and performed a series of optimization tasks to test the model's ability to choose colors for icons to minimize search time across icons. Map display designs made by this procedure were tested experimentally. In a follow-up experiment, we examined the model's flexibility to assign colors in novel search situations. The model fits human performance, performs well on the optimization tasks, and can choose colors for icons on maps with novel stimuli to minimize search time without requiring additional model parameter fitting. Models of visual search can suggest color choices that produce search time reductions for display icons. Designers should consider constructing visual search models as a low-cost method of evaluating color assignments.

Manual control of yaw motion with combined visual and vestibular cues

NASA Technical Reports Server (NTRS)

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

1977-01-01

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 was modelled 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 correction to the frequency responses is provided by a separate measurement of manual control performance in an analogous visual pursuit nulling task. The resulting dual-input describing function for motion perception dependence on combined cue presentation supports the complementary model, in which vestibular cues dominate sensation at frequencies above 0.05 Hz. The describing function model is extended by the proposal of a non-linear cue conflict model, in which cue weighting depends on the level of agreement between visual and vestibular cues.

Visualization of 3D CT-based anatomical models

NASA Astrophysics Data System (ADS)

Alaytsev, Innokentiy K.; Danilova, Tatyana V.; Manturov, Alexey O.; Mareev, Gleb O.; Mareev, Oleg V.

2018-04-01

Biomedical volumetric data visualization techniques for the exploration purposes are well developed. Most of the known methods are inappropriate for surgery simulation systems due to lack of realism. A segmented data visualization is a well-known approach for the visualization of the structured volumetric data. The research is focused on improvement of the segmented data visualization technique by the aliasing problems resolution and the use of material transparency modeling for better semitransparent structures rendering.

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…

Three-Dimension Visualization for Primary Wheat Diseases Based on Simulation Model

NASA Astrophysics Data System (ADS)

Shijuan, Li; Yeping, Zhu

Crop simulation model has been becoming the core of agricultural production management and resource optimization management. Displaying crop growth process makes user observe the crop growth and development intuitionisticly. On the basis of understanding and grasping the occurrence condition, popularity season, key impact factors for main wheat diseases of stripe rust, leaf rust, stem rust, head blight and powdery mildew from research material and literature, we designed 3D visualization model for wheat growth and diseases occurrence. The model system will help farmer, technician and decision-maker to use crop growth simulation model better and provide decision-making support. Now 3D visualization model for wheat growth on the basis of simulation model has been developed, and the visualization model for primary wheat diseases is in the process of development.

The Modulation of Visual and Task Characteristics of a Writing System on Hemispheric Lateralization in Visual Word Recognition--A Computational Exploration

ERIC Educational Resources Information Center

Hsiao, Janet H.; Lam, Sze Man

2013-01-01

Through computational modeling, here we examine whether visual and task characteristics of writing systems alone can account for lateralization differences in visual word recognition between different languages without assuming influence from left hemisphere (LH) lateralized language processes. We apply a hemispheric processing model of face…

A Fractional Cartesian Composition Model for Semi-Spatial Comparative Visualization Design.

PubMed

Kolesar, Ivan; Bruckner, Stefan; Viola, Ivan; Hauser, Helwig

2017-01-01

The study of spatial data ensembles leads to substantial visualization challenges in a variety of applications. In this paper, we present a model for comparative visualization that supports the design of according ensemble visualization solutions by partial automation. We focus on applications, where the user is interested in preserving selected spatial data characteristics of the data as much as possible-even when many ensemble members should be jointly studied using comparative visualization. In our model, we separate the design challenge into a minimal set of user-specified parameters and an optimization component for the automatic configuration of the remaining design variables. We provide an illustrated formal description of our model and exemplify our approach in the context of several application examples from different domains in order to demonstrate its generality within the class of comparative visualization problems for spatial data ensembles.

A novel visual hardware behavioral language

NASA Technical Reports Server (NTRS)

Li, Xueqin; Cheng, H. D.

1992-01-01

Most hardware behavioral languages just use texts to describe the behavior of the desired hardware design. This is inconvenient for VLSI designers who enjoy using the schematic approach. The proposed visual hardware behavioral language has the ability to graphically express design information using visual parallel models (blocks), visual sequential models (processes) and visual data flow graphs (which consist of primitive operational icons, control icons, and Data and Synchro links). Thus, the proposed visual hardware behavioral language can not only specify hardware concurrent and sequential functionality, but can also visually expose parallelism, sequentiality, and disjointness (mutually exclusive operations) for the hardware designers. That would make the hardware designers capture the design ideas easily and explicitly using this visual hardware behavioral language.

Flexible Coding of Visual Working Memory Representations during Distraction.

PubMed

Lorenc, Elizabeth S; Sreenivasan, Kartik K; Nee, Derek E; Vandenbroucke, Annelinde R E; D'Esposito, Mark

2018-06-06

Visual working memory (VWM) recruits a broad network of brain regions, including prefrontal, parietal, and visual cortices. Recent evidence supports a "sensory recruitment" model of VWM, whereby precise visual details are maintained in the same stimulus-selective regions responsible for perception. A key question in evaluating the sensory recruitment model is how VWM representations persist through distracting visual input, given that the early visual areas that putatively represent VWM content are susceptible to interference from visual stimulation.To address this question, we used a functional magnetic resonance imaging inverted encoding model approach to quantitatively assess the effect of distractors on VWM representations in early visual cortex and the intraparietal sulcus (IPS), another region previously implicated in the storage of VWM information. This approach allowed us to reconstruct VWM representations for orientation, both before and after visual interference, and to examine whether oriented distractors systematically biased these representations. In our human participants (both male and female), we found that orientation information was maintained simultaneously in early visual areas and IPS in anticipation of possible distraction, and these representations persisted in the absence of distraction. Importantly, early visual representations were susceptible to interference; VWM orientations reconstructed from visual cortex were significantly biased toward distractors, corresponding to a small attractive bias in behavior. In contrast, IPS representations did not show such a bias. These results provide quantitative insight into the effect of interference on VWM representations, and they suggest a dynamic tradeoff between visual and parietal regions that allows flexible adaptation to task demands in service of VWM. SIGNIFICANCE STATEMENT Despite considerable evidence that stimulus-selective visual regions maintain precise visual information in working memory, it remains unclear how these representations persist through subsequent input. Here, we used quantitative model-based fMRI analyses to reconstruct the contents of working memory and examine the effects of distracting input. Although representations in the early visual areas were systematically biased by distractors, those in the intraparietal sulcus appeared distractor-resistant. In contrast, early visual representations were most reliable in the absence of distraction. These results demonstrate the dynamic, adaptive nature of visual working memory processes, and provide quantitative insight into the ways in which representations can be affected by interference. Further, they suggest that current models of working memory should be revised to incorporate this flexibility. Copyright © 2018 the authors 0270-6474/18/385267-10$15.00/0.

Tactical 3D Model Generation using Structure-From-Motion on Video from Unmanned Systems

DTIC Science & Technology

2015-04-01

available SfM application known as VisualSFM .6,7 VisualSFM is an end-user, “off-the-shelf” implementation of SfM that is easy to configure and used for...most 3D model generation applications from imagery. While the usual interface with VisualSFM is through their graphical user interface (GUI), we will be...of our system.5 There are two types of 3D model generation available within VisualSFM ; sparse and dense reconstruction. Sparse reconstruction begins

Modeling and visualizing borehole information on virtual globes using KML

NASA Astrophysics Data System (ADS)

Zhu, Liang-feng; Wang, Xi-feng; Zhang, Bing

2014-01-01

Advances in virtual globes and Keyhole Markup Language (KML) are providing the Earth scientists with the universal platforms to manage, visualize, integrate and disseminate geospatial information. In order to use KML to represent and disseminate subsurface geological information on virtual globes, we present an automatic method for modeling and visualizing a large volume of borehole information. Based on a standard form of borehole database, the method first creates a variety of borehole models with different levels of detail (LODs), including point placemarks representing drilling locations, scatter dots representing contacts and tube models representing strata. Subsequently, the level-of-detail based (LOD-based) multi-scale representation is constructed to enhance the efficiency of visualizing large numbers of boreholes. Finally, the modeling result can be loaded into a virtual globe application for 3D visualization. An implementation program, termed Borehole2KML, is developed to automatically convert borehole data into KML documents. A case study of using Borehole2KML to create borehole models in Shanghai shows that the modeling method is applicable to visualize, integrate and disseminate borehole information on the Internet. The method we have developed has potential use in societal service of geological information.

Merging Psychophysical and Psychometric Theory to Estimate Global Visual State Measures from Forced-Choices

NASA Astrophysics Data System (ADS)

Massof, Robert W.; Schmidt, Karen M.; Laby, Daniel M.; Kirschen, David; Meadows, David

2013-09-01

Visual acuity, a forced-choice psychophysical measure of visual spatial resolution, is the sine qua non of clinical visual impairment testing in ophthalmology and optometry patients with visual system disorders ranging from refractive error to retinal, optic nerve, or central visual system pathology. Visual acuity measures are standardized against a norm, but it is well known that visual acuity depends on a variety of stimulus parameters, including contrast and exposure duration. This paper asks if it is possible to estimate a single global visual state measure from visual acuity measures as a function of stimulus parameters that can represent the patient's overall visual health state with a single variable. Psychophysical theory (at the sensory level) and psychometric theory (at the decision level) are merged to identify the conditions that must be satisfied to derive a global visual state measure from parameterised visual acuity measures. A global visual state measurement model is developed and tested with forced-choice visual acuity measures from 116 subjects with no visual impairments and 560 subjects with uncorrected refractive error. The results are in agreement with the expectations of the model.

Cognitive aging on latent constructs for visual processing capacity: a novel structural equation modeling framework with causal assumptions based on a theory of visual attention.

PubMed

Nielsen, Simon; Wilms, L Inge

2014-01-01

We examined the effects of normal aging on visual cognition in a sample of 112 healthy adults aged 60-75. A testbattery was designed to capture high-level measures of visual working memory and low-level measures of visuospatial attention and memory. To answer questions of how cognitive aging affects specific aspects of visual processing capacity, we used confirmatory factor analyses in Structural Equation Modeling (SEM; Model 2), informed by functional structures that were modeled with path analyses in SEM (Model 1). The results show that aging effects were selective to measures of visual processing speed compared to visual short-term memory (VSTM) capacity (Model 2). These results are consistent with some studies reporting selective aging effects on processing speed, and inconsistent with other studies reporting aging effects on both processing speed and VSTM capacity. In the discussion we argue that this discrepancy may be mediated by differences in age ranges, and variables of demography. The study demonstrates that SEM is a sensitive method to detect cognitive aging effects even within a narrow age-range, and a useful approach to structure the relationships between measured variables, and the cognitive functional foundation they supposedly represent.

Lifting business process diagrams to 2.5 dimensions

NASA Astrophysics Data System (ADS)

Effinger, Philip; Spielmann, Johannes

2010-01-01

In this work, we describe our visualization approach for business processes using 2.5 dimensional techniques (2.5D). The idea of 2.5D is to add the concept of layering to a two dimensional (2D) visualization. The layers are arranged in a three-dimensional display space. For the modeling of the business processes, we use the Business Process Modeling Notation (BPMN). The benefit of connecting BPMN with a 2.5D visualization is not only to obtain a more abstract view on the business process models but also to develop layering criteria that eventually increase readability of the BPMN model compared to 2D. We present a 2.5D Navigator for BPMN models that offers different perspectives for visualization. Therefore we also develop BPMN specific perspectives. The 2.5D Navigator combines the 2.5D approach with perspectives and allows free navigation in the three dimensional display space. We also demonstrate our tool and libraries used for implementation of the visualizations. The underlying general framework for 2.5D visualizations is explored and presented in a fashion that it can easily be used for different applications. Finally, an evaluation of our navigation tool demonstrates that we can achieve satisfying and aesthetic displays of diagrams stating BPMN models in 2.5D-visualizations.

A State Space Model for Spatial Updating of Remembered Visual Targets during Eye Movements

PubMed Central

Mohsenzadeh, Yalda; Dash, Suryadeep; Crawford, J. Douglas

2016-01-01

In the oculomotor system, spatial updating is the ability to aim a saccade toward a remembered visual target position despite intervening eye movements. Although this has been the subject of extensive experimental investigation, there is still no unifying theoretical framework to explain the neural mechanism for this phenomenon, and how it influences visual signals in the brain. Here, we propose a unified state-space model (SSM) to account for the dynamics of spatial updating during two types of eye movement; saccades and smooth pursuit. Our proposed model is a non-linear SSM and implemented through a recurrent radial-basis-function neural network in a dual Extended Kalman filter (EKF) structure. The model parameters and internal states (remembered target position) are estimated sequentially using the EKF method. The proposed model replicates two fundamental experimental observations: continuous gaze-centered updating of visual memory-related activity during smooth pursuit, and predictive remapping of visual memory activity before and during saccades. Moreover, our model makes the new prediction that, when uncertainty of input signals is incorporated in the model, neural population activity and receptive fields expand just before and during saccades. These results suggest that visual remapping and motor updating are part of a common visuomotor mechanism, and that subjective perceptual constancy arises in part from training the visual system on motor tasks. PMID:27242452

Computational models of cortical visual processing.

PubMed Central

Heeger, D J; Simoncelli, E P; Movshon, J A

1996-01-01

The visual responses of neurons in the cerebral cortex were first adequately characterized in the 1960s by D. H. Hubel and T. N. Wiesel [(1962) J. Physiol. (London) 160, 106-154; (1968) J. Physiol. (London) 195, 215-243] using qualitative analyses based on simple geometric visual targets. Over the past 30 years, it has become common to consider the properties of these neurons by attempting to make formal descriptions of these transformations they execute on the visual image. Most such models have their roots in linear-systems approaches pioneered in the retina by C. Enroth-Cugell and J. R. Robson [(1966) J. Physiol. (London) 187, 517-552], but it is clear that purely linear models of cortical neurons are inadequate. We present two related models: one designed to account for the responses of simple cells in primary visual cortex (V1) and one designed to account for the responses of pattern direction selective cells in MT (or V5), an extrastriate visual area thought to be involved in the analysis of visual motion. These models share a common structure that operates in the same way on different kinds of input, and instantiate the widely held view that computational strategies are similar throughout the cerebral cortex. Implementations of these models for Macintosh microcomputers are available and can be used to explore the models' properties. PMID:8570605

Visual Attention Model Based on Statistical Properties of Neuron Responses

PubMed Central

Duan, Haibin; Wang, Xiaohua

2015-01-01

Visual attention is a mechanism of the visual system that can select relevant objects from a specific scene. Interactions among neurons in multiple cortical areas are considered to be involved in attentional allocation. However, the characteristics of the encoded features and neuron responses in those attention related cortices are indefinite. Therefore, further investigations carried out in this study aim at demonstrating that unusual regions arousing more attention generally cause particular neuron responses. We suppose that visual saliency is obtained on the basis of neuron responses to contexts in natural scenes. A bottom-up visual attention model is proposed based on the self-information of neuron responses to test and verify the hypothesis. Four different color spaces are adopted and a novel entropy-based combination scheme is designed to make full use of color information. Valuable regions are highlighted while redundant backgrounds are suppressed in the saliency maps obtained by the proposed model. Comparative results reveal that the proposed model outperforms several state-of-the-art models. This study provides insights into the neuron responses based saliency detection and may underlie the neural mechanism of early visual cortices for bottom-up visual attention. PMID:25747859

Neuro-cognitive mechanisms of conscious and unconscious visual perception: From a plethora of phenomena to general principles

PubMed Central

Kiefer, Markus; Ansorge, Ulrich; Haynes, John-Dylan; Hamker, Fred; Mattler, Uwe; Verleger, Rolf; Niedeggen, Michael

2011-01-01

Psychological and neuroscience approaches have promoted much progress in elucidating the cognitive and neural mechanisms that underlie phenomenal visual awareness during the last decades. In this article, we provide an overview of the latest research investigating important phenomena in conscious and unconscious vision. We identify general principles to characterize conscious and unconscious visual perception, which may serve as important building blocks for a unified model to explain the plethora of findings. We argue that in particular the integration of principles from both conscious and unconscious vision is advantageous and provides critical constraints for developing adequate theoretical models. Based on the principles identified in our review, we outline essential components of a unified model of conscious and unconscious visual perception. We propose that awareness refers to consolidated visual representations, which are accessible to the entire brain and therefore globally available. However, visual awareness not only depends on consolidation within the visual system, but is additionally the result of a post-sensory gating process, which is mediated by higher-level cognitive control mechanisms. We further propose that amplification of visual representations by attentional sensitization is not exclusive to the domain of conscious perception, but also applies to visual stimuli, which remain unconscious. Conscious and unconscious processing modes are highly interdependent with influences in both directions. We therefore argue that exactly this interdependence renders a unified model of conscious and unconscious visual perception valuable. Computational modeling jointly with focused experimental research could lead to a better understanding of the plethora of empirical phenomena in consciousness research. PMID:22253669

Consumer Control Points: Creating a Visual Food Safety Education Model for Consumers.

ERIC Educational Resources Information Center

Schiffman, Carole B.

Consumer education has always been a primary consideration in the prevention of food-borne illness. Using nutrition education and the new food guide as a model, this paper develops suggestions for a framework of microbiological food safety principles and a compatible visual model for communicating key concepts. Historically, visual food guides in…

Evaluation of the 3d Urban Modelling Capabilities in Geographical Information Systems

NASA Astrophysics Data System (ADS)

Dogru, A. O.; Seker, D. Z.

2010-12-01

Geographical Information System (GIS) Technology, which provides successful solutions to basic spatial problems, is currently widely used in 3 dimensional (3D) modeling of physical reality with its developing visualization tools. The modeling of large and complicated phenomenon is a challenging problem in terms of computer graphics currently in use. However, it is possible to visualize that phenomenon in 3D by using computer systems. 3D models are used in developing computer games, military training, urban planning, tourism and etc. The use of 3D models for planning and management of urban areas is very popular issue of city administrations. In this context, 3D City models are produced and used for various purposes. However the requirements of the models vary depending on the type and scope of the application. While a high level visualization, where photorealistic visualization techniques are widely used, is required for touristy and recreational purposes, an abstract visualization of the physical reality is generally sufficient for the communication of the thematic information. The visual variables, which are the principle components of cartographic visualization, such as: color, shape, pattern, orientation, size, position, and saturation are used for communicating the thematic information. These kinds of 3D city models are called as abstract models. Standardization of technologies used for 3D modeling is now available by the use of CityGML. CityGML implements several novel concepts to support interoperability, consistency and functionality. For example it supports different Levels-of-Detail (LoD), which may arise from independent data collection processes and are used for efficient visualization and efficient data analysis. In one CityGML data set, the same object may be represented in different LoD simultaneously, enabling the analysis and visualization of the same object with regard to different degrees of resolution. Furthermore, two CityGML data sets containing the same object in different LoD may be combined and integrated. In this study GIS tools used for 3D modeling issues were examined. In this context, the availability of the GIS tools for obtaining different LoDs of CityGML standard. Additionally a 3D GIS application that covers a small part of the city of Istanbul was implemented for communicating the thematic information rather than photorealistic visualization by using 3D model. An abstract model was created by using a commercial GIS software modeling tools and the results of the implementation were also presented in the study.

GLO-STIX: Graph-Level Operations for Specifying Techniques and Interactive eXploration

PubMed Central

Stolper, Charles D.; Kahng, Minsuk; Lin, Zhiyuan; Foerster, Florian; Goel, Aakash; Stasko, John; Chau, Duen Horng

2015-01-01

The field of graph visualization has produced a wealth of visualization techniques for accomplishing a variety of analysis tasks. Therefore analysts often rely on a suite of different techniques, and visual graph analysis application builders strive to provide this breadth of techniques. To provide a holistic model for specifying network visualization techniques (as opposed to considering each technique in isolation) we present the Graph-Level Operations (GLO) model. We describe a method for identifying GLOs and apply it to identify five classes of GLOs, which can be flexibly combined to re-create six canonical graph visualization techniques. We discuss advantages of the GLO model, including potentially discovering new, effective network visualization techniques and easing the engineering challenges of building multi-technique graph visualization applications. Finally, we implement the GLOs that we identified into the GLO-STIX prototype system that enables an analyst to interactively explore a graph by applying GLOs. PMID:26005315

Texas lignite and the visual resource: an objective approach to visual resource evaluation and management

Treesearch

Harlow C. Landphair

1979-01-01

This paper relates the evolution of an empirical model used to predict public response to scenic quality objectively. The text relates the methods used to develop the visual quality index model, explains the terms used in the equation and briefly illustrates how the model is applied and how it is tested. While the technical application of the model relies heavily on...

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.

A self-organizing model of perisaccadic visual receptive field dynamics in primate visual and oculomotor system.

PubMed

Mender, Bedeho M W; Stringer, Simon M

2015-01-01

We propose and examine a model for how perisaccadic visual receptive field dynamics, observed in a range of primate brain areas such as LIP, FEF, SC, V3, V3A, V2, and V1, may develop through a biologically plausible process of unsupervised visually guided learning. These dynamics are associated with remapping, which is the phenomenon where receptive fields anticipate the consequences of saccadic eye movements. We find that a neural network model using a local associative synaptic learning rule, when exposed to visual scenes in conjunction with saccades, can account for a range of associated phenomena. In particular, our model demonstrates predictive and pre-saccadic remapping, responsiveness shifts around the time of saccades, and remapping from multiple directions.

A self-organizing model of perisaccadic visual receptive field dynamics in primate visual and oculomotor system

PubMed Central

Mender, Bedeho M. W.; Stringer, Simon M.

2015-01-01

We propose and examine a model for how perisaccadic visual receptive field dynamics, observed in a range of primate brain areas such as LIP, FEF, SC, V3, V3A, V2, and V1, may develop through a biologically plausible process of unsupervised visually guided learning. These dynamics are associated with remapping, which is the phenomenon where receptive fields anticipate the consequences of saccadic eye movements. We find that a neural network model using a local associative synaptic learning rule, when exposed to visual scenes in conjunction with saccades, can account for a range of associated phenomena. In particular, our model demonstrates predictive and pre-saccadic remapping, responsiveness shifts around the time of saccades, and remapping from multiple directions. PMID:25717301

Audio visual speech source separation via improved context dependent association model

NASA Astrophysics Data System (ADS)

Kazemi, Alireza; Boostani, Reza; Sobhanmanesh, Fariborz

2014-12-01

In this paper, we exploit the non-linear relation between a speech source and its associated lip video as a source of extra information to propose an improved audio-visual speech source separation (AVSS) algorithm. The audio-visual association is modeled using a neural associator which estimates the visual lip parameters from a temporal context of acoustic observation frames. We define an objective function based on mean square error (MSE) measure between estimated and target visual parameters. This function is minimized for estimation of the de-mixing vector/filters to separate the relevant source from linear instantaneous or time-domain convolutive mixtures. We have also proposed a hybrid criterion which uses AV coherency together with kurtosis as a non-Gaussianity measure. Experimental results are presented and compared in terms of visually relevant speech detection accuracy and output signal-to-interference ratio (SIR) of source separation. The suggested audio-visual model significantly improves relevant speech classification accuracy compared to existing GMM-based model and the proposed AVSS algorithm improves the speech separation quality compared to reference ICA- and AVSS-based methods.

Molecular Dynamics Visualization (MDV): Stereoscopic 3D Display of Biomolecular Structure and Interactions Using the Unity Game Engine.

PubMed

Wiebrands, Michael; Malajczuk, Chris J; Woods, Andrew J; Rohl, Andrew L; Mancera, Ricardo L

2018-06-21

Molecular graphics systems are visualization tools which, upon integration into a 3D immersive environment, provide a unique virtual reality experience for research and teaching of biomolecular structure, function and interactions. We have developed a molecular structure and dynamics application, the Molecular Dynamics Visualization tool, that uses the Unity game engine combined with large scale, multi-user, stereoscopic visualization systems to deliver an immersive display experience, particularly with a large cylindrical projection display. The application is structured to separate the biomolecular modeling and visualization systems. The biomolecular model loading and analysis system was developed as a stand-alone C# library and provides the foundation for the custom visualization system built in Unity. All visual models displayed within the tool are generated using Unity-based procedural mesh building routines. A 3D user interface was built to allow seamless dynamic interaction with the model while being viewed in 3D space. Biomolecular structure analysis and display capabilities are exemplified with a range of complex systems involving cell membranes, protein folding and lipid droplets.

Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons.

PubMed

Zhuang, Chengxu; Wang, Yulong; Yamins, Daniel; Hu, Xiaolin

2017-01-01

Visual information in the visual cortex is processed in a hierarchical manner. Recent studies show that higher visual areas, such as V2, V3, and V4, respond more vigorously to images with naturalistic higher-order statistics than to images lacking them. This property is a functional signature of higher areas, as it is much weaker or even absent in the primary visual cortex (V1). However, the mechanism underlying this signature remains elusive. We studied this problem using computational models. In several typical hierarchical visual models including the AlexNet, VggNet, and SHMAX, this signature was found to be prominent in higher layers but much weaker in lower layers. By changing both the model structure and experimental settings, we found that the signature strongly correlated with sparse firing of units in higher layers but not with any other factors, including model structure, training algorithm (supervised or unsupervised), receptive field size, and property of training stimuli. The results suggest an important role of sparse neuronal activity underlying this special feature of higher visual areas.

Deep Learning Predicts Correlation between a Functional Signature of Higher Visual Areas and Sparse Firing of Neurons

PubMed Central

Zhuang, Chengxu; Wang, Yulong; Yamins, Daniel; Hu, Xiaolin

2017-01-01

Visual information in the visual cortex is processed in a hierarchical manner. Recent studies show that higher visual areas, such as V2, V3, and V4, respond more vigorously to images with naturalistic higher-order statistics than to images lacking them. This property is a functional signature of higher areas, as it is much weaker or even absent in the primary visual cortex (V1). However, the mechanism underlying this signature remains elusive. We studied this problem using computational models. In several typical hierarchical visual models including the AlexNet, VggNet, and SHMAX, this signature was found to be prominent in higher layers but much weaker in lower layers. By changing both the model structure and experimental settings, we found that the signature strongly correlated with sparse firing of units in higher layers but not with any other factors, including model structure, training algorithm (supervised or unsupervised), receptive field size, and property of training stimuli. The results suggest an important role of sparse neuronal activity underlying this special feature of higher visual areas. PMID:29163117

A novel computational model to probe visual search deficits during motor performance

PubMed Central

Singh, Tarkeshwar; Fridriksson, Julius; Perry, Christopher M.; Tryon, Sarah C.; Ross, Angela; Fritz, Stacy

2016-01-01

Successful execution of many motor skills relies on well-organized visual search (voluntary eye movements that actively scan the environment for task-relevant information). Although impairments of visual search that result from brain injuries are linked to diminished motor performance, the neural processes that guide visual search within this context remain largely unknown. The first objective of this study was to examine how visual search in healthy adults and stroke survivors is used to guide hand movements during the Trail Making Test (TMT), a neuropsychological task that is a strong predictor of visuomotor and cognitive deficits. Our second objective was to develop a novel computational model to investigate combinatorial interactions between three underlying processes of visual search (spatial planning, working memory, and peripheral visual processing). We predicted that stroke survivors would exhibit deficits in integrating the three underlying processes, resulting in deteriorated overall task performance. We found that normal TMT performance is associated with patterns of visual search that primarily rely on spatial planning and/or working memory (but not peripheral visual processing). Our computational model suggested that abnormal TMT performance following stroke is associated with impairments of visual search that are characterized by deficits integrating spatial planning and working memory. This innovative methodology provides a novel framework for studying how the neural processes underlying visual search interact combinatorially to guide motor performance. NEW & NOTEWORTHY Visual search has traditionally been studied in cognitive and perceptual paradigms, but little is known about how it contributes to visuomotor performance. We have developed a novel computational model to examine how three underlying processes of visual search (spatial planning, working memory, and peripheral visual processing) contribute to visual search during a visuomotor task. We show that deficits integrating spatial planning and working memory underlie abnormal performance in stroke survivors with frontoparietal damage. PMID:27733596

Visualizing Terrestrial and Aquatic Systems in 3-D

EPA Science Inventory

The environmental modeling community has a long-standing need for affordable, easy-to-use tools that support 3-D visualization of complex spatial and temporal model output. The Visualization of Terrestrial and Aquatic Systems project (VISTAS) aims to help scientists produce effe...

An amodal shared resource model of language-mediated visual attention

PubMed Central

Smith, Alastair C.; Monaghan, Padraic; Huettig, Falk

2013-01-01

Language-mediated visual attention describes the interaction of two fundamental components of the human cognitive system, language and vision. Within this paper we present an amodal shared resource model of language-mediated visual attention that offers a description of the information and processes involved in this complex multimodal behavior and a potential explanation for how this ability is acquired. We demonstrate that the model is not only sufficient to account for the experimental effects of Visual World Paradigm studies but also that these effects are emergent properties of the architecture of the model itself, rather than requiring separate information processing channels or modular processing systems. The model provides an explicit description of the connection between the modality-specific input from language and vision and the distribution of eye gaze in language-mediated visual attention. The paper concludes by discussing future applications for the model, specifically its potential for investigating the factors driving observed individual differences in language-mediated eye gaze. PMID:23966967

Lightness computation by the human visual system

NASA Astrophysics Data System (ADS)

Rudd, Michael E.

2017-05-01

A model of achromatic color computation by the human visual system is presented, which is shown to account in an exact quantitative way for a large body of appearance matching data collected with simple visual displays. The model equations are closely related to those of the original Retinex model of Land and McCann. However, the present model differs in important ways from Land and McCann's theory in that it invokes additional biological and perceptual mechanisms, including contrast gain control, different inherent neural gains for incremental, and decremental luminance steps, and two types of top-down influence on the perceptual weights applied to local luminance steps in the display: edge classification and spatial integration attentional windowing. Arguments are presented to support the claim that these various visual processes must be instantiated by a particular underlying neural architecture. By pointing to correspondences between the architecture of the model and findings from visual neurophysiology, this paper suggests that edge classification involves a top-down gating of neural edge responses in early visual cortex (cortical areas V1 and/or V2) while spatial integration windowing occurs in cortical area V4 or beyond.

Modeling Efficient Serial Visual Search

DTIC Science & Technology

2012-08-01

parafovea size) to explore the parameter space associated with serial search efficiency. Visual search as a paradigm has been studied meticulously for...continues (Over, Hooge , Vlaskamp, & Erkelens, 2007). Over et al. (2007) found that participants initially attended to general properties of the search environ...the efficiency of human serial visual search. There were three parameters that were manipulated in the modeling of the visual search process in this

Impact of oral health education by audio aids, braille and tactile models on the oral health status of visually impaired children of Bhopal City.

PubMed

Gautam, Anjali; Bhambal, Ajay; Moghe, Swapnil

2018-01-01

Children with special needs face unique challenges in day-to-day practice. They are dependent on their close ones for everything. To improve oral hygiene in such visually impaired children, undue training and education are required. Braille is an important language for reading and writing for the visually impaired. It helps them understand and visualize the world via touch. Audio aids are being used to impart health education to the visually impaired. Tactile models help them perceive things which they cannot visualize and hence are an important learning tool. This study aimed to assess the improvement in oral hygiene by audio aids and Braille and tactile models in visually impaired children aged 6-16 years of Bhopal city. This was a prospective study. Sixty visually impaired children aged 6-16 years were selected and randomly divided into three groups (20 children each). Group A: audio aids + Braille, Group B: audio aids + tactile models, and Group C: audio aids + Braille + tactile models. Instructions were given for maintaining good oral hygiene and brushing techniques were explained to all children. After 3 months' time, the oral hygiene status was recorded and compared using plaque and gingival index. ANNOVA test was used. The present study showed a decrease in the mean plaque and gingival scores at all time intervals in individual group as compared to that of the baseline that was statistically significant. The study depicts that the combination of audio aids, Braille and tactile models is an effective way to provide oral health education and improve oral health status of visually impaired children.

Seeing number using texture: How summary statistics account for reductions in perceived numerosity in the visual periphery.

PubMed

Balas, Benjamin

2016-11-01

Peripheral visual perception is characterized by reduced information about appearance due to constraints on how image structure is represented. Visual crowding is a consequence of excessive integration in the visual periphery. Basic phenomenology of visual crowding and other tasks have been successfully accounted for by a summary-statistic model of pooling, suggesting that texture-like processing is useful for how information is reduced in peripheral vision. I attempt to extend the scope of this model by examining a property of peripheral vision: reduced perceived numerosity in the periphery. I demonstrate that a summary-statistic model of peripheral appearance accounts for reduced numerosity in peripherally viewed arrays of randomly placed dots, but does not account for observed effects of dot clustering within such arrays. The model thus offers a limited account of how numerosity is perceived in the visual periphery. I also demonstrate that the model predicts that numerosity estimation is sensitive to element shape, which represents a novel prediction regarding the phenomenology of peripheral numerosity perception. Finally, I discuss ways to extend the model to a broader range of behavior and the potential for using the model to make further predictions about how number is perceived in untested scenarios in peripheral vision.

Self-organization of head-centered visual responses under ecological training conditions.

PubMed

Mender, Bedeho M W; Stringer, Simon M

2014-01-01

We have studied the development of head-centered visual responses in an unsupervised self-organizing neural network model which was trained under ecological training conditions. Four independent spatio-temporal characteristics of the training stimuli were explored to investigate the feasibility of the self-organization under more ecological conditions. First, the number of head-centered visual training locations was varied over a broad range. Model performance improved as the number of training locations approached the continuous sampling of head-centered space. Second, the model depended on periods of time where visual targets remained stationary in head-centered space while it performed saccades around the scene, and the severity of this constraint was explored by introducing increasing levels of random eye movement and stimulus dynamics. Model performance was robust over a range of randomization. Third, the model was trained on visual scenes where multiple simultaneous targets where always visible. Model self-organization was successful, despite never being exposed to a visual target in isolation. Fourth, the duration of fixations during training were made stochastic. With suitable changes to the learning rule, it self-organized successfully. These findings suggest that the fundamental learning mechanism upon which the model rests is robust to the many forms of stimulus variability under ecological training conditions.

The Visual Geophysical Exploration Environment: A Multi-dimensional Scientific Visualization

NASA Astrophysics Data System (ADS)

Pandya, R. E.; Domenico, B.; Murray, D.; Marlino, M. R.

2003-12-01

The Visual Geophysical Exploration Environment (VGEE) is an online learning environment designed to help undergraduate students understand fundamental Earth system science concepts. The guiding principle of the VGEE is the importance of hands-on interaction with scientific visualization and data. The VGEE consists of four elements: 1) an online, inquiry-based curriculum for guiding student exploration; 2) a suite of El Nino-related data sets adapted for student use; 3) a learner-centered interface to a scientific visualization tool; and 4) a set of concept models (interactive tools that help students understand fundamental scientific concepts). There are two key innovations featured in this interactive poster session. One is the integration of concept models and the visualization tool. Concept models are simple, interactive, Java-based illustrations of fundamental physical principles. We developed eight concept models and integrated them into the visualization tool to enable students to probe data. The ability to probe data using a concept model addresses the common problem of transfer: the difficulty students have in applying theoretical knowledge to everyday phenomenon. The other innovation is a visualization environment and data that are discoverable in digital libraries, and installed, configured, and used for investigations over the web. By collaborating with the Integrated Data Viewer developers, we were able to embed a web-launchable visualization tool and access to distributed data sets into the online curricula. The Thematic Real-time Environmental Data Distributed Services (THREDDS) project is working to provide catalogs of datasets that can be used in new VGEE curricula under development. By cataloging this curricula in the Digital Library for Earth System Education (DLESE), learners and educators can discover the data and visualization tool within a framework that guides their use.

Utterance independent bimodal emotion recognition in spontaneous communication

NASA Astrophysics Data System (ADS)

Tao, Jianhua; Pan, Shifeng; Yang, Minghao; Li, Ya; Mu, Kaihui; Che, Jianfeng

2011-12-01

Emotion expressions sometimes are mixed with the utterance expression in spontaneous face-to-face communication, which makes difficulties for emotion recognition. This article introduces the methods of reducing the utterance influences in visual parameters for the audio-visual-based emotion recognition. The audio and visual channels are first combined under a Multistream Hidden Markov Model (MHMM). Then, the utterance reduction is finished by finding the residual between the real visual parameters and the outputs of the utterance related visual parameters. This article introduces the Fused Hidden Markov Model Inversion method which is trained in the neutral expressed audio-visual corpus to solve the problem. To reduce the computing complexity the inversion model is further simplified to a Gaussian Mixture Model (GMM) mapping. Compared with traditional bimodal emotion recognition methods (e.g., SVM, CART, Boosting), the utterance reduction method can give better results of emotion recognition. The experiments also show the effectiveness of our emotion recognition system when it was used in a live environment.

Visual Environment for Rich Data Interpretation (VERDI) program for environmental modeling systems

EPA Pesticide Factsheets

VERDI is a flexible, modular, Java-based program used for visualizing multivariate gridded meteorology, emissions and air quality modeling data created by environmental modeling systems such as the CMAQ model and WRF.

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.

Frontal–Occipital Connectivity During Visual Search

PubMed Central

Pantazatos, Spiro P.; Yanagihara, Ted K.; Zhang, Xian; Meitzler, Thomas

2012-01-01

Abstract Although expectation- and attention-related interactions between ventral and medial prefrontal cortex and stimulus category-selective visual regions have been identified during visual detection and discrimination, it is not known if similar neural mechanisms apply to other tasks such as visual search. The current work tested the hypothesis that high-level frontal regions, previously implicated in expectation and visual imagery of object categories, interact with visual regions associated with object recognition during visual search. Using functional magnetic resonance imaging, subjects searched for a specific object that varied in size and location within a complex natural scene. A model-free, spatial-independent component analysis isolated multiple task-related components, one of which included visual cortex, as well as a cluster within ventromedial prefrontal cortex (vmPFC), consistent with the engagement of both top-down and bottom-up processes. Analyses of psychophysiological interactions showed increased functional connectivity between vmPFC and object-sensitive lateral occipital cortex (LOC), and results from dynamic causal modeling and Bayesian Model Selection suggested bidirectional connections between vmPFC and LOC that were positively modulated by the task. Using image-guided diffusion-tensor imaging, functionally seeded, probabilistic white-matter tracts between vmPFC and LOC, which presumably underlie this effective interconnectivity, were also observed. These connectivity findings extend previous models of visual search processes to include specific frontal–occipital neuronal interactions during a natural and complex search task. PMID:22708993

VISUAL PLUMES MIXING ZONE MODELING SOFTWARE

EPA Science Inventory

The US Environmental Protection Agency has a history of developing plume models and providing technical assistance. The Visual Plumes model (VP) is a recent addition to the public-domain models available on the EPA Center for Exposure Assessment Modeling (CEAM) web page. The Wind...

VISUAL PLUMES MIXING ZONE MODELING SOFTWARE

EPA Science Inventory

The U.S. Environmental Protection Agency has a long history of both supporting plume model development and providing mixing zone modeling software. The Visual Plumes model is the most recent addition to the suite of public-domain models available through the EPA-Athens Center f...

A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets

ERIC Educational Resources Information Center

Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.

2013-01-01

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…

Finding and recognizing objects in natural scenes: complementary computations in the dorsal and ventral visual systems

PubMed Central

Rolls, Edmund T.; Webb, Tristan J.

2014-01-01

Searching for and recognizing objects in complex natural scenes is implemented by multiple saccades until the eyes reach within the reduced receptive field sizes of inferior temporal cortex (IT) neurons. We analyze and model how the dorsal and ventral visual streams both contribute to this. Saliency detection in the dorsal visual system including area LIP is modeled by graph-based visual saliency, and allows the eyes to fixate potential objects within several degrees. Visual information at the fixated location subtending approximately 9° corresponding to the receptive fields of IT neurons is then passed through a four layer hierarchical model of the ventral cortical visual system, VisNet. We show that VisNet can be trained using a synaptic modification rule with a short-term memory trace of recent neuronal activity to capture both the required view and translation invariances to allow in the model approximately 90% correct object recognition for 4 objects shown in any view across a range of 135° anywhere in a scene. The model was able to generalize correctly within the four trained views and the 25 trained translations. This approach analyses the principles by which complementary computations in the dorsal and ventral visual cortical streams enable objects to be located and recognized in complex natural scenes. PMID:25161619

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.

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.

The Mission Planning Lab: A Visualization and Analysis Tool

NASA Technical Reports Server (NTRS)

Daugherty, Sarah C.; Cervantes, Benjamin W.

2009-01-01

Simulation and visualization are powerful decision making tools that are time-saving and cost-effective. Space missions pose testing and e valuation challenges that can be overcome through modeling, simulatio n, and visualization of mission parameters. The National Aeronautics and Space Administration?s (NASA) Wallops Flight Facility (WFF) capi talizes on the benefits of modeling, simulation, and visualization to ols through a project initiative called The Mission Planning Lab (MPL ).

Comprehensive Modeling and Visualization of Cardiac Anatomy and Physiology from CT Imaging and Computer Simulations

PubMed Central

Sun, Peng; Zhou, Haoyin; Ha, Seongmin; Hartaigh, Bríain ó; Truong, Quynh A.; Min, James K.

2016-01-01

In clinical cardiology, both anatomy and physiology are needed to diagnose cardiac pathologies. CT imaging and computer simulations provide valuable and complementary data for this purpose. However, it remains challenging to gain useful information from the large amount of high-dimensional diverse data. The current tools are not adequately integrated to visualize anatomic and physiologic data from a complete yet focused perspective. We introduce a new computer-aided diagnosis framework, which allows for comprehensive modeling and visualization of cardiac anatomy and physiology from CT imaging data and computer simulations, with a primary focus on ischemic heart disease. The following visual information is presented: (1) Anatomy from CT imaging: geometric modeling and visualization of cardiac anatomy, including four heart chambers, left and right ventricular outflow tracts, and coronary arteries; (2) Function from CT imaging: motion modeling, strain calculation, and visualization of four heart chambers; (3) Physiology from CT imaging: quantification and visualization of myocardial perfusion and contextual integration with coronary artery anatomy; (4) Physiology from computer simulation: computation and visualization of hemodynamics (e.g., coronary blood velocity, pressure, shear stress, and fluid forces on the vessel wall). Substantially, feedback from cardiologists have confirmed the practical utility of integrating these features for the purpose of computer-aided diagnosis of ischemic heart disease. PMID:26863663

Visual performance modeling in the human operator simulator

NASA Technical Reports Server (NTRS)

Strieb, M. I.

1979-01-01

A brief description of the history of the development of the human operator simulator (HOS) model is presented. Features of the HOS micromodels that impact on the obtainment of visual performance data are discussed along with preliminary details on a HOS pilot model designed to predict the results of visual performance workload data obtained through oculometer studies on pilots in real and simulated approaches and landings.

Influence of visual clutter on the effect of navigated safety inspection: a case study on elevator installation.

PubMed

Liao, Pin-Chao; Sun, Xinlu; Liu, Mei; Shih, Yu-Nien

2018-01-11

Navigated safety inspection based on task-specific checklists can increase the hazard detection rate, theoretically with interference from scene complexity. Visual clutter, a proxy of scene complexity, can theoretically impair visual search performance, but its impact on the effect of safety inspection performance remains to be explored for the optimization of navigated inspection. This research aims to explore whether the relationship between working memory and hazard detection rate is moderated by visual clutter. Based on a perceptive model of hazard detection, we: (a) developed a mathematical influence model for construction hazard detection; (b) designed an experiment to observe the performance of hazard detection rate with adjusted working memory under different levels of visual clutter, while using an eye-tracking device to observe participants' visual search processes; (c) utilized logistic regression to analyze the developed model under various visual clutter. The effect of a strengthened working memory on the detection rate through increased search efficiency is more apparent in high visual clutter. This study confirms the role of visual clutter in construction-navigated inspections, thus serving as a foundation for the optimization of inspection planning.

Texture-Based Correspondence Display

NASA Technical Reports Server (NTRS)

Gerald-Yamasaki, Michael

2004-01-01

Texture-based correspondence display is a methodology to display corresponding data elements in visual representations of complex multidimensional, multivariate data. Texture is utilized as a persistent medium to contain a visual representation model and as a means to create multiple renditions of data where color is used to identify correspondence. Corresponding data elements are displayed over a variety of visual metaphors in a normal rendering process without adding extraneous linking metadata creation and maintenance. The effectiveness of visual representation for understanding data is extended to the expression of the visual representation model in texture.

Designing multifocal corneal models to correct presbyopia by laser ablation

NASA Astrophysics Data System (ADS)

Alarcón, Aixa; Anera, Rosario G.; Del Barco, Luis Jiménez; Jiménez, José R.

2012-01-01

Two multifocal corneal models and an aspheric model designed to correct presbyopia by corneal photoablation were evaluated. The design of each model was optimized to achieve the best visual quality possible for both near and distance vision. In addition, we evaluated the effect of myosis and pupil decentration on visual quality. The corrected model with the central zone for near vision provides better results since it requires less ablated corneal surface area, permits higher addition values, presents stabler visual quality with pupil-size variations and lower high-order aberrations.

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.

Driver Vision Based Perception-Response Time Prediction and Assistance Model on Mountain Highway Curve.

PubMed

Li, Yi; Chen, Yuren

2016-12-30

To make driving assistance system more humanized, this study focused on the prediction and assistance of drivers' perception-response time on mountain highway curves. Field tests were conducted to collect real-time driving data and driver vision information. A driver-vision lane model quantified curve elements in drivers' vision. A multinomial log-linear model was established to predict perception-response time with traffic/road environment information, driver-vision lane model, and mechanical status (last second). A corresponding assistance model showed a positive impact on drivers' perception-response times on mountain highway curves. Model results revealed that the driver-vision lane model and visual elements did have important influence on drivers' perception-response time. Compared with roadside passive road safety infrastructure, proper visual geometry design, timely visual guidance, and visual information integrality of a curve are significant factors for drivers' perception-response time.

Self-paced model learning for robust visual tracking

NASA Astrophysics Data System (ADS)

Huang, Wenhui; Gu, Jason; Ma, Xin; Li, Yibin

2017-01-01

In visual tracking, learning a robust and efficient appearance model is a challenging task. Model learning determines both the strategy and the frequency of model updating, which contains many details that could affect the tracking results. Self-paced learning (SPL) has recently been attracting considerable interest in the fields of machine learning and computer vision. SPL is inspired by the learning principle underlying the cognitive process of humans, whose learning process is generally from easier samples to more complex aspects of a task. We propose a tracking method that integrates the learning paradigm of SPL into visual tracking, so reliable samples can be automatically selected for model learning. In contrast to many existing model learning strategies in visual tracking, we discover the missing link between sample selection and model learning, which are combined into a single objective function in our approach. Sample weights and model parameters can be learned by minimizing this single objective function. Additionally, to solve the real-valued learning weight of samples, an error-tolerant self-paced function that considers the characteristics of visual tracking is proposed. We demonstrate the robustness and efficiency of our tracker on a recent tracking benchmark data set with 50 video sequences.

Predictors of Visualization: A Structural Equation Model.

ERIC Educational Resources Information Center

Robichaux, Rebecca R.; Guarino, A. J.

This study tested a causal model of the development of spatial visualization based on a synthesis of past and present research. During the summer and fall of 1999, 117 third- and fourth-year undergraduates majoring in architecture, mathematics, mathematics education, and mechanical engineering completed a spatial visualization test and a…

Modeling Spatial and Temporal Aspects of Visual Backward Masking

ERIC Educational Resources Information Center

Hermens, Frouke; Luksys, Gediminas; Gerstner, Wulfram; Herzog, Michael H.; Ernst, Udo

2008-01-01

Visual backward masking is a versatile tool for understanding principles and limitations of visual information processing in the human brain. However, the mechanisms underlying masking are still poorly understood. In the current contribution, the authors show that a structurally simple mathematical model can explain many spatial and temporal…

Feature and Region Selection for Visual Learning.

PubMed

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

VISUAL3D - An EIT network on visualization of geomodels

NASA Astrophysics Data System (ADS)

Bauer, Tobias

2017-04-01

When it comes to interpretation of data and understanding of deep geological structures and bodies at different scales then modelling tools and modelling experience is vital for deep exploration. Geomodelling provides a platform for integration of different types of data, including new kinds of information (e.g., new improved measuring methods). EIT Raw Materials, initiated by the EIT (European Institute of Innovation and Technology) and funded by the European Commission, is the largest and strongest consortium in the raw materials sector worldwide. The VISUAL3D network of infrastructure is an initiative by EIT Raw Materials and aims at bringing together partners with 3D-4D-visualisation infrastructure and 3D-4D-modelling experience. The recently formed network collaboration interlinks hardware, software and expert knowledge in modelling visualization and output. A special focus will be the linking of research, education and industry and integrating multi-disciplinary data and to visualize the data in three and four dimensions. By aiding network collaborations we aim at improving the combination of geomodels with differing file formats and data characteristics. This will create an increased competency in modelling visualization and the ability to interchange and communicate models more easily. By combining knowledge and experience in geomodelling with expertise in Virtual Reality visualization partners of EIT Raw Materials but also external parties will have the possibility to visualize, analyze and validate their geomodels in immersive VR-environments. The current network combines partners from universities, research institutes, geological surveys and industry with a strong background in geological 3D-modelling and 3D visualization and comprises: Luleå University of Technology, Geological Survey of Finland, Geological Survey of Denmark and Greenland, TUBA Freiberg, Uppsala University, Geological Survey of France, RWTH Aachen, DMT, KGHM Cuprum, Boliden, Montan Universität Leoben, Slovenian National Building and Civil Engineering Institute, Tallinn University of Technology and Turku University. The infrastructure within the network comprises different types of capturing and visualization hardware, ranging from high resolution cubes, VR walls, VR goggle solutions, high resolution photogrammetry, UAVs, lidar-scanners, and many more.

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

Keefer, Donald A.; Shaffer, Eric G.; Storsved, Brynne

A free software application, RVA, has been developed as a plugin to the US DOE-funded ParaView visualization package, to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed as an open-source plugin to the 64 bit Windows version of ParaView 3.14. RVA was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing jointmore » visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed on enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.« less

RVA: A Plugin for ParaView 3.14

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

2015-09-04

RVA is a plugin developed for the 64-bit Windows version of the ParaView 3.14 visualization package. RVA is designed to provide support in the visualization and analysis of complex reservoirs being managed using multi-fluid EOR techniques. RVA, for Reservoir Visualization and Analysis, was developed at the University of Illinois at Urbana-Champaign, with contributions from the Illinois State Geological Survey, Department of Computer Science and National Center for Supercomputing Applications. RVA was designed to utilize and enhance the state-of-the-art visualization capabilities within ParaView, readily allowing joint visualization of geologic framework and reservoir fluid simulation model results. Particular emphasis was placed onmore » enabling visualization and analysis of simulation results highlighting multiple fluid phases, multiple properties for each fluid phase (including flow lines), multiple geologic models and multiple time steps. Additional advanced functionality was provided through the development of custom code to implement data mining capabilities. The built-in functionality of ParaView provides the capacity to process and visualize data sets ranging from small models on local desktop systems to extremely large models created and stored on remote supercomputers. The RVA plugin that we developed and the associated User Manual provide improved functionality through new software tools, and instruction in the use of ParaView-RVA, targeted to petroleum engineers and geologists in industry and research. The RVA web site (http://rva.cs.illinois.edu) provides an overview of functions, and the development web site (https://github.com/shaffer1/RVA) provides ready access to the source code, compiled binaries, user manual, and a suite of demonstration data sets. Key functionality has been included to support a range of reservoirs visualization and analysis needs, including: sophisticated connectivity analysis, cross sections through simulation results between selected wells, simplified volumetric calculations, global vertical exaggeration adjustments, ingestion of UTChem simulation results, ingestion of Isatis geostatistical framework models, interrogation of joint geologic and reservoir modeling results, joint visualization and analysis of well history files, location-targeted visualization, advanced correlation analysis, visualization of flow paths, and creation of static images and animations highlighting targeted reservoir features.« less

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.

A picture is worth a thousand words: helping students visualize a conceptual model.

PubMed

Johnson, S E

1989-01-01

Communicating the functional applicability of a conceptual framework to nursing students can be a challenge of considerable magnitude. Nurse educators are convinced that nursing practice and process should stem from theory. However, when attempting to teach this, many educators have struggled with the expressions of confused, skeptical students. To provide a better understanding of a nursing model, the author uses a visual representation of the Neuman Systems Model variables. The student can then visualize application of the Model to nursing practice.

Visual modeling in an analysis of multidimensional data

NASA Astrophysics Data System (ADS)

Zakharova, A. A.; Vekhter, E. V.; Shklyar, A. V.; Pak, A. J.

2018-01-01

The article proposes an approach to solve visualization problems and the subsequent analysis of multidimensional data. Requirements to the properties of visual models, which were created to solve analysis problems, are described. As a perspective direction for the development of visual analysis tools for multidimensional and voluminous data, there was suggested an active use of factors of subjective perception and dynamic visualization. Practical results of solving the problem of multidimensional data analysis are shown using the example of a visual model of empirical data on the current state of studying processes of obtaining silicon carbide by an electric arc method. There are several results of solving this problem. At first, an idea of possibilities of determining the strategy for the development of the domain, secondly, the reliability of the published data on this subject, and changes in the areas of attention of researchers over time.

Simulating Visual Attention Allocation of Pilots in an Advanced Cockpit Environment

NASA Technical Reports Server (NTRS)

Frische, F.; Osterloh, J.-P.; Luedtke, A.

2011-01-01

This paper describes the results of experiments conducted with human line pilots and a cognitive pilot model during interaction with a new 40 Flight Management System (FMS). The aim of these experiments was to gather human pilot behavior data in order to calibrate the behavior of the model. Human behavior is mainly triggered by visual perception. Thus, the main aspect was to setup a profile of human pilots' visual attention allocation in a cockpit environment containing the new FMS. We first performed statistical analyses of eye tracker data and then compared our results to common results of familiar analyses in standard cockpit environments. The comparison has shown a significant influence of the new system on the visual performance of human pilots. Further on, analyses of the pilot models' visual performance have been performed. A comparison to human pilots' visual performance revealed important improvement potentials.

Explore the virtual side of earth science

USGS Publications Warehouse

,

1998-01-01

Scientists have always struggled to find an appropriate technology that could represent three-dimensional (3-D) data, facilitate dynamic analysis, and encourage on-the-fly interactivity. In the recent past, scientific visualization has increased the scientist's ability to visualize information, but it has not provided the interactive environment necessary for rapidly changing the model or for viewing the model in ways not predetermined by the visualization specialist. Virtual Reality Modeling Language (VRML 2.0) is a new environment for visualizing 3-D information spaces and is accessible through the Internet with current browser technologies. Researchers from the U.S. Geological Survey (USGS) are using VRML as a scientific visualization tool to help convey complex scientific concepts to various audiences. Kevin W. Laurent, computer scientist, and Maura J. Hogan, technical information specialist, have created a collection of VRML models available through the Internet at Virtual Earth Science (virtual.er.usgs.gov).

Alerts Visualization and Clustering in Network-based Intrusion Detection

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

Yang, Dr. Li; Gasior, Wade C; Dasireddy, Swetha

2010-04-01

Today's Intrusion detection systems when deployed on a busy network overload the network with huge number of alerts. This behavior of producing too much raw information makes it less effective. We propose a system which takes both raw data and Snort alerts to visualize and analyze possible intrusions in a network. Then we present with two models for the visualization of clustered alerts. Our first model gives the network administrator with the logical topology of the network and detailed information of each node that involves its associated alerts and connections. In the second model, flocking model, presents the network administratormore » with the visual representation of IDS data in which each alert is represented in different color and the alerts with maximum similarity move together. This gives network administrator with the idea of detecting various of intrusions through visualizing the alert patterns.« less

Towards a visual modeling approach to designing microelectromechanical system transducers

NASA Astrophysics Data System (ADS)

Dewey, Allen; Srinivasan, Vijay; Icoz, Evrim

1999-12-01

In this paper, we address initial design capture and system conceptualization of microelectromechanical system transducers based on visual modeling and design. Visual modeling frames the task of generating hardware description language (analog and digital) component models in a manner similar to the task of generating software programming language applications. A structured topological design strategy is employed, whereby microelectromechanical foundry cell libraries are utilized to facilitate the design process of exploring candidate cells (topologies), varying key aspects of the transduction for each topology, and determining which topology best satisfies design requirements. Coupled-energy microelectromechanical system characterizations at a circuit level of abstraction are presented that are based on branch constitutive relations and an overall system of simultaneous differential and algebraic equations. The resulting design methodology is called visual integrated-microelectromechanical VHDL-AMS interactive design (VHDL-AMS is visual hardware design language for analog and mixed signal).

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks.

PubMed

Yap, Florence G H; Yen, Hong-Hsu

2016-12-30

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor's visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs.

Novel Visual Sensor Coverage and Deployment in Time Aware PTZ Wireless Visual Sensor Networks

PubMed Central

Yap, Florence G. H.; Yen, Hong-Hsu

2016-01-01

In this paper, we consider the visual sensor deployment algorithm in Pan-Tilt-Zoom (PTZ) Wireless Visual Sensor Networks (WVSNs). With PTZ capability, a sensor’s visual coverage can be extended to reduce the number of visual sensors that need to be deployed. The coverage zone of a visual sensor in PTZ WVSN is composed of two regions, a Direct Coverage Region (DCR) and a PTZ Coverage Region (PTZCR). In the PTZCR, a visual sensor needs a mechanical pan-tilt-zoom operation to cover an object. This mechanical operation can take seconds, so the sensor might not be able to adjust the camera in time to capture the visual data. In this paper, for the first time, we study this PTZ time-aware PTZ WVSN deployment problem. We formulate this PTZ time-aware PTZ WVSN deployment problem as an optimization problem where the objective is to minimize the total visual sensor deployment cost so that each area is either covered in the DCR or in the PTZCR while considering the PTZ time constraint. The proposed Time Aware Coverage Zone (TACZ) model successfully captures the PTZ visual sensor coverage in terms of camera focal range, angle span zone coverage and camera PTZ time. Then a novel heuristic, called Time Aware Deployment with PTZ camera (TADPTZ) algorithm, is proposed to solve the problem. From our computational experiments, we found out that TACZ model outperforms the existing M coverage model under all network scenarios. In addition, as compared to the optimal solutions, the TACZ model is scalable and adaptable to the different PTZ time requirements when deploying large PTZ WVSNs. PMID:28042829

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.

PROCRU: A model for analyzing crew procedures in approach to landing

NASA Technical Reports Server (NTRS)

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

1980-01-01

A model for analyzing crew procedures in approach to landing is developed. The model employs the information processing structure used in the optimal control model and in recent models for monitoring and failure detection. Mechanisms are added to this basic structure to model crew decision making in this multi task environment. Decisions are based on probability assessments and potential mission impact (or gain). Sub models for procedural activities are included. The model distinguishes among external visual, instrument visual, and auditory sources of information. The external visual scene perception models incorporate limitations in obtaining information. The auditory information channel contains a buffer to allow for storage in memory until that information can be processed.

Learning to rank using user clicks and visual features for image retrieval.

PubMed

Yu, Jun; Tao, Dacheng; Wang, Meng; Rui, Yong

2015-04-01

The inconsistency between textual features and visual contents can cause poor image search results. To solve this problem, click features, which are more reliable than textual information in justifying the relevance between a query and clicked images, are adopted in image ranking model. However, the existing ranking model cannot integrate visual features, which are efficient in refining the click-based search results. In this paper, we propose a novel ranking model based on the learning to rank framework. Visual features and click features are simultaneously utilized to obtain the ranking model. Specifically, the proposed approach is based on large margin structured output learning and the visual consistency is integrated with the click features through a hypergraph regularizer term. In accordance with the fast alternating linearization method, we design a novel algorithm to optimize the objective function. This algorithm alternately minimizes two different approximations of the original objective function by keeping one function unchanged and linearizing the other. We conduct experiments on a large-scale dataset collected from the Microsoft Bing image search engine, and the results demonstrate that the proposed learning to rank models based on visual features and user clicks outperforms state-of-the-art algorithms.

Novel Models of Visual Topographic Map Alignment in the Superior Colliculus

PubMed Central

El-Ghazawi, Tarek A.; Triplett, Jason W.

2016-01-01

The establishment of precise neuronal connectivity during development is critical for sensing the external environment and informing appropriate behavioral responses. In the visual system, many connections are organized topographically, which preserves the spatial order of the visual scene. The superior colliculus (SC) is a midbrain nucleus that integrates visual inputs from the retina and primary visual cortex (V1) to regulate goal-directed eye movements. In the SC, topographically organized inputs from the retina and V1 must be aligned to facilitate integration. Previously, we showed that retinal input instructs the alignment of V1 inputs in the SC in a manner dependent on spontaneous neuronal activity; however, the mechanism of activity-dependent instruction remains unclear. To begin to address this gap, we developed two novel computational models of visual map alignment in the SC that incorporate distinct activity-dependent components. First, a Correlational Model assumes that V1 inputs achieve alignment with established retinal inputs through simple correlative firing mechanisms. A second Integrational Model assumes that V1 inputs contribute to the firing of SC neurons during alignment. Both models accurately replicate in vivo findings in wild type, transgenic and combination mutant mouse models, suggesting either activity-dependent mechanism is plausible. In silico experiments reveal distinct behaviors in response to weakening retinal drive, providing insight into the nature of the system governing map alignment depending on the activity-dependent strategy utilized. Overall, we describe novel computational frameworks of visual map alignment that accurately model many aspects of the in vivo process and propose experiments to test them. PMID:28027309

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.

Descriptive Linear modeling of steady-state visual evoked response

NASA Technical Reports Server (NTRS)

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

1986-01-01

A study is being conducted to explore use of the steady state visual-evoke electrocortical response as an indicator of cognitive task loading. Application of linear descriptive modeling to steady state Visual Evoked Response (VER) data is summarized. Two aspects of linear modeling are reviewed: (1) unwrapping the phase-shift portion of the frequency response, and (2) parsimonious characterization of task-loading effects in terms of changes in model parameters. Model-based phase unwrapping appears to be most reliable in applications, such as manual control, where theoretical models are available. Linear descriptive modeling of the VER has not yet been shown to provide consistent and readily interpretable results.

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.

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).

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.

Pilot/vehicle model analysis of visually guided flight

NASA Technical Reports Server (NTRS)

Zacharias, Greg L.

1991-01-01

Information is given in graphical and outline form on a pilot/vehicle model description, control of altitude with simple terrain clues, simulated flight with visual scene delays, model-based in-cockpit display design, and some thoughts on the role of pilot/vehicle modeling.

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.

Behavior Selection of Mobile Robot Based on Integration of Multimodal Information

NASA Astrophysics Data System (ADS)

Chen, Bin; Kaneko, Masahide

Recently, biologically inspired robots have been developed to acquire the capacity for directing visual attention to salient stimulus generated from the audiovisual environment. On purpose to realize this behavior, a general method is to calculate saliency maps to represent how much the external information attracts the robot's visual attention, where the audiovisual information and robot's motion status should be involved. In this paper, we represent a visual attention model where three modalities, that is, audio information, visual information and robot's motor status are considered, while the previous researches have not considered all of them. Firstly, we introduce a 2-D density map, on which the value denotes how much the robot pays attention to each spatial location. Then we model the attention density using a Bayesian network where the robot's motion statuses are involved. Secondly, the information from both of audio and visual modalities is integrated with the attention density map in integrate-fire neurons. The robot can direct its attention to the locations where the integrate-fire neurons are fired. Finally, the visual attention model is applied to make the robot select the visual information from the environment, and react to the content selected. Experimental results show that it is possible for robots to acquire the visual information related to their behaviors by using the attention model considering motion statuses. The robot can select its behaviors to adapt to the dynamic environment as well as to switch to another task according to the recognition results of visual attention.

Visual Modelling of Learning Processes

ERIC Educational Resources Information Center

Copperman, Elana; Beeri, Catriel; Ben-Zvi, Nava

2007-01-01

This paper introduces various visual models for the analysis and description of learning processes. The models analyse learning on two levels: the dynamic level (as a process over time) and the functional level. Two types of model for dynamic modelling are proposed: the session trace, which documents a specific learner in a particular learning…

[Effect of acupuncture on pattern-visual evoked potential in rats with monocular visual deprivation].

PubMed

Yan, Xing-Ke; Dong, Li-Li; Liu, An-Guo; Wang, Jun-Yan; Ma, Chong-Bing; Zhu, Tian-Tian

2013-08-01

To explore electrophysiology mechanism of acupuncture for treatment and prevention of visual deprivation effect. Eighteen healthy 15-day Evans rats were randomly divided into a normal group, a model group and an acupuncture group, 6 rats in each one. Deprivation amblyopia model was established by monocular eyelid suture in the model group and acupuncture group. Acupuncture was applied at "Jingming" (BL 1), "Chengqi" (ST 1), "Qiuhou" (EX-HN 7) and "Cuanzhu" (BL 2) in the acupuncture group. The bilateral acupoints were selected alternately, one side for a day, and totally 14 days were required. The effect of acupuncture on visual evoked potential in different spatial frequencies was observed. Under three different kinds of spatial frequencies of 2 X 2, 4 X 4 and 8 X 8, compared with normal group, there was obvious visual deprivation effect in the model group where P1 peak latency was delayed (P<0.01) while N1 -P1 amplitude value was decreased (P<0.01). Compared with model group, P1 peak latency was obviously ahead of time (P<0.01) while N1-P1 amplitude value was increased (P<0.01) in the acupuncture group, there was no statistical significance compared with normal group (P>0.05). Under spatial frequency of 4 X 4, N1-P1 amplitude value was maximum in the normal group and acupuncture group. With this spatial frequency the rat's eye had best resolving ability, indicating it could be the best spatial frequency for rat visual system. The visual system has obvious electrophysiology plasticity in sensitive period. Acupuncture treatment could adjust visual deprivation-induced suppression and slow of visual response in order to antagonism deprivation effect.

A neural network model of ventriloquism effect and aftereffect.

PubMed

Magosso, Elisa; Cuppini, Cristiano; Ursino, Mauro

2012-01-01

Presenting simultaneous but spatially discrepant visual and auditory stimuli induces a perceptual translocation of the sound towards the visual input, the ventriloquism effect. General explanation is that vision tends to dominate over audition because of its higher spatial reliability. The underlying neural mechanisms remain unclear. We address this question via a biologically inspired neural network. The model contains two layers of unimodal visual and auditory neurons, with visual neurons having higher spatial resolution than auditory ones. Neurons within each layer communicate via lateral intra-layer synapses; neurons across layers are connected via inter-layer connections. The network accounts for the ventriloquism effect, ascribing it to a positive feedback between the visual and auditory neurons, triggered by residual auditory activity at the position of the visual stimulus. Main results are: i) the less localized stimulus is strongly biased toward the most localized stimulus and not vice versa; ii) amount of the ventriloquism effect changes with visual-auditory spatial disparity; iii) ventriloquism is a robust behavior of the network with respect to parameter value changes. Moreover, the model implements Hebbian rules for potentiation and depression of lateral synapses, to explain ventriloquism aftereffect (that is, the enduring sound shift after exposure to spatially disparate audio-visual stimuli). By adaptively changing the weights of lateral synapses during cross-modal stimulation, the model produces post-adaptive shifts of auditory localization that agree with in-vivo observations. The model demonstrates that two unimodal layers reciprocally interconnected may explain ventriloquism effect and aftereffect, even without the presence of any convergent multimodal area. The proposed study may provide advancement in understanding neural architecture and mechanisms at the basis of visual-auditory integration in the spatial realm.

Computational model for perception of objects and motions.

PubMed

Yang, WenLu; Zhang, LiQing; Ma, LiBo

2008-06-01

Perception of objects and motions in the visual scene is one of the basic problems in the visual system. There exist 'What' and 'Where' pathways in the superior visual cortex, starting from the simple cells in the primary visual cortex. The former is able to perceive objects such as forms, color, and texture, and the latter perceives 'where', for example, velocity and direction of spatial movement of objects. This paper explores brain-like computational architectures of visual information processing. We propose a visual perceptual model and computational mechanism for training the perceptual model. The computational model is a three-layer network. The first layer is the input layer which is used to receive the stimuli from natural environments. The second layer is designed for representing the internal neural information. The connections between the first layer and the second layer, called the receptive fields of neurons, are self-adaptively learned based on principle of sparse neural representation. To this end, we introduce Kullback-Leibler divergence as the measure of independence between neural responses and derive the learning algorithm based on minimizing the cost function. The proposed algorithm is applied to train the basis functions, namely receptive fields, which are localized, oriented, and bandpassed. The resultant receptive fields of neurons in the second layer have the characteristics resembling that of simple cells in the primary visual cortex. Based on these basis functions, we further construct the third layer for perception of what and where in the superior visual cortex. The proposed model is able to perceive objects and their motions with a high accuracy and strong robustness against additive noise. Computer simulation results in the final section show the feasibility of the proposed perceptual model and high efficiency of the learning algorithm.

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.

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.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics.

PubMed

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-10-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation.

Specificity and timescales of cortical adaptation as inferences about natural movie statistics

PubMed Central

Snow, Michoel; Coen-Cagli, Ruben; Schwartz, Odelia

2016-01-01

Adaptation is a phenomenological umbrella term under which a variety of temporal contextual effects are grouped. Previous models have shown that some aspects of visual adaptation reflect optimal processing of dynamic visual inputs, suggesting that adaptation should be tuned to the properties of natural visual inputs. However, the link between natural dynamic inputs and adaptation is poorly understood. Here, we extend a previously developed Bayesian modeling framework for spatial contextual effects to the temporal domain. The model learns temporal statistical regularities of natural movies and links these statistics to adaptation in primary visual cortex via divisive normalization, a ubiquitous neural computation. In particular, the model divisively normalizes the present visual input by the past visual inputs only to the degree that these are inferred to be statistically dependent. We show that this flexible form of normalization reproduces classical findings on how brief adaptation affects neuronal selectivity. Furthermore, prior knowledge acquired by the Bayesian model from natural movies can be modified by prolonged exposure to novel visual stimuli. We show that this updating can explain classical results on contrast adaptation. We also simulate the recent finding that adaptation maintains population homeostasis, namely, a balanced level of activity across a population of neurons with different orientation preferences. Consistent with previous disparate observations, our work further clarifies the influence of stimulus-specific and neuronal-specific normalization signals in adaptation. PMID:27699416

Visual Communication: Its Process and Effects.

ERIC Educational Resources Information Center

Metallinos, Nikos

The process and effects of visual communication are examined in this paper. The first section, "Visual Literacy," discusses the need for a visual literacy involving an understanding of the instruments, materials, and techniques of visual communication media; it then presents and discusses a model illustrating factors involved in the…

Situated sentence processing: the coordinated interplay account and a neurobehavioral model.

PubMed

Crocker, Matthew W; Knoeferle, Pia; Mayberry, Marshall R

2010-03-01

Empirical evidence demonstrating that sentence meaning is rapidly reconciled with the visual environment has been broadly construed as supporting the seamless interaction of visual and linguistic representations during situated comprehension. Based on recent behavioral and neuroscientific findings, however, we argue for the more deeply rooted coordination of the mechanisms underlying visual and linguistic processing, and for jointly considering the behavioral and neural correlates of scene-sentence reconciliation during situated comprehension. The Coordinated Interplay Account (CIA; Knoeferle, P., & Crocker, M. W. (2007). The influence of recent scene events on spoken comprehension: Evidence from eye movements. Journal of Memory and Language, 57(4), 519-543) asserts that incremental linguistic interpretation actively directs attention in the visual environment, thereby increasing the salience of attended scene information for comprehension. We review behavioral and neuroscientific findings in support of the CIA's three processing stages: (i) incremental sentence interpretation, (ii) language-mediated visual attention, and (iii) the on-line influence of non-linguistic visual context. We then describe a recently developed connectionist model which both embodies the central CIA proposals and has been successfully applied in modeling a range of behavioral findings from the visual world paradigm (Mayberry, M. R., Crocker, M. W., & Knoeferle, P. (2009). Learning to attend: A connectionist model of situated language comprehension. Cognitive Science). Results from a new simulation suggest the model also correlates with event-related brain potentials elicited by the immediate use of visual context for linguistic disambiguation (Knoeferle, P., Habets, B., Crocker, M. W., & Münte, T. F. (2008). Visual scenes trigger immediate syntactic reanalysis: Evidence from ERPs during situated spoken comprehension. Cerebral Cortex, 18(4), 789-795). Finally, we argue that the mechanisms underlying interpretation, visual attention, and scene apprehension are not only in close temporal synchronization, but have co-adapted to optimize real-time visual grounding of situated spoken language, thus facilitating the association of linguistic, visual and motor representations that emerge during the course of our embodied linguistic experience in the world. Copyright 2009 Elsevier Inc. All rights reserved.

Spatial Visualization Ability and Impact of Drafting Models: A Quasi Experimental Study

ERIC Educational Resources Information Center

Katsioloudis, Petros J.; Jovanovic, Vukica

2014-01-01

A quasi experimental study was done to determine significant positive effects among three different types of visual models and to identify whether any individual type or combination contributed towards a positive increase of spatial visualization ability for students in engineering technology courses. In particular, the study compared the use of…

The Effects of Solid Modeling and Visualization on Technical Problem Solving

ERIC Educational Resources Information Center

Koch, Douglas

2011-01-01

The purpose of this study was to determine whether or not the use of solid modeling software increases participants' success in solving a specified technical problem and how visualization affects their ability to solve a technical problem. Specifically, the study sought to determine if (a) students' visualization skills affect their problem…

How Spatial Abilities and Dynamic Visualizations Interplay When Learning Functional Anatomy with 3D Anatomical Models

ERIC Educational Resources Information Center

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…

Conceptual Data Visualization in Archival Finding Aids: Preliminary User Responses

ERIC Educational Resources Information Center

Bahde, Anne

2017-01-01

This paper explores possibilities for marrying data visualization to online archival finding aids, which have continually suffered from usability issues in their long history. This paper describes a project in which two different data visualization models were built to replace sections of an archival finding aid. Users were then shown the models,…

Modeling DNA structure and processes through animation and kinesthetic visualizations

NASA Astrophysics Data System (ADS)

Hager, Christine

There have been many studies regarding the effectiveness of visual aids that go beyond that of static illustrations. Many of these have been concentrated on the effectiveness of visual aids such as animations and models or even non-traditional visual aid activities like role-playing activities. This study focuses on the effectiveness of three different types of visual aids: models, animation, and a role-playing activity. Students used a modeling kit made of Styrofoam balls and toothpicks to construct nucleotides and then bond nucleotides together to form DNA. Next, students created their own animation to depict the processes of DNA replication, transcription, and translation. Finally, students worked in teams to build proteins while acting out the process of translation. Students were given a pre- and post-test that measured their knowledge and comprehension of the four topics mentioned above. Results show that there was a significant gain in the post-test scores when compared to the pre-test scores. This indicates that the incorporated visual aids were effective methods for teaching DNA structure and processes.

Interaction Junk: User Interaction-Based Evaluation of Visual Analytic Systems

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

Endert, Alexander; North, Chris

2012-10-14

With the growing need for visualization to aid users in understanding large, complex datasets, the ability for users to interact and explore these datasets is critical. As visual analytic systems have advanced to leverage powerful computational models and data analytics capabilities, the modes by which users engage and interact with the information are limited. Often, users are taxed with directly manipulating parameters of these models through traditional GUIs (e.g., using sliders to directly manipulate the value of a parameter). However, the purpose of user interaction in visual analytic systems is to enable visual data exploration – where users can focusmore » on their task, as opposed to the tool or system. As a result, users can engage freely in data exploration and decision-making, for the purpose of gaining insight. In this position paper, we discuss how evaluating visual analytic systems can be approached through user interaction analysis, where the goal is to minimize the cognitive translation between the visual metaphor and the mode of interaction (i.e., reducing the “Interactionjunk”). We motivate this concept through a discussion of traditional GUIs used in visual analytics for direct manipulation of model parameters, and the importance of designing interactions the support visual data exploration.« less

Theories of Visual Rhetoric: Looking at the Human Genome.

ERIC Educational Resources Information Center

Rosner, Mary

2001-01-01

Considers how visuals are constructions that are products of a writer's interpretation with its own "power-laden agenda." Reviews the current approach taken by composition scholars, surveys richer interdisciplinary work on visuals, and (by using visuals connected with the Human Genome Project) models an analysis of visuals as rhetoric.…

Meaning and Identities: A Visual Performative Pedagogy for Socio-Cultural Learning

ERIC Educational Resources Information Center

Grushka, Kathryn

2009-01-01

In this article I present personalised socio-cultural inquiry in visual art education as a critical and expressive material praxis. The model of "Visual Performative Pedagogy and Communicative Proficiency for the Visual Art Classroom" is presented as a legitimate means of manipulating visual codes, communicating meaning and mediating…

The Levels of Visual Framing

ERIC Educational Resources Information Center

Rodriguez, Lulu; Dimitrova, Daniela V.

2011-01-01

While framing research has centered mostly on the evaluations of media texts, visual news discourse has remained relatively unexamined. This study surveys the visual framing techniques and methods employed in previous studies and proposes a four-tiered model of identifying and analyzing visual frames: (1) visuals as denotative systems, (2) visuals…

Differences in Visual-Spatial Input May Underlie Different Compression Properties of Firing Fields for Grid Cell Modules in Medial Entorhinal Cortex

PubMed Central

Raudies, Florian; Hasselmo, Michael E.

2015-01-01

Firing fields of grid cells in medial entorhinal cortex show compression or expansion after manipulations of the location of environmental barriers. This compression or expansion could be selective for individual grid cell modules with particular properties of spatial scaling. We present a model for differences in the response of modules to barrier location that arise from different mechanisms for the influence of visual features on the computation of location that drives grid cell firing patterns. These differences could arise from differences in the position of visual features within the visual field. When location was computed from the movement of visual features on the ground plane (optic flow) in the ventral visual field, this resulted in grid cell spatial firing that was not sensitive to barrier location in modules modeled with small spacing between grid cell firing fields. In contrast, when location was computed from static visual features on walls of barriers, i.e. in the more dorsal visual field, this resulted in grid cell spatial firing that compressed or expanded based on the barrier locations in modules modeled with large spacing between grid cell firing fields. This indicates that different grid cell modules might have differential properties for computing location based on visual cues, or the spatial radius of sensitivity to visual cues might differ between modules. PMID:26584432

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.

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

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

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.

Effects of aging on audio-visual speech integration.

PubMed

Huyse, Aurélie; Leybaert, Jacqueline; Berthommier, Frédéric

2014-10-01

This study investigated the impact of aging on audio-visual speech integration. A syllable identification task was presented in auditory-only, visual-only, and audio-visual congruent and incongruent conditions. Visual cues were either degraded or unmodified. Stimuli were embedded in stationary noise alternating with modulated noise. Fifteen young adults and 15 older adults participated in this study. Results showed that older adults had preserved lipreading abilities when the visual input was clear but not when it was degraded. The impact of aging on audio-visual integration also depended on the quality of the visual cues. In the visual clear condition, the audio-visual gain was similar in both groups and analyses in the framework of the fuzzy-logical model of perception confirmed that older adults did not differ from younger adults in their audio-visual integration abilities. In the visual reduction condition, the audio-visual gain was reduced in the older group, but only when the noise was stationary, suggesting that older participants could compensate for the loss of lipreading abilities by using the auditory information available in the valleys of the noise. The fuzzy-logical model of perception confirmed the significant impact of aging on audio-visual integration by showing an increased weight of audition in the older group.

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

Gestalt isomorphism and the primacy of subjective conscious experience: a Gestalt Bubble model.

PubMed

Lehar, Steven

2003-08-01

A serious crisis is identified in theories of neurocomputation, marked by a persistent disparity between the phenomenological or experiential account of visual perception and the neurophysiological level of description of the visual system. In particular, conventional concepts of neural processing offer no explanation for the holistic global aspects of perception identified by Gestalt theory. The problem is paradigmatic and can be traced to contemporary concepts of the functional role of the neural cell, known as the Neuron Doctrine. In the absence of an alternative neurophysiologically plausible model, I propose a perceptual modeling approach, to model the percept as experienced subjectively, rather than modeling the objective neurophysiological state of the visual system that supposedly subserves that experience. A Gestalt Bubble model is presented to demonstrate how the elusive Gestalt principles of emergence, reification, and invariance can be expressed in a quantitative model of the subjective experience of visual consciousness. That model in turn reveals a unique computational strategy underlying visual processing, which is unlike any algorithm devised by man, and certainly unlike the atomistic feed-forward model of neurocomputation offered by the Neuron Doctrine paradigm. The perceptual modeling approach reveals the primary function of perception as that of generating a fully spatial virtual-reality replica of the external world in an internal representation. The common objections to this "picture-in-the-head" concept of perceptual representation are shown to be ill founded.

A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields

PubMed Central

Cocchi, Luca; Sale, Martin V; L Gollo, Leonardo; Bell, Peter T; Nguyen, Vinh T; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B

2016-01-01

Within the primate visual system, areas at lower levels of the cortical hierarchy process basic visual features, whereas those at higher levels, such as the frontal eye fields (FEF), are thought to modulate sensory processes via feedback connections. Despite these functional exchanges during perception, there is little shared activity between early and late visual regions at rest. How interactions emerge between regions encompassing distinct levels of the visual hierarchy remains unknown. Here we combined neuroimaging, non-invasive cortical stimulation and computational modelling to characterize changes in functional interactions across widespread neural networks before and after local inhibition of primary visual cortex or FEF. We found that stimulation of early visual cortex selectively increased feedforward interactions with FEF and extrastriate visual areas, whereas identical stimulation of the FEF decreased feedback interactions with early visual areas. Computational modelling suggests that these opposing effects reflect a fast-slow timescale hierarchy from sensory to association areas. DOI: http://dx.doi.org/10.7554/eLife.15252.001 PMID:27596931

A hierarchy of timescales explains distinct effects of local inhibition of primary visual cortex and frontal eye fields.

PubMed

Cocchi, Luca; Sale, Martin V; L Gollo, Leonardo; Bell, Peter T; Nguyen, Vinh T; Zalesky, Andrew; Breakspear, Michael; Mattingley, Jason B

2016-09-06

Within the primate visual system, areas at lower levels of the cortical hierarchy process basic visual features, whereas those at higher levels, such as the frontal eye fields (FEF), are thought to modulate sensory processes via feedback connections. Despite these functional exchanges during perception, there is little shared activity between early and late visual regions at rest. How interactions emerge between regions encompassing distinct levels of the visual hierarchy remains unknown. Here we combined neuroimaging, non-invasive cortical stimulation and computational modelling to characterize changes in functional interactions across widespread neural networks before and after local inhibition of primary visual cortex or FEF. We found that stimulation of early visual cortex selectively increased feedforward interactions with FEF and extrastriate visual areas, whereas identical stimulation of the FEF decreased feedback interactions with early visual areas. Computational modelling suggests that these opposing effects reflect a fast-slow timescale hierarchy from sensory to association areas.

[The relationship between eyeball structure and visual acuity in high myopia].

PubMed

Liu, Yi-Chang; Xia, Wen-Tao; Zhu, Guang-You; Zhou, Xing-Tao; Fan, Li-Hua; Liu, Rui-Jue; Chen, Jie-Min

2010-06-01

To explore the relationship between eyeball structure and visual acuity in high myopia. Totally, 152 people (283 eyeballs) with different levels of myopia were tested for visual acuity, axial length, and fundus. All cases were classified according to diopter, axial length, and fundus. The relationships between diopter, axial length, fundus and visual acuity were studied. The mathematical models were established for visual acuity and eyeball structure markers. The visual acuity showed a moderate correlation with fundus class, comus, axial length and diopter ([r] > 0.4, P < 0.000 1). The visual acuity in people with the axial length longer than 30.00 mm, diopter above -20.00 D and fundus in 4th class were mostly below 0.5. The mathematical models were established by visual acuity and eyeball structure markers. The visual acuity should decline with axial length extension, diopter deepening and pathological deterioration of fundus. To detect the structure changes by combining different kinds of objective methods can help to assess and to judge the vision in high myopia.

A Web-based Visualization System for Three Dimensional Geological Model using Open GIS

NASA Astrophysics Data System (ADS)

Nemoto, T.; Masumoto, S.; Nonogaki, S.

2017-12-01

A three dimensional geological model is an important information in various fields such as environmental assessment, urban planning, resource development, waste management and disaster mitigation. In this study, we have developed a web-based visualization system for 3D geological model using free and open source software. The system has been successfully implemented by integrating web mapping engine MapServer and geographic information system GRASS. MapServer plays a role of mapping horizontal cross sections of 3D geological model and a topographic map. GRASS provides the core components for management, analysis and image processing of the geological model. Online access to GRASS functions has been enabled using PyWPS that is an implementation of WPS (Web Processing Service) Open Geospatial Consortium (OGC) standard. The system has two main functions. Two dimensional visualization function allows users to generate horizontal and vertical cross sections of 3D geological model. These images are delivered via WMS (Web Map Service) and WPS OGC standards. Horizontal cross sections are overlaid on the topographic map. A vertical cross section is generated by clicking a start point and an end point on the map. Three dimensional visualization function allows users to visualize geological boundary surfaces and a panel diagram. The user can visualize them from various angles by mouse operation. WebGL is utilized for 3D visualization. WebGL is a web technology that brings hardware-accelerated 3D graphics to the browser without installing additional software. The geological boundary surfaces can be downloaded to incorporate the geologic structure in a design on CAD and model for various simulations. This study was supported by JSPS KAKENHI Grant Number JP16K00158.

An Introductory Classroom Exercise on Protein Molecular Model Visualization and Detailed Analysis of Protein-Ligand Binding

ERIC Educational Resources Information Center

Poeylaut-Palena, Andres, A.; de los Angeles Laborde, Maria

2013-01-01

A learning module for molecular level analysis of protein structure and ligand/drug interaction through the visualization of X-ray diffraction is presented. Using DeepView as molecular model visualization software, students learn about the general concepts of protein structure. This Biochemistry classroom exercise is designed to be carried out by…

Visualisierungen im Lehr-Lern-Process (Visualizations in the Process of Teaching and Learning).

ERIC Educational Resources Information Center

Schnotz, Wolfgang; Zink, Thomas; Pfeiffer, Michael

1996-01-01

Discusses the role of visualization of information in learning. Theorizes that the comprehension of visualizations is a process of structure mapping between a visuo-spatial configuration and a mental model. Tests the model and finds differences in the use of text and picture information to answer different kinds of text questions. (DSK)

Integration of visual and motion cues for flight simulator requirements and ride quality investigation

NASA Technical Reports Server (NTRS)

Young, L. R.

1976-01-01

Investigations for the improvement of flight simulators are reported. Topics include: visual cues in landing, comparison of linear and nonlinear washout filters using a model of the vestibular system, and visual vestibular interactions (yaw axis). An abstract is given for a thesis on the applications of human dynamic orientation models to motion simulation.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet

PubMed Central

Rolls, Edmund T.

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus. PMID:22723777

Dynamic interactions between visual working memory and saccade target selection

PubMed Central

Schneegans, Sebastian; Spencer, John P.; Schöner, Gregor; Hwang, Seongmin; Hollingworth, Andrew

2014-01-01

Recent psychophysical experiments have shown that working memory for visual surface features interacts with saccadic motor planning, even in tasks where the saccade target is unambiguously specified by spatial cues. Specifically, a match between a memorized color and the color of either the designated target or a distractor stimulus influences saccade target selection, saccade amplitudes, and latencies in a systematic fashion. To elucidate these effects, we present a dynamic neural field model in combination with new experimental data. The model captures the neural processes underlying visual perception, working memory, and saccade planning relevant to the psychophysical experiment. It consists of a low-level visual sensory representation that interacts with two separate pathways: a spatial pathway implementing spatial attention and saccade generation, and a surface feature pathway implementing color working memory and feature attention. Due to bidirectional coupling between visual working memory and feature attention in the model, the working memory content can indirectly exert an effect on perceptual processing in the low-level sensory representation. This in turn biases saccadic movement planning in the spatial pathway, allowing the model to quantitatively reproduce the observed interaction effects. The continuous coupling between representations in the model also implies that modulation should be bidirectional, and model simulations provide specific predictions for complementary effects of saccade target selection on visual working memory. These predictions were empirically confirmed in a new experiment: Memory for a sample color was biased toward the color of a task-irrelevant saccade target object, demonstrating the bidirectional coupling between visual working memory and perceptual processing. PMID:25228628

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.

Invariant Visual Object and Face Recognition: Neural and Computational Bases, and a Model, VisNet.

PubMed

Rolls, Edmund T

2012-01-01

Neurophysiological evidence for invariant representations of objects and faces in the primate inferior temporal visual cortex is described. Then a computational approach to how invariant representations are formed in the brain is described that builds on the neurophysiology. A feature hierarchy model in which invariant representations can be built by self-organizing learning based on the temporal and spatial statistics of the visual input produced by objects as they transform in the world is described. VisNet can use temporal continuity in an associative synaptic learning rule with a short-term memory trace, and/or it can use spatial continuity in continuous spatial transformation learning which does not require a temporal trace. The model of visual processing in the ventral cortical stream can build representations of objects that are invariant with respect to translation, view, size, and also lighting. The model has been extended to provide an account of invariant representations in the dorsal visual system of the global motion produced by objects such as looming, rotation, and object-based movement. The model has been extended to incorporate top-down feedback connections to model the control of attention by biased competition in, for example, spatial and object search tasks. The approach has also been extended to account for how the visual system can select single objects in complex visual scenes, and how multiple objects can be represented in a scene. The approach has also been extended to provide, with an additional layer, for the development of representations of spatial scenes of the type found in the hippocampus.

Coherence in the Visual Imagination.

PubMed

Vertolli, Michael O; Kelly, Matthew A; Davies, Jim

2018-04-01

An incoherent visualization is when aspects of different senses of a word (e.g., the biological "mouse" vs. the computer "mouse") are present in the same visualization (e.g., a visualization of a biological mouse in the same image with a computer tower). We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show that co-occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C 3 model of concept combination created by Costello and Keane (2000). We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial. Copyright © 2017 Cognitive Science Society, Inc.

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

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).

Physically-based in silico light sheet microscopy for visualizing fluorescent brain models

PubMed Central

2015-01-01

Background We present a physically-based computational model of the light sheet fluorescence microscope (LSFM). Based on Monte Carlo ray tracing and geometric optics, our method simulates the operational aspects and image formation process of the LSFM. This simulated, in silico LSFM creates synthetic images of digital fluorescent specimens that can resemble those generated by a real LSFM, as opposed to established visualization methods producing visually-plausible images. We also propose an accurate fluorescence rendering model which takes into account the intrinsic characteristics of fluorescent dyes to simulate the light interaction with fluorescent biological specimen. Results We demonstrate first results of our visualization pipeline to a simplified brain tissue model reconstructed from the somatosensory cortex of a young rat. The modeling aspects of the LSFM units are qualitatively analysed, and the results of the fluorescence model were quantitatively validated against the fluorescence brightness equation and characteristic emission spectra of different fluorescent dyes. AMS subject classification Modelling and simulation PMID:26329404

Enhanced HMAX model with feedforward feature learning for multiclass categorization.

PubMed

Li, Yinlin; Wu, Wei; Zhang, Bo; Li, Fengfu

2015-01-01

In recent years, the interdisciplinary research between neuroscience and computer vision has promoted the development in both fields. Many biologically inspired visual models are proposed, and among them, the Hierarchical Max-pooling model (HMAX) is a feedforward model mimicking the structures and functions of V1 to posterior inferotemporal (PIT) layer of the primate visual cortex, which could generate a series of position- and scale- invariant features. However, it could be improved with attention modulation and memory processing, which are two important properties of the primate visual cortex. Thus, in this paper, based on recent biological research on the primate visual cortex, we still mimic the first 100-150 ms of visual cognition to enhance the HMAX model, which mainly focuses on the unsupervised feedforward feature learning process. The main modifications are as follows: (1) To mimic the attention modulation mechanism of V1 layer, a bottom-up saliency map is computed in the S1 layer of the HMAX model, which can support the initial feature extraction for memory processing; (2) To mimic the learning, clustering and short-term memory to long-term memory conversion abilities of V2 and IT, an unsupervised iterative clustering method is used to learn clusters with multiscale middle level patches, which are taken as long-term memory; (3) Inspired by the multiple feature encoding mode of the primate visual cortex, information including color, orientation, and spatial position are encoded in different layers of the HMAX model progressively. By adding a softmax layer at the top of the model, multiclass categorization experiments can be conducted, and the results on Caltech101 show that the enhanced model with a smaller memory size exhibits higher accuracy than the original HMAX model, and could also achieve better accuracy than other unsupervised feature learning methods in multiclass categorization task.

A study of the laminar separation bubble on an airfoil at low Reynolds numbers using flow visualization techniques

NASA Technical Reports Server (NTRS)

Schmidt, Gordon S.; Mueller, Thomas J.

1987-01-01

The use of flow visualization to study separation bubbles is evaluated. The wind tunnel, two NACA 66(3)-018 airfoil models, and kerosene vapor, titanium tetrachloride, and surface flow visualizations techniques are described. The application of the three visualization techniques to the two airfoil models reveals that the smoke and vapor techniques provide data on the location of laminar separation and the onset of transition, and the surface method produces information about the location of turbulent boundary layer separation. The data obtained with the three flow visualization techniques are compared to pressure distribution data and good correlation is detected. It is noted that flow visualization is an effective technique for examining separation bubbles.

Elementary Teachers' Selection and Use of Visual Models

ERIC Educational Resources Information Center

Lee, Tammy D.; Jones, M. Gail

2018-01-01

As science grows in complexity, science teachers face an increasing challenge of helping students interpret models that represent complex science systems. Little is known about how teachers select and use models when planning lessons. This mixed methods study investigated the pedagogical approaches and visual models used by elementary in-service…

A medaka model of cancer allowing direct observation of transplanted tumor cells in vivo at a cellular-level resolution.

PubMed

Hasegawa, Sumitaka; Maruyama, Kouichi; Takenaka, Hikaru; Furukawa, Takako; Saga, Tsuneo

2009-08-18

The recent success with small fish as an animal model of cancer with the aid of fluorescence technique has attracted cancer modelers' attention because it would be possible to directly visualize tumor cells in vivo in real time. Here, we report a medaka model capable of allowing the observation of various cell behaviors of transplanted tumor cells, such as cell proliferation and metastasis, which were visualized easily in vivo. We established medaka melanoma (MM) cells stably expressing GFP and transplanted them into nonirradiated and irradiated medaka. The tumor cells were grown at the injection sites in medaka, and the spatiotemporal changes were visualized under a fluorescence stereoscopic microscope at a cellular-level resolution, and even at a single-cell level. Tumor dormancy and metastasis were also observed. Interestingly, in irradiated medaka, accelerated tumor growth and metastasis of the transplanted tumor cells were directly visualized. Our medaka model provides an opportunity to visualize in vivo tumor cells "as seen in a culture dish" and would be useful for in vivo tumor cell biology.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

DOE PAGES

Christensen, A. J.; Srinivasan, V.; Hart, J. C.; ...

2018-03-17

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

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

Christensen, A. J.; Srinivasan, V.; Hart, J. C.

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have ledmore » to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. Lastly, this survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.« less

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security.

PubMed

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-05-01

Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in "big data" analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields.

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.

Use of computational modeling combined with advanced visualization to develop strategies for the design of crop ideotypes to address food security

PubMed Central

Christensen, A J; Srinivasan, Venkatraman; Hart, John C; Marshall-Colon, Amy

2018-01-01

Abstract Sustainable crop production is a contributing factor to current and future food security. Innovative technologies are needed to design strategies that will achieve higher crop yields on less land and with fewer resources. Computational modeling coupled with advanced scientific visualization enables researchers to explore and interact with complex agriculture, nutrition, and climate data to predict how crops will respond to untested environments. These virtual observations and predictions can direct the development of crop ideotypes designed to meet future yield and nutritional demands. This review surveys modeling strategies for the development of crop ideotypes and scientific visualization technologies that have led to discoveries in “big data” analysis. Combined modeling and visualization approaches have been used to realistically simulate crops and to guide selection that immediately enhances crop quantity and quality under challenging environmental conditions. This survey of current and developing technologies indicates that integrative modeling and advanced scientific visualization may help overcome challenges in agriculture and nutrition data as large-scale and multidimensional data become available in these fields. PMID:29562368

A deep (learning) dive into visual search behaviour of breast radiologists

NASA Astrophysics Data System (ADS)

Mall, Suneeta; Brennan, Patrick C.; Mello-Thoms, Claudia

2018-03-01

Visual search, the process of detecting and identifying objects using the eye movements (saccades) and the foveal vision, has been studied for identification of root causes of errors in the interpretation of mammography. The aim of this study is to model visual search behaviour of radiologists and their interpretation of mammograms using deep machine learning approaches. Our model is based on a deep convolutional neural network, a biologically-inspired multilayer perceptron that simulates the visual cortex, and is reinforced with transfer learning techniques. Eye tracking data obtained from 8 radiologists (of varying experience levels in reading mammograms) reviewing 120 two-view digital mammography cases (59 cancers) have been used to train the model, which was pre-trained with the ImageNet dataset for transfer learning. Areas of the mammogram that received direct (foveally fixated), indirect (peripherally fixated) or no (never fixated) visual attention were extracted from radiologists' visual search maps (obtained by a head mounted eye tracking device). These areas, along with the radiologists' assessment (including confidence of the assessment) of suspected malignancy were used to model: 1) Radiologists' decision; 2) Radiologists' confidence on such decision; and 3) The attentional level (i.e. foveal, peripheral or none) obtained by an area of the mammogram. Our results indicate high accuracy and low misclassification in modelling such behaviours.

Modeling of pilot's visual behavior for low-level flight

NASA Astrophysics Data System (ADS)

Schulte, Axel; Onken, Reiner

1995-06-01

Developers of synthetic vision systems for low-level flight simulators deal with the problem to decide which features to incorporate in order to achieve most realistic training conditions. This paper supports an approach to this problem on the basis of modeling the pilot's visual behavior. This approach is founded upon the basic requirement that the pilot's mechanisms of visual perception should be identical in simulated and real low-level flight. Flight simulator experiments with pilots were conducted for knowledge acquisition. During the experiments video material of a real low-level flight mission containing different situations was displayed to the pilot who was acting under a realistic mission assignment in a laboratory environment. Pilot's eye movements could be measured during the replay. The visual mechanisms were divided into rule based strategies for visual navigation, based on the preflight planning process, as opposed to skill based processes. The paper results in a model of the pilot's planning strategy of a visual fixing routine as part of the navigation task. The model is a knowledge based system based upon the fuzzy evaluation of terrain features in order to determine the landmarks used by pilots. It can be shown that a computer implementation of the model selects those features, which were preferred by trained pilots, too.

There's Waldo! A Normalization Model of Visual Search Predicts Single-Trial Human Fixations in an Object Search Task

PubMed Central

Miconi, Thomas; Groomes, Laura; Kreiman, Gabriel

2016-01-01

When searching for an object in a scene, how does the brain decide where to look next? Visual search theories suggest the existence of a global “priority map” that integrates bottom-up visual information with top-down, target-specific signals. We propose a mechanistic model of visual search that is consistent with recent neurophysiological evidence, can localize targets in cluttered images, and predicts single-trial behavior in a search task. This model posits that a high-level retinotopic area selective for shape features receives global, target-specific modulation and implements local normalization through divisive inhibition. The normalization step is critical to prevent highly salient bottom-up features from monopolizing attention. The resulting activity pattern constitues a priority map that tracks the correlation between local input and target features. The maximum of this priority map is selected as the locus of attention. The visual input is then spatially enhanced around the selected location, allowing object-selective visual areas to determine whether the target is present at this location. This model can localize objects both in array images and when objects are pasted in natural scenes. The model can also predict single-trial human fixations, including those in error and target-absent trials, in a search task involving complex objects. PMID:26092221

The Perceptual Root of Object-Based Storage: An Interactive Model of Perception and Visual Working Memory

ERIC Educational Resources Information Center

Gao, Tao; Gao, Zaifeng; Li, Jie; Sun, Zhongqiang; Shen, Mowei

2011-01-01

Mainstream theories of visual perception assume that visual working memory (VWM) is critical for integrating online perceptual information and constructing coherent visual experiences in changing environments. Given the dynamic interaction between online perception and VWM, we propose that how visual information is processed during visual…

Beyond Control Panels: Direct Manipulation for Visual Analytics

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

Endert, Alexander; Bradel, Lauren; North, Chris

2013-07-19

Information Visualization strives to provide visual representations through which users can think about and gain insight into information. By leveraging the visual and cognitive systems of humans, complex relationships and phenomena occurring within datasets can be uncovered by exploring information visually. Interaction metaphors for such visualizations are designed to enable users direct control over the filters, queries, and other parameters controlling how the data is visually represented. Through the evolution of information visualization, more complex mathematical and data analytic models are being used to visualize relationships and patterns in data – creating the field of Visual Analytics. However, the expectationsmore » for how users interact with these visualizations has remained largely unchanged – focused primarily on the direct manipulation of parameters of the underlying mathematical models. In this article we present an opportunity to evolve the methodology for user interaction from the direct manipulation of parameters through visual control panels, to interactions designed specifically for visual analytic systems. Instead of focusing on traditional direct manipulation of mathematical parameters, the evolution of the field can be realized through direct manipulation within the visual representation – where users can not only gain insight, but also interact. This article describes future directions and research challenges that fundamentally change the meaning of direct manipulation with regards to visual analytics, advancing the Science of Interaction.« less

Gaze distribution analysis and saliency prediction across age groups.

PubMed

Krishna, Onkar; Helo, Andrea; Rämä, Pia; Aizawa, Kiyoharu

2018-01-01

Knowledge of the human visual system helps to develop better computational models of visual attention. State-of-the-art models have been developed to mimic the visual attention system of young adults that, however, largely ignore the variations that occur with age. In this paper, we investigated how visual scene processing changes with age and we propose an age-adapted framework that helps to develop a computational model that can predict saliency across different age groups. Our analysis uncovers how the explorativeness of an observer varies with age, how well saliency maps of an age group agree with fixation points of observers from the same or different age groups, and how age influences the center bias tendency. We analyzed the eye movement behavior of 82 observers belonging to four age groups while they explored visual scenes. Explorative- ness was quantified in terms of the entropy of a saliency map, and area under the curve (AUC) metrics was used to quantify the agreement analysis and the center bias tendency. Analysis results were used to develop age adapted saliency models. Our results suggest that the proposed age-adapted saliency model outperforms existing saliency models in predicting the regions of interest across age groups.

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.

Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

PubMed Central

Quillin, Kim; Thomas, Stephen

2015-01-01

The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

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.

3D Visualization of Global Ocean Circulation

NASA Astrophysics Data System (ADS)

Nelson, V. G.; Sharma, R.; Zhang, E.; Schmittner, A.; Jenny, B.

2015-12-01

Advanced 3D visualization techniques are seldom used to explore the dynamic behavior of ocean circulation. Streamlines are an effective method for visualization of flow, and they can be designed to clearly show the dynamic behavior of a fluidic system. We employ vector field editing and extraction software to examine the topology of velocity vector fields generated by a 3D global circulation model coupled to a one-layer atmosphere model simulating preindustrial and last glacial maximum (LGM) conditions. This results in a streamline-based visualization along multiple density isosurfaces on which we visualize points of vertical exchange and the distribution of properties such as temperature and biogeochemical tracers. Previous work involving this model examined the change in the energetics driving overturning circulation and mixing between simulations of LGM and preindustrial conditions. This visualization elucidates the relationship between locations of vertical exchange and mixing, as well as demonstrates the effects of circulation and mixing on the distribution of tracers such as carbon isotopes.

High-resolution remotely sensed small target detection by imitating fly visual perception mechanism.

PubMed

Huang, Fengchen; Xu, Lizhong; Li, Min; Tang, Min

2012-01-01

The difficulty and limitation of small target detection methods for high-resolution remote sensing data have been a recent research hot spot. Inspired by the information capture and processing theory of fly visual system, this paper endeavors to construct a characterized model of information perception and make use of the advantages of fast and accurate small target detection under complex varied nature environment. The proposed model forms a theoretical basis of small target detection for high-resolution remote sensing data. After the comparison of prevailing simulation mechanism behind fly visual systems, we propose a fly-imitated visual system method of information processing for high-resolution remote sensing data. A small target detector and corresponding detection algorithm are designed by simulating the mechanism of information acquisition, compression, and fusion of fly visual system and the function of pool cell and the character of nonlinear self-adaption. Experiments verify the feasibility and rationality of the proposed small target detection model and fly-imitated visual perception method.

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.

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.

An Analysis of Machine- and Human-Analytics in Classification.

PubMed

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

NCWin — A Component Object Model (COM) for processing and visualizing NetCDF data

USGS Publications Warehouse

Liu, Jinxun; Chen, J.M.; Price, D.T.; Liu, S.

2005-01-01

NetCDF (Network Common Data Form) is a data sharing protocol and library that is commonly used in large-scale atmospheric and environmental data archiving and modeling. The NetCDF tool described here, named NCWin and coded with Borland C + + Builder, was built as a standard executable as well as a COM (component object model) for the Microsoft Windows environment. COM is a powerful technology that enhances the reuse of applications (as components). Environmental model developers from different modeling environments, such as Python, JAVA, VISUAL FORTRAN, VISUAL BASIC, VISUAL C + +, and DELPHI, can reuse NCWin in their models to read, write and visualize NetCDF data. Some Windows applications, such as ArcGIS and Microsoft PowerPoint, can also call NCWin within the application. NCWin has three major components: 1) The data conversion part is designed to convert binary raw data to and from NetCDF data. It can process six data types (unsigned char, signed char, short, int, float, double) and three spatial data formats (BIP, BIL, BSQ); 2) The visualization part is designed for displaying grid map series (playing forward or backward) with simple map legend, and displaying temporal trend curves for data on individual map pixels; and 3) The modeling interface is designed for environmental model development by which a set of integrated NetCDF functions is provided for processing NetCDF data. To demonstrate that the NCWin can easily extend the functions of some current GIS software and the Office applications, examples of calling NCWin within ArcGIS and MS PowerPoint for showing NetCDF map animations are given.

Comparison of L-system applications towards plant modelling, music rendering and score generation using visual language programming

NASA Astrophysics Data System (ADS)

Lim, Chen Kim; Tan, Kian Lam; Yusran, Hazwanni; Suppramaniam, Vicknesh

2017-10-01

Visual language or visual representation has been used in the past few years in order to express the knowledge in graphic. One of the important graphical elements is fractal and L-Systems is a mathematic-based grammatical model for modelling cell development and plant topology. From the plant model, L-Systems can be interpreted as music sound and score. In this paper, LSound which is a Visual Language Programming (VLP) framework has been developed to model plant to music sound and generate music score and vice versa. The objectives of this research has three folds: (i) To expand the grammar dictionary of L-Systems music based on visual programming, (ii) To design and produce a user-friendly and icon based visual language framework typically for L-Systems musical score generation which helps the basic learners in musical field and (iii) To generate music score from plant models and vice versa using L-Systems method. This research undergoes a four phases methodology where the plant is first modelled, then the music is interpreted, followed by the output of music sound through MIDI and finally score is generated. LSound is technically compared to other existing applications in the aspects of the capability of modelling the plant, rendering the music and generating the sound. It has been found that LSound is a flexible framework in which the plant can be easily altered through arrow-based programming and the music score can be altered through the music symbols and notes. This work encourages non-experts to understand L-Systems and music hand-in-hand.

Detection of visual signals by rats: A computational model

EPA Science Inventory

We applied a neural network model of classical conditioning proposed by Schmajuk, Lam, and Gray (1996) to visual signal detection and discrimination tasks designed to assess sustained attention in rats (Bushnell, 1999). The model describes the animals’ expectation of receiving fo...

The evaluative imaging of mental models - Visual representations of complexity

NASA Technical Reports Server (NTRS)

Dede, Christopher

1989-01-01

The paper deals with some design issues involved in building a system that could visually represent the semantic structures of training materials and their underlying mental models. In particular, hypermedia-based semantic networks that instantiate classification problem solving strategies are thought to be a useful formalism for such representations; the complexity of these web structures can be best managed through visual depictions. It is also noted that a useful approach to implement in these hypermedia models would be some metrics of conceptual distance.

A risk-based coverage model for video surveillance camera control optimization

NASA Astrophysics Data System (ADS)

Zhang, Hongzhou; Du, Zhiguo; Zhao, Xingtao; Li, Peiyue; Li, Dehua

2015-12-01

Visual surveillance system for law enforcement or police case investigation is different from traditional application, for it is designed to monitor pedestrians, vehicles or potential accidents. Visual surveillance risk is defined as uncertainty of visual information of targets and events monitored in present work and risk entropy is introduced to modeling the requirement of police surveillance task on quality and quantity of vide information. the prosed coverage model is applied to calculate the preset FoV position of PTZ camera.

Computational Modeling of Age-Differences In a Visually Demanding Driving Task: Vehicle Detection

DTIC Science & Technology

1997-10-07

overall estimate of d’ for each scene was calculated from the two levels using the method described in MacMillan and Creelman [13]. MODELING VEHICLE...Scialfa, "Visual and auditory aging," In J. Birren & K. W. Schaie (Eds.) Handbook of the Psychology of Aging (4th edition), 1996, New York: Academic...Computational models of Visual Processing, 1991, Boston MA: MIT Press. [13] N. A. MacMillan & C. D. Creelman , Detection Theory: A User’s Guide, 1991

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…

Implications of Sustained and Transient Channels for Theories of Visual Pattern Masking, Saccadic Suppression, and Information Processing

ERIC Educational Resources Information Center

Breitmeyer, Bruno G.; Ganz, Leo

1976-01-01

This paper reviewed briefly the major types of masking effects obtained with various methods and the major theories or models that have been proposed to account for these effects, and outlined a three-mechanism model of visual pattern masking based on psychophysical and neurophysiological properties of the visual system. (Author/RK)

Retinal Information Processing for Minimum Laser Lesion Detection and Cumulative Damage

DTIC Science & Technology

1992-09-17

TAL3Unaqr~orJ:ccd [] J ,;--Wicic tion --------------... MYRON....... . ................... ... ....... ...........................MYRON L. WOLBARSHT B D ist...possible beneficial visual function of the small retinal image movements. B . Visual System Models Prior models of visual system information processing have...against standard secondary sources whose calibrations can be traced to the National Bureau of Standards. B . Electrophysiological Techniques Extracellular

Is the Oxygen Atom Static or Dynamic? The Effect of Generating Animations on Students' Mental Models of Atomic Structure

ERIC Educational Resources Information Center

Akaygun, Sevil

2016-01-01

Visualizing the chemical structure and dynamics of particles has been challenging for many students; therefore, various visualizations and tools have been used in chemistry education. For science educators, it has been important to understand how students visualize and represent particular phenomena--i.e., their mental models-- to design more…

3D Visualization for Phoenix Mars Lander Science Operations

NASA Technical Reports Server (NTRS)

Edwards, Laurence; Keely, Leslie; Lees, David; Stoker, Carol

2012-01-01

Planetary surface exploration missions present considerable operational challenges in the form of substantial communication delays, limited communication windows, and limited communication bandwidth. A 3D visualization software was developed and delivered to the 2008 Phoenix Mars Lander (PML) mission. The components of the system include an interactive 3D visualization environment called Mercator, terrain reconstruction software called the Ames Stereo Pipeline, and a server providing distributed access to terrain models. The software was successfully utilized during the mission for science analysis, site understanding, and science operations activity planning. A terrain server was implemented that provided distribution of terrain models from a central repository to clients running the Mercator software. The Ames Stereo Pipeline generates accurate, high-resolution, texture-mapped, 3D terrain models from stereo image pairs. These terrain models can then be visualized within the Mercator environment. The central cross-cutting goal for these tools is to provide an easy-to-use, high-quality, full-featured visualization environment that enhances the mission science team s ability to develop low-risk productive science activity plans. In addition, for the Mercator and Viz visualization environments, extensibility and adaptability to different missions and application areas are key design goals.

Solid object visualization of 3D ultrasound data

NASA Astrophysics Data System (ADS)

Nelson, Thomas R.; Bailey, Michael J.

2000-04-01

Visualization of volumetric medical data is challenging. Rapid-prototyping (RP) equipment producing solid object prototype models of computer generated structures is directly applicable to visualization of medical anatomic data. The purpose of this study was to develop methods for transferring 3D Ultrasound (3DUS) data to RP equipment for visualization of patient anatomy. 3DUS data were acquired using research and clinical scanning systems. Scaling information was preserved and the data were segmented using threshold and local operators to extract features of interest, converted from voxel raster coordinate format to a set of polygons representing an iso-surface and transferred to the RP machine to create a solid 3D object. Fabrication required 30 to 60 minutes depending on object size and complexity. After creation the model could be touched and viewed. A '3D visualization hardcopy device' has advantages for conveying spatial relations compared to visualization using computer display systems. The hardcopy model may be used for teaching or therapy planning. Objects may be produced at the exact dimension of the original object or scaled up (or down) to facilitate matching the viewers reference frame more optimally. RP models represent a useful means of communicating important information in a tangible fashion to patients and physicians.

Characterization of electroencephalography signals for estimating saliency features in videos.

PubMed

Liang, Zhen; Hamada, Yasuyuki; Oba, Shigeyuki; Ishii, Shin

2018-05-12

Understanding the functions of the visual system has been one of the major targets in neuroscience formany years. However, the relation between spontaneous brain activities and visual saliency in natural stimuli has yet to be elucidated. In this study, we developed an optimized machine learning-based decoding model to explore the possible relationships between the electroencephalography (EEG) characteristics and visual saliency. The optimal features were extracted from the EEG signals and saliency map which was computed according to an unsupervised saliency model ( Tavakoli and Laaksonen, 2017). Subsequently, various unsupervised feature selection/extraction techniques were examined using different supervised regression models. The robustness of the presented model was fully verified by means of ten-fold or nested cross validation procedure, and promising results were achieved in the reconstruction of saliency features based on the selected EEG characteristics. Through the successful demonstration of using EEG characteristics to predict the real-time saliency distribution in natural videos, we suggest the feasibility of quantifying visual content through measuring brain activities (EEG signals) in real environments, which would facilitate the understanding of cortical involvement in the processing of natural visual stimuli and application developments motivated by human visual processing. Copyright © 2018 Elsevier Ltd. All rights reserved.

Deep recurrent neural network reveals a hierarchy of process memory during dynamic natural vision.

PubMed

Shi, Junxing; Wen, Haiguang; Zhang, Yizhen; Han, Kuan; Liu, Zhongming

2018-05-01

The human visual cortex extracts both spatial and temporal visual features to support perception and guide behavior. Deep convolutional neural networks (CNNs) provide a computational framework to model cortical representation and organization for spatial visual processing, but unable to explain how the brain processes temporal information. To overcome this limitation, we extended a CNN by adding recurrent connections to different layers of the CNN to allow spatial representations to be remembered and accumulated over time. The extended model, or the recurrent neural network (RNN), embodied a hierarchical and distributed model of process memory as an integral part of visual processing. Unlike the CNN, the RNN learned spatiotemporal features from videos to enable action recognition. The RNN better predicted cortical responses to natural movie stimuli than the CNN, at all visual areas, especially those along the dorsal stream. As a fully observable model of visual processing, the RNN also revealed a cortical hierarchy of temporal receptive window, dynamics of process memory, and spatiotemporal representations. These results support the hypothesis of process memory, and demonstrate the potential of using the RNN for in-depth computational understanding of dynamic natural vision. © 2018 Wiley Periodicals, Inc.

Tactile Approaches for Teaching Blind and Visually-Impaired Students in the Geosciences

NASA Astrophysics Data System (ADS)

Permenter, J. L.; Runyon, C.

2003-12-01

Hearing and touch are perhaps the two most important senses for teaching visually-impaired students in any context. Classroom lectures obviously emphasize the auditory aspects of learning, while touch is often relegated to either Braille texts or raised--line drawings for illustrative figures. From the student's perspective, some lecture topics, especially in the sciences, can be a challenge to grasp without additional stimuli. Geosciences have a distinct visual component that can be lost when teaching blind or visually-impaired students, particularly in the study of geomorphology and landform change. As an example, the matters raised concerning volcanic hazards can be difficult to envision without due attention to the limitations of visually-impaired students. Here, we suggest an example of a tactile approach for introducing the study of volcanoes and the hazards associated with them. Large, visually-stimulating images of a volcanic, populated region in southern Peru are supplied for those students who have poor but extant visual acuity, while precise, clay-based models of the region complement the images for those students, as well as for students who have no visual ability whatsoever. We use a model of the terrestrial volcano El Misti and the nearby city of Arequipa, Peru, to directly reflect the volcanic morphology and hazardous aspects of the terrain. The use of computer-generated digital elevation models from remote sensing imaging systems allows accurate replication of the regional topography. Instructors are able to modify these clay models to illustrate spatial and temporal changes in the region, allowing students to better grasp potential geological and geographical transformations over time. The models spawn engaging class discussions and help with designing hazard mitigation protocols.

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.

Picture this: The value of multiple visual representations for student learning of quantum concepts in general chemistry

NASA Astrophysics Data System (ADS)

Allen, Emily Christine

Mental models for scientific learning are often defined as, "cognitive tools situated between experiments and theories" (Duschl & Grandy, 2012). In learning, these cognitive tools are used to not only take in new information, but to help problem solve in new contexts. Nancy Nersessian (2008) describes a mental model as being "[loosely] characterized as a representation of a system with interactive parts with representations of those interactions. Models can be qualitative, quantitative, and/or simulative (mental, physical, computational)" (p. 63). If conceptual parts used by the students in science education are inaccurate, then the resulting model will not be useful. Students in college general chemistry courses are presented with multiple abstract topics and often struggle to fit these parts into complete models. This is especially true for topics that are founded on quantum concepts, such as atomic structure and molecular bonding taught in college general chemistry. The objectives of this study were focused on how students use visual tools introduced during instruction to reason with atomic and molecular structure, what misconceptions may be associated with these visual tools, and how visual modeling skills may be taught to support students' use of visual tools for reasoning. The research questions for this study follow from Gilbert's (2008) theory that experts use multiple representations when reasoning and modeling a system, and Kozma and Russell's (2005) theory of representational competence levels. This study finds that as students developed greater command of their understanding of abstract quantum concepts, they spontaneously provided additional representations to describe their more sophisticated models of atomic and molecular structure during interviews. This suggests that when visual modeling with multiple representations is taught, along with the limitations of the representations, it can assist students in the development of models for reasoning about abstract topics such as atomic and molecular structure. There is further gain if students' difficulties with these representations are targeted through the use additional instruction such as a workbook that requires the students to exercise their visual modeling skills.

A Dynamic Systems Theory Model of Visual Perception Development

ERIC Educational Resources Information Center

Coté, Carol A.

2015-01-01

This article presents a model for understanding the development of visual perception from a dynamic systems theory perspective. It contrasts to a hierarchical or reductionist model that is often found in the occupational therapy literature. In this proposed model vision and ocular motor abilities are not foundational to perception, they are seen…

Making It Visual: Creating a Model of the Atom

ERIC Educational Resources Information Center

Pringle, Rose M.

2004-01-01

This article describes a lesson in which students construct Bohr's planetary model of the atom. Niels Bohr's atomic model provides a framework for discussing with middle and high school students the historical development of our understanding of the structure of the atom. The model constructed in this activity will enable students to visualize the…

A cortical integrate-and-fire neural network model for blind decoding of visual prosthetic stimulation.

PubMed

Eiber, Calvin D; Morley, John W; Lovell, Nigel H; Suaning, Gregg J

2014-01-01

We present a computational model of the optic pathway which has been adapted to simulate cortical responses to visual-prosthetic stimulation. This model reproduces the statistically observed distributions of spikes for cortical recordings of sham and maximum-intensity stimuli, while simultaneously generating cellular receptive fields consistent with those observed using traditional visual neuroscience methods. By inverting this model to generate candidate phosphenes which could generate the responses observed to novel stimulation strategies, we hope to aid the development of said strategies in-vivo before being deployed in clinical settings.

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.

Web-based Visual Analytics for Extreme Scale Climate Science

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

Steed, Chad A; Evans, Katherine J; Harney, John F

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via newmore » visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.« less

A novel visualization model for web search results.

PubMed

Nguyen, Tien N; Zhang, Jin

2006-01-01

This paper presents an interactive visualization system, named WebSearchViz, for visualizing the Web search results and acilitating users' navigation and exploration. The metaphor in our model is the solar system with its planets and asteroids revolving around the sun. Location, color, movement, and spatial distance of objects in the visual space are used to represent the semantic relationships between a query and relevant Web pages. Especially, the movement of objects and their speeds add a new dimension to the visual space, illustrating the degree of relevance among a query and Web search results in the context of users' subjects of interest. By interacting with the visual space, users are able to observe the semantic relevance between a query and a resulting Web page with respect to their subjects of interest, context information, or concern. Users' subjects of interest can be dynamically changed, redefined, added, or deleted from the visual space.

Impulse processing: A dynamical systems model of incremental eye movements in the visual world paradigm

PubMed Central

Kukona, Anuenue; Tabor, Whitney

2011-01-01

The visual world paradigm presents listeners with a challenging problem: they must integrate two disparate signals, the spoken language and the visual context, in support of action (e.g., complex movements of the eyes across a scene). We present Impulse Processing, a dynamical systems approach to incremental eye movements in the visual world that suggests a framework for integrating language, vision, and action generally. Our approach assumes that impulses driven by the language and the visual context impinge minutely on a dynamical landscape of attractors corresponding to the potential eye-movement behaviors of the system. We test three unique predictions of our approach in an empirical study in the visual world paradigm, and describe an implementation in an artificial neural network. We discuss the Impulse Processing framework in relation to other models of the visual world paradigm. PMID:21609355

Development of cortical orientation selectivity in the absence of visual experience with contour

PubMed Central

Hussain, Shaista; Weliky, Michael

2011-01-01

Visual cortical neurons are selective for the orientation of lines, and the full development of this selectivity requires natural visual experience after eye opening. Here we examined whether this selectivity develops without seeing lines and contours. Juvenile ferrets were reared in a dark room and visually trained by being shown a movie of flickering, sparse spots. We found that despite the lack of contour visual experience, the cortical neurons of these ferrets developed strong orientation selectivity and exhibited simple-cell receptive fields. This finding suggests that overt contour visual experience is unnecessary for the maturation of orientation selectivity and is inconsistent with the computational models that crucially require the visual inputs of lines and contours for the development of orientation selectivity. We propose that a correlation-based model supplemented with a constraint on synaptic strength dynamics is able to account for our experimental result. PMID:21753023

Visualizing along-strike change in deformation style using analog modeling and digital visualization software

NASA Astrophysics Data System (ADS)

Burberry, C. M.

2012-12-01

It is a well-known phenomenon that deformation style varies in space; both along the strike of a deformed belt and along the strike of individual structures within that belt. This variation in deformation style is traditionally visualized with a series of closely spaced 2D cross-sections. However, the use of 2D section lines implies plane strain along those lines, and the true 3D nature of the deformation is not necessarily captured. By using a combination of remotely sensed data, analog modeling of field datasets and this remote data, and numerical and digital visualization of the finished model, a 3D understanding and restoration of the deformation style within the region can be achieved. The workflow used for this study begins by considering the variation in deformation style which can be observed from satellite images and combining this data with traditional field data, in order to understand the deformation in the region under consideration. The conceptual model developed at this stage is then modeled using a sand and silicone modeling system, where the kinematics and dynamics of the deformation processes can be examined. A series of closely-spaced cross-sections, as well as 3D images of the deformation, are created from the analog model, and input into a digital visualization and modeling system for restoration. In this fashion, a valid 3D model is created where the internal structure of the deformed system can be visualized and mined for information. The region used in the study is the Sawtooth Range, Montana. The region forms part of the Montana Disturbed Belt in the Front Ranges of the Rocky Mountains, along strike from the Alberta Syncline in the Canadian Rocky Mountains. Interpretation of satellite data indicates that the deformation front structures include both folds and thrust structures. The thrust structures vary from hinterland-verging triangle zones to foreland-verging imbricate thrusts along strike, and the folds also vary in geometry along strike. The analog models, constrained by data from exploration wells, indicate that this change in geometry is related to a change in mechanical stratigraphy along the strike of the belt. Results from the kinematic and dynamic analysis of the digital model will also be presented. Additional implications of such a workflow and visualization system include the possibility of creating and viewing multiple cross-sections, including sections created at oblique angles to the original model. This allows the analysis of the non-plane strain component of the models and thus a more complete analysis, understanding and visualization of the deformed region. This workflow and visualization system is applicable to any region where traditional field methods must be coupled with remote data, intensely processed depth data, or analog modeling systems in order to generate valid geologic or geophsyical models.

Modeling the Perception of Audiovisual Distance: Bayesian Causal Inference and Other Models

PubMed Central

2016-01-01

Studies of audiovisual perception of distance are rare. Here, visual and auditory cue interactions in distance are tested against several multisensory models, including a modified causal inference model. In this causal inference model predictions of estimate distributions are included. In our study, the audiovisual perception of distance was overall better explained by Bayesian causal inference than by other traditional models, such as sensory dominance and mandatory integration, and no interaction. Causal inference resolved with probability matching yielded the best fit to the data. Finally, we propose that sensory weights can also be estimated from causal inference. The analysis of the sensory weights allows us to obtain windows within which there is an interaction between the audiovisual stimuli. We find that the visual stimulus always contributes by more than 80% to the perception of visual distance. The visual stimulus also contributes by more than 50% to the perception of auditory distance, but only within a mobile window of interaction, which ranges from 1 to 4 m. PMID:27959919

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.

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.

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.

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.

Visualizations and Mental Models - The Educational Implications of GEOWALL

NASA Astrophysics Data System (ADS)

Rapp, D.; Kendeou, P.

2003-12-01

Work in the earth sciences has outlined many of the faulty beliefs that students possess concerning particular geological systems and processes. Evidence from educational and cognitive psychology has demonstrated that students often have difficulty overcoming their na‹ve beliefs about science. Prior knowledge is often remarkably resistant to change, particularly when students' existing mental models for geological principles may be faulty or inaccurate. Figuring out how to help students revise their mental models to include appropriate information is a major challenge. Up until this point, research has tended to focus on whether 2-dimensional computer visualizations are useful tools for helping students develop scientifically correct models. Research suggests that when students are given the opportunity to use dynamic computer-based visualizations, they are more likely to recall the learned information, and are more likely to transfer that knowledge to novel settings. Unfortunately, 2-dimensional visualization systems are often inadequate representations of the material that educators would like students to learn. For example, a 2-dimensional image of the Earth's surface does not adequately convey particular features that are critical for visualizing the geological environment. This may limit the models that students can construct following these visualizations. GEOWALL is a stereo projection system that has attempted to address this issue. It can display multidimensional static geologic images and dynamic geologic animations in a 3-dimensional format. Our current research examines whether multidimensional visualization systems such as GEOWALL may facilitate learning by helping students to develop more complex mental models. This talk will address some of the cognitive issues that influence the construction of mental models, and the difficulty of updating existing mental models. We will also discuss our current work that seeks to examine whether GEOWALL is an effective tool for helping students to learn geological information (and potentially restructure their na‹ve conceptions of geologic principles).

Emergence of transformation-tolerant representations of visual objects in rat lateral extrastriate cortex

PubMed Central

Tafazoli, Sina; Safaai, Houman; De Franceschi, Gioia; Rosselli, Federica Bianca; Vanzella, Walter; Riggi, Margherita; Buffolo, Federica; Panzeri, Stefano; Zoccolan, Davide

2017-01-01

Rodents are emerging as increasingly popular models of visual functions. Yet, evidence that rodent visual cortex is capable of advanced visual processing, such as object recognition, is limited. Here we investigate how neurons located along the progression of extrastriate areas that, in the rat brain, run laterally to primary visual cortex, encode object information. We found a progressive functional specialization of neural responses along these areas, with: (1) a sharp reduction of the amount of low-level, energy-related visual information encoded by neuronal firing; and (2) a substantial increase in the ability of both single neurons and neuronal populations to support discrimination of visual objects under identity-preserving transformations (e.g., position and size changes). These findings strongly argue for the existence of a rat object-processing pathway, and point to the rodents as promising models to dissect the neuronal circuitry underlying transformation-tolerant recognition of visual objects. DOI: http://dx.doi.org/10.7554/eLife.22794.001 PMID:28395730

Analysis of Visual Illusions Using Multiresolution Wavelet Decomposition Based Models

DTIC Science & Technology

1991-12-01

1962). 22. Hubel , David H. "The Visual Cortex of The Brain," Scientific American, 209(5):54-62 (November 1963). 23. Hubel , David H. and Torsten N...model the visual system. In 1990, Oberndorf, a masters student at the Air Force Institrt, of Technology, tested the Gabor theo y on visual illusion...represento d by x2 + y2 = r 2 in Cartesian space is now more easily expressed by p = r in polar space. The coordinates x and y or p and 0 provide alternate

Assessing Local Model Adequacy in Bayesian Hierarchical Models Using the Partitioned Deviance Information Criterion

PubMed Central

Wheeler, David C.; Hickson, DeMarc A.; Waller, Lance A.

2010-01-01

Many diagnostic tools and goodness-of-fit measures, such as the Akaike information criterion (AIC) and the Bayesian deviance information criterion (DIC), are available to evaluate the overall adequacy of linear regression models. In addition, visually assessing adequacy in models has become an essential part of any regression analysis. In this paper, we focus on a spatial consideration of the local DIC measure for model selection and goodness-of-fit evaluation. We use a partitioning of the DIC into the local DIC, leverage, and deviance residuals to assess local model fit and influence for both individual observations and groups of observations in a Bayesian framework. We use visualization of the local DIC and differences in local DIC between models to assist in model selection and to visualize the global and local impacts of adding covariates or model parameters. We demonstrate the utility of the local DIC in assessing model adequacy using HIV prevalence data from pregnant women in the Butare province of Rwanda during 1989-1993 using a range of linear model specifications, from global effects only to spatially varying coefficient models, and a set of covariates related to sexual behavior. Results of applying the diagnostic visualization approach include more refined model selection and greater understanding of the models as applied to the data. PMID:21243121

Visualization of risk of radiogenic second cancer in the organs and tissues of the human body.

PubMed

Zhang, Rui; Mirkovic, Dragan; Newhauser, Wayne D

2015-04-28

Radiogenic second cancer is a common late effect in long term cancer survivors. Currently there are few methods or tools available to visually evaluate the spatial distribution of risks of radiogenic late effects in the human body. We developed a risk visualization method and demonstrated it for radiogenic second cancers in tissues and organs of one patient treated with photon volumetric modulated arc therapy and one patient treated with proton craniospinal irradiation. Treatment plans were generated using radiotherapy treatment planning systems (TPS) and dose information was obtained from TPS. Linear non-threshold risk coefficients for organs at risk of second cancer incidence were taken from the Biological Effects of Ionization Radiation VII report. Alternative risk models including linear exponential model and linear plateau model were also examined. The predicted absolute lifetime risk distributions were visualized together with images of the patient anatomy. The risk distributions of second cancer for the two patients were visually presented. The risk distributions varied with tissue, dose, dose-risk model used, and the risk distribution could be similar to or very different from the dose distribution. Our method provides a convenient way to directly visualize and evaluate the risks of radiogenic second cancer in organs and tissues of the human body. In the future, visual assessment of risk distribution could be an influential determinant for treatment plan scoring.

Unsupervised Neural Network Quantifies the Cost of Visual Information Processing.

PubMed

Orbán, Levente L; Chartier, Sylvain

2015-01-01

Untrained, "flower-naïve" bumblebees display behavioural preferences when presented with visual properties such as colour, symmetry, spatial frequency and others. Two unsupervised neural networks were implemented to understand the extent to which these models capture elements of bumblebees' unlearned visual preferences towards flower-like visual properties. The computational models, which are variants of Independent Component Analysis and Feature-Extracting Bidirectional Associative Memory, use images of test-patterns that are identical to ones used in behavioural studies. Each model works by decomposing images of floral patterns into meaningful underlying factors. We reconstruct the original floral image using the components and compare the quality of the reconstructed image to the original image. Independent Component Analysis matches behavioural results substantially better across several visual properties. These results are interpreted to support a hypothesis that the temporal and energetic costs of information processing by pollinators served as a selective pressure on floral displays: flowers adapted to pollinators' cognitive constraints.

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.

Visual Perceptual Learning and Models.

PubMed

Dosher, Barbara; Lu, Zhong-Lin

2017-09-15

Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

Restoring Fort Frontenac in 3D: Effective Usage of 3D Technology for Heritage Visualization

NASA Astrophysics Data System (ADS)

Yabe, M.; Goins, E.; Jackson, C.; Halbstein, D.; Foster, S.; Bazely, S.

2015-02-01

This paper is composed of three elements: 3D modeling, web design, and heritage visualization. The aim is to use computer graphics design to inform and create an interest in historical visualization by rebuilding Fort Frontenac using 3D modeling and interactive design. The final model will be integr ated into an interactive website to learn more about the fort's historic imp ortance. It is apparent that using computer graphics can save time and money when it comes to historical visualization. Visitors do not have to travel to the actual archaeological buildings. They can simply use the Web in their own home to learn about this information virtually. Meticulously following historical records to create a sophisticated restoration of archaeological buildings will draw viewers into visualizations, such as the historical world of Fort Frontenac. As a result, it allows the viewers to effectively understand the fort's social sy stem, habits, and historical events.

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.

Introduction to Information Visualization (InfoVis) Techniques for Model-Based Systems Engineering

NASA Technical Reports Server (NTRS)

Sindiy, Oleg; Litomisky, Krystof; Davidoff, Scott; Dekens, Frank

2013-01-01

This paper presents insights that conform to numerous system modeling languages/representation standards. The insights are drawn from best practices of Information Visualization as applied to aerospace-based applications.

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.

Solar System Visualization (SSV) Project

NASA Technical Reports Server (NTRS)

Todd, Jessida L.

2005-01-01

The Solar System Visualization (SSV) project aims at enhancing scientific and public understanding through visual representations and modeling procedures. The SSV project's objectives are to (1) create new visualization technologies, (2) organize science observations and models, and (3) visualize science results and mission Plans. The SSV project currently supports the Mars Exploration Rovers (MER) mission, the Mars Reconnaissance Orbiter (MRO), and Cassini. In support of the these missions, the SSV team has produced pan and zoom animations of large mosaics to reveal details of surface features and topography, created 3D animations of science instruments and procedures, formed 3-D anaglyphs from left and right stereo pairs, and animated registered multi-resolution mosaics to provide context for microscopic images.

Creating Visual Materials for Multi-Handicapped Deaf Learners.

ERIC Educational Resources Information Center

Hack, Carole; Brosmith, Susan

1980-01-01

The article describes two groups of visual materials developed for multiply handicapped deaf teenagers. The daily living skills project includes vocabulary lists, visuals, games and a model related to household cleaning, personal grooming, or consumer skills. The occupational information project includes visuals of tools, materials, and clothing…

Development of a Bayesian Estimator for Audio-Visual Integration: A Neurocomputational Study

PubMed Central

Ursino, Mauro; Crisafulli, Andrea; di Pellegrino, Giuseppe; Magosso, Elisa; Cuppini, Cristiano

2017-01-01

The brain integrates information from different sensory modalities to generate a coherent and accurate percept of external events. Several experimental studies suggest that this integration follows the principle of Bayesian estimate. However, the neural mechanisms responsible for this behavior, and its development in a multisensory environment, are still insufficiently understood. We recently presented a neural network model of audio-visual integration (Neural Computation, 2017) to investigate how a Bayesian estimator can spontaneously develop from the statistics of external stimuli. Model assumes the presence of two unimodal areas (auditory and visual) topologically organized. Neurons in each area receive an input from the external environment, computed as the inner product of the sensory-specific stimulus and the receptive field synapses, and a cross-modal input from neurons of the other modality. Based on sensory experience, synapses were trained via Hebbian potentiation and a decay term. Aim of this work is to improve the previous model, including a more realistic distribution of visual stimuli: visual stimuli have a higher spatial accuracy at the central azimuthal coordinate and a lower accuracy at the periphery. Moreover, their prior probability is higher at the center, and decreases toward the periphery. Simulations show that, after training, the receptive fields of visual and auditory neurons shrink to reproduce the accuracy of the input (both at the center and at the periphery in the visual case), thus realizing the likelihood estimate of unimodal spatial position. Moreover, the preferred positions of visual neurons contract toward the center, thus encoding the prior probability of the visual input. Finally, a prior probability of the co-occurrence of audio-visual stimuli is encoded in the cross-modal synapses. The model is able to simulate the main properties of a Bayesian estimator and to reproduce behavioral data in all conditions examined. In particular, in unisensory conditions the visual estimates exhibit a bias toward the fovea, which increases with the level of noise. In cross modal conditions, the SD of the estimates decreases when using congruent audio-visual stimuli, and a ventriloquism effect becomes evident in case of spatially disparate stimuli. Moreover, the ventriloquism decreases with the eccentricity. PMID:29046631

Forest inventory and management-based visual preference models of southern pine stands

Treesearch

Victor A. Rudis; James H. Gramann; Edward J. Ruddell; Joanne M. Westphal

1988-01-01

Statistical models explaining students' ratings of photographs of within stand forest scenes were constructed for 99 forest inventory plots in east Texas pine and oak-pine forest types. Models with parameters that are sensitive to visual preference yet compatible with forest management and timber inventories are presented. The models suggest that the density of...

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.

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.

Visual Reconciliation of Alternative Similarity Spaces in Climate Modeling.

PubMed

Poco, Jorge; Dasgupta, Aritra; Wei, Yaxing; Hargrove, William; Schwalm, Christopher R; Huntzinger, Deborah N; Cook, Robert; Bertini, Enrico; Silva, Claudio T

2014-12-01

Visual data analysis often requires grouping of data objects based on their similarity. In many application domains researchers use algorithms and techniques like clustering and multidimensional scaling to extract groupings from data. While extracting these groups using a single similarity criteria is relatively straightforward, comparing alternative criteria poses additional challenges. In this paper we define visual reconciliation as the problem of reconciling multiple alternative similarity spaces through visualization and interaction. We derive this problem from our work on model comparison in climate science where climate modelers are faced with the challenge of making sense of alternative ways to describe their models: one through the output they generate, another through the large set of properties that describe them. Ideally, they want to understand whether groups of models with similar spatio-temporal behaviors share similar sets of criteria or, conversely, whether similar criteria lead to similar behaviors. We propose a visual analytics solution based on linked views, that addresses this problem by allowing the user to dynamically create, modify and observe the interaction among groupings, thereby making the potential explanations apparent. We present case studies that demonstrate the usefulness of our technique in the area of climate science.

The feature-weighted receptive field: an interpretable encoding model for complex feature spaces.

PubMed

St-Yves, Ghislain; Naselaris, Thomas

2017-06-20

We introduce the feature-weighted receptive field (fwRF), an encoding model designed to balance expressiveness, interpretability and scalability. The fwRF is organized around the notion of a feature map-a transformation of visual stimuli into visual features that preserves the topology of visual space (but not necessarily the native resolution of the stimulus). The key assumption of the fwRF model is that activity in each voxel encodes variation in a spatially localized region across multiple feature maps. This region is fixed for all feature maps; however, the contribution of each feature map to voxel activity is weighted. Thus, the model has two separable sets of parameters: "where" parameters that characterize the location and extent of pooling over visual features, and "what" parameters that characterize tuning to visual features. The "where" parameters are analogous to classical receptive fields, while "what" parameters are analogous to classical tuning functions. By treating these as separable parameters, the fwRF model complexity is independent of the resolution of the underlying feature maps. This makes it possible to estimate models with thousands of high-resolution feature maps from relatively small amounts of data. Once a fwRF model has been estimated from data, spatial pooling and feature tuning can be read-off directly with no (or very little) additional post-processing or in-silico experimentation. We describe an optimization algorithm for estimating fwRF models from data acquired during standard visual neuroimaging experiments. We then demonstrate the model's application to two distinct sets of features: Gabor wavelets and features supplied by a deep convolutional neural network. We show that when Gabor feature maps are used, the fwRF model recovers receptive fields and spatial frequency tuning functions consistent with known organizational principles of the visual cortex. We also show that a fwRF model can be used to regress entire deep convolutional networks against brain activity. The ability to use whole networks in a single encoding model yields state-of-the-art prediction accuracy. Our results suggest a wide variety of uses for the feature-weighted receptive field model, from retinotopic mapping with natural scenes, to regressing the activities of whole deep neural networks onto measured brain activity. Copyright © 2017. Published by Elsevier Inc.

Creating Physical 3D Stereolithograph Models of Brain and Skull

PubMed Central

Kelley, Daniel J.; Farhoud, Mohammed; Meyerand, M. Elizabeth; Nelson, David L.; Ramirez, Lincoln F.; Dempsey, Robert J.; Wolf, Alan J.; Alexander, Andrew L.; Davidson, Richard J.

2007-01-01

The human brain and skull are three dimensional (3D) anatomical structures with complex surfaces. However, medical images are often two dimensional (2D) and provide incomplete visualization of structural morphology. To overcome this loss in dimension, we developed and validated a freely available, semi-automated pathway to build 3D virtual reality (VR) and hand-held, stereolithograph models. To evaluate whether surface visualization in 3D was more informative than in 2D, undergraduate students (n = 50) used the Gillespie scale to rate 3D VR and physical models of both a living patient-volunteer's brain and the skull of Phineas Gage, a historically famous railroad worker whose misfortune with a projectile tamping iron provided the first evidence of a structure-function relationship in brain. Using our processing pathway, we successfully fabricated human brain and skull replicas and validated that the stereolithograph model preserved the scale of the VR model. Based on the Gillespie ratings, students indicated that the biological utility and quality of visual information at the surface of VR and stereolithograph models were greater than the 2D images from which they were derived. The method we developed is useful to create VR and stereolithograph 3D models from medical images and can be used to model hard or soft tissue in living or preserved specimens. Compared to 2D images, VR and stereolithograph models provide an extra dimension that enhances both the quality of visual information and utility of surface visualization in neuroscience and medicine. PMID:17971879

A neural computational model for animal's time-to-collision estimation.

PubMed

Wang, Ling; Yao, Dezhong

2013-04-17

The time-to-collision (TTC) is the time elapsed before a looming object hits the subject. An accurate estimation of TTC plays a critical role in the survival of animals in nature and acts as an important factor in artificial intelligence systems that depend on judging and avoiding potential dangers. The theoretic formula for TTC is 1/τ≈θ'/sin θ, where θ and θ' are the visual angle and its variation, respectively, and the widely used approximation computational model is θ'/θ. However, both of these measures are too complex to be implemented by a biological neuronal model. We propose a new simple computational model: 1/τ≈Mθ-P/(θ+Q)+N, where M, P, Q, and N are constants that depend on a predefined visual angle. This model, weighted summation of visual angle model (WSVAM), can achieve perfect implementation through a widely accepted biological neuronal model. WSVAM has additional merits, including a natural minimum consumption and simplicity. Thus, it yields a precise and neuronal-implemented estimation for TTC, which provides a simple and convenient implementation for artificial vision, and represents a potential visual brain mechanism.

Visual Attention Modeling for Stereoscopic Video: A Benchmark and Computational Model.

PubMed

Fang, Yuming; Zhang, Chi; Li, Jing; Lei, Jianjun; Perreira Da Silva, Matthieu; Le Callet, Patrick

2017-10-01

In this paper, we investigate the visual attention modeling for stereoscopic video from the following two aspects. First, we build one large-scale eye tracking database as the benchmark of visual attention modeling for stereoscopic video. The database includes 47 video sequences and their corresponding eye fixation data. Second, we propose a novel computational model of visual attention for stereoscopic video based on Gestalt theory. In the proposed model, we extract the low-level features, including luminance, color, texture, and depth, from discrete cosine transform coefficients, which are used to calculate feature contrast for the spatial saliency computation. The temporal saliency is calculated by the motion contrast from the planar and depth motion features in the stereoscopic video sequences. The final saliency is estimated by fusing the spatial and temporal saliency with uncertainty weighting, which is estimated by the laws of proximity, continuity, and common fate in Gestalt theory. Experimental results show that the proposed method outperforms the state-of-the-art stereoscopic video saliency detection models on our built large-scale eye tracking database and one other database (DML-ITRACK-3D).

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study

PubMed Central

Bornschein, Jörg; Henniges, Marc; Lücke, Jörg

2013-01-01

Simple cells in primary visual cortex were famously found to respond to low-level image components such as edges. Sparse coding and independent component analysis (ICA) emerged as the standard computational models for simple cell coding because they linked their receptive fields to the statistics of visual stimuli. However, a salient feature of image statistics, occlusions of image components, is not considered by these models. Here we ask if occlusions have an effect on the predicted shapes of simple cell receptive fields. We use a comparative approach to answer this question and investigate two models for simple cells: a standard linear model and an occlusive model. For both models we simultaneously estimate optimal receptive fields, sparsity and stimulus noise. The two models are identical except for their component superposition assumption. We find the image encoding and receptive fields predicted by the models to differ significantly. While both models predict many Gabor-like fields, the occlusive model predicts a much sparser encoding and high percentages of ‘globular’ receptive fields. This relatively new center-surround type of simple cell response is observed since reverse correlation is used in experimental studies. While high percentages of ‘globular’ fields can be obtained using specific choices of sparsity and overcompleteness in linear sparse coding, no or only low proportions are reported in the vast majority of studies on linear models (including all ICA models). Likewise, for the here investigated linear model and optimal sparsity, only low proportions of ‘globular’ fields are observed. In comparison, the occlusive model robustly infers high proportions and can match the experimentally observed high proportions of ‘globular’ fields well. Our computational study, therefore, suggests that ‘globular’ fields may be evidence for an optimal encoding of visual occlusions in primary visual cortex. PMID:23754938

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.

Visual perception and social foraging in birds.

PubMed

Fernández-Juricic, Esteban; Erichsen, Jonathan T; Kacelnik, Alex

2004-01-01

Birds gather information about their environment mainly through vision by scanning their surroundings. Many prevalent models of social foraging assume that foraging and scanning are mutually exclusive. Although this assumption is valid for birds with narrow visual fields, these models have also been applied to species with wide fields. In fact, available models do not make precise predictions for birds with large visual fields, in which the head-up, head-down dichotomy is not accurate and, moreover, do not consider the effects of detection distance and limited attention. Studies of how different types of visual information are acquired as a function of body posture and of how information flows within flocks offer new insights into the costs and benefits of living in groups.

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.

Position Information Encoded by Population Activity in Hierarchical Visual Areas

PubMed Central

Majima, Kei; Horikawa, Tomoyasu

2017-01-01

Abstract Neurons in high-level visual areas respond to more complex visual features with broader receptive fields (RFs) compared to those in low-level visual areas. Thus, high-level visual areas are generally considered to carry less information regarding the position of seen objects in the visual field. However, larger RFs may not imply loss of position information at the population level. Here, we evaluated how accurately the position of a seen object could be predicted (decoded) from activity patterns in each of six representative visual areas with different RF sizes [V1–V4, lateral occipital complex (LOC), and fusiform face area (FFA)]. We collected functional magnetic resonance imaging (fMRI) responses while human subjects viewed a ball randomly moving in a two-dimensional field. To estimate population RF sizes of individual fMRI voxels, RF models were fitted for individual voxels in each brain area. The voxels in higher visual areas showed larger estimated RFs than those in lower visual areas. Then, the ball’s position in a separate session was predicted by maximum likelihood estimation using the RF models of individual voxels. We also tested a model-free multivoxel regression (support vector regression, SVR) to predict the position. We found that regardless of the difference in RF size, all visual areas showed similar prediction accuracies, especially on the horizontal dimension. Higher areas showed slightly lower accuracies on the vertical dimension, which appears to be attributed to the narrower spatial distributions of the RF centers. The results suggest that much position information is preserved in population activity through the hierarchical visual pathway regardless of RF sizes and is potentially available in later processing for recognition and behavior. PMID:28451634

Virtual Reality: Visualization in Three Dimensions.

ERIC Educational Resources Information Center

McLellan, Hilary

Virtual reality is a newly emerging tool for scientific visualization that makes possible multisensory, three-dimensional modeling of scientific data. While the emphasis is on visualization, the other senses are added to enhance what the scientist can visualize. Researchers are working to extend the sensory range of what can be perceived in…

Learning STEM through Integrative Visual Representations

ERIC Educational Resources Information Center

Virk, Satyugjit Singh

2013-01-01

Previous cognitive models of memory have not comprehensively taken into account the internal cognitive load of chunking isolated information and have emphasized the external cognitive load of visual presentation only. Under the Virk Long Term Working Memory Multimedia Model of cognitive load, drawing from the Cowan model, students presented with…

SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data

Treesearch

J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva

2014-01-01

Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...

A Neurobehavioral Model of Flexible Spatial Language Behaviors

ERIC Educational Resources Information Center

Lipinski, John; Schneegans, Sebastian; Sandamirskaya, Yulia; Spencer, John P.; Schoner, 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…

A Simple Model of Hox Genes: Bone Morphology Demonstration

ERIC Educational Resources Information Center

Shmaefsky, Brian

2008-01-01

Visual demonstrations of abstract scientific concepts are effective strategies for enhancing content retention (Shmaefsky 2004). The concepts associated with gene regulation of growth and development are particularly complex and are well suited for teaching with visual models. This demonstration provides a simple and accurate model of Hox gene…

Model for nerve visualization in preoperative image data based on intraoperatively gained EMG signals.

PubMed

Strauss, Mario; Lueders, Christian; Strauss, Gero; Stopp, Sebastian; Shi, Jiaxi; Lueth, Tim C

2008-01-01

While removing bone tissue of the mastoid, the facial nerve is at risk of being injured. In this contribution a model for nerve visualization in preoperative image data based on intraoperatively gained EMG signals is proposed. A neuro monitor can assist the surgeon locating and preserving the nerve. With the proposed model gained EMG signals can be spatially related to the patient resp. the image data. During navigation the detected nerve course will be visualized and hence permanently available for assessing the situs.

Stereoscopic display of 3D models for design visualization

NASA Astrophysics Data System (ADS)

Gilson, Kevin J.

2006-02-01

Advances in display technology and 3D design visualization applications have made real-time stereoscopic visualization of architectural and engineering projects a reality. Parsons Brinkerhoff (PB) is a transportation consulting firm that has used digital visualization tools from their inception and has helped pioneer the application of those tools to large scale infrastructure projects. PB is one of the first Architecture/Engineering/Construction (AEC) firms to implement a CAVE- an immersive presentation environment that includes stereoscopic rear-projection capability. The firm also employs a portable stereoscopic front-projection system, and shutter-glass systems for smaller groups. PB is using commercial real-time 3D applications in combination with traditional 3D modeling programs to visualize and present large AEC projects to planners, clients and decision makers in stereo. These presentations create more immersive and spatially realistic presentations of the proposed designs. This paper will present the basic display tools and applications, and the 3D modeling techniques PB is using to produce interactive stereoscopic content. The paper will discuss several architectural and engineering design visualizations we have produced.

Iterating between Tools to Create and Edit Visualizations.

PubMed

Bigelow, Alex; Drucker, Steven; Fisher, Danyel; Meyer, Miriah

2017-01-01

A common workflow for visualization designers begins with a generative tool, like D3 or Processing, to create the initial visualization; and proceeds to a drawing tool, like Adobe Illustrator or Inkscape, for editing and cleaning. Unfortunately, this is typically a one-way process: once a visualization is exported from the generative tool into a drawing tool, it is difficult to make further, data-driven changes. In this paper, we propose a bridge model to allow designers to bring their work back from the drawing tool to re-edit in the generative tool. Our key insight is to recast this iteration challenge as a merge problem - similar to when two people are editing a document and changes between them need to reconciled. We also present a specific instantiation of this model, a tool called Hanpuku, which bridges between D3 scripts and Illustrator. We show several examples of visualizations that are iteratively created using Hanpuku in order to illustrate the flexibility of the approach. We further describe several hypothetical tools that bridge between other visualization tools to emphasize the generality of the model.

Visual Attention and Applications in Multimedia Technologies

PubMed Central

Le Callet, Patrick; Niebur, Ernst

2013-01-01

Making technological advances in the field of human-machine interactions requires that the capabilities and limitations of the human perceptual system are taken into account. The focus of this report is an important mechanism of perception, visual selective attention, which is becoming more and more important for multimedia applications. We introduce the concept of visual attention and describe its underlying mechanisms. In particular, we introduce the concepts of overt and covert visual attention, and of bottom-up and top-down processing. Challenges related to modeling visual attention and their validation using ad hoc ground truth are also discussed. Examples of the usage of visual attention models in image and video processing are presented. We emphasize multimedia delivery, retargeting and quality assessment of image and video, medical imaging, and the field of stereoscopic 3D images applications. PMID:24489403

Eye-fixation behavior, lexical storage, and visual word recognition in a split processing model.

PubMed

Shillcock, R; Ellison, T M; Monaghan, P

2000-10-01

Some of the implications of a model of visual word recognition in which processing is conditioned by the anatomical splitting of the visual field between the two hemispheres of the brain are explored. The authors investigate the optimal processing of visually presented words within such an architecture, and, for a realistically sized lexicon of English, characterize a computationally optimal fixation point in reading. They demonstrate that this approach motivates a range of behavior observed in reading isolated words and text, including the optimal viewing position and its relationship with the preferred viewing location, the failure to fixate smaller words, asymmetries in hemisphere-specific processing, and the priority given to the exterior letters of words. The authors also show that split architectures facilitate the uptake of all the letter-position information necessary for efficient word recognition and that this information may be less specific than is normally assumed. A split model of word recognition captures a range of behavior in reading that is greater than that covered by existing models of visual word recognition.

Simulating the role of visual selective attention during the development of perceptual completion

PubMed Central

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

2014-01-01

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 visual selective attention. In the current simulation study, we used the same model to simulate 3-month-olds’ performance on a second measure, the perceptual unity task. Two parameters in the model – corresponding to areas in the occipital and parietal cortices – were systematically varied while the gaze patterns produced by the model were recorded and subsequently analyzed. Three key findings emerged from the simulation study. First, the model successfully replicated the performance of 3-month-olds on the unity perception task. Second, the model also helps to explain the improved performance of 2-month-olds when the size of the occluder in the unity perception task is reduced. Third, in contrast to our previous simulation results, variation in only one of the two cortical regions simulated (i.e. recurrent activity in posterior parietal cortex) resulted in a performance pattern that matched 3-month-olds. These findings provide additional support for our hypothesis that the development of perceptual completion in early infancy is promoted by progressive improvements in visual selective attention and oculomotor skill. PMID:23106728

Simulating the role of visual selective attention during the development of perceptual completion.

PubMed

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

2012-11-01

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 visual selective attention. In the current simulation study, we used the same model to simulate 3-month-olds' performance on a second measure, the perceptual unity task. Two parameters in the model - corresponding to areas in the occipital and parietal cortices - were systematically varied while the gaze patterns produced by the model were recorded and subsequently analyzed. Three key findings emerged from the simulation study. First, the model successfully replicated the performance of 3-month-olds on the unity perception task. Second, the model also helps to explain the improved performance of 2-month-olds when the size of the occluder in the unity perception task is reduced. Third, in contrast to our previous simulation results, variation in only one of the two cortical regions simulated (i.e. recurrent activity in posterior parietal cortex) resulted in a performance pattern that matched 3-month-olds. These findings provide additional support for our hypothesis that the development of perceptual completion in early infancy is promoted by progressive improvements in visual selective attention and oculomotor skill. © 2012 Blackwell Publishing Ltd.

A New Approach to the Visual Rendering of Mantle Tomography

NASA Astrophysics Data System (ADS)

Holtzman, B. K.; Pratt, M. J.; Turk, M.; Hannasch, D. A.

2016-12-01

Visualization of mantle tomographic models requires a range of subjective aesthetic decisions that are often made subconsciously or unarticulated by authors. Many of these decisions affect the interpretations of the model, and therefore should be articulated and understood. In 2D these decisions are manifest in the choice of colormap, including the data values associated with the neutral/transitional colorband, as well as the correspondence between the extrema in the colormap and the parameters of the extrema. For example, we generally choose warm color signifying slow- and cool colors signifying fast velocities (or perturbations), but where is the transition, and the color gradients from transition to extrema? In 3D, volumes are generally rendered by choosing an isosurface of a velocity perturbation (relative to a model at each depth) and coloring it slow to fast. The choice of isosurface is arbitrary or guided by a researcher's intuition, again strongly affecting (or driven by) the interpretation. Here, we present a different approach to 3-D rendering of tomography models, using true volumetric rendering with "yt", a python package for visualization and analysis of data. In our approach, we do not use isosurfaces; instead, we render the extrema in the tomographic model as the most opaque, with an opacity function that touches zero (totally transparent) at dynamically selected values, or at the average value at each depth. The intent is that the most robust aspects of the model are visually clear, and the visualization emphasizes the nature of the interfaces between regions as well as the form of distinct mantle regions. Much of the current scientific discussion in upper mantle tomography focuses on the nature of interfaces, so we will demonstrate how decisions in the definition of the transparent regions influence interpretation of tomographic models. Our aim is to develop a visual language for tomographic visualization that can help focus geodynamic questions.

Long-term Recurrent Convolutional Networks for Visual Recognition and Description

DTIC Science & Technology

2014-11-17

deep???, are effective for tasks involving sequences, visual and otherwise. We develop a novel recurrent convolutional architecture suitable for large...models which are also recurrent, or “temporally deep”, are effective for tasks involving sequences, visual and otherwise. We develop a novel recurrent...limitation of simple RNN models which strictly integrate state information over time is known as the “vanishing gradient” effect : the ability to

Fluorescence Imaging and Streamline Visualization of Hypersonic Flow over Rapid Prototype Wind-Tunnel Models

NASA Technical Reports Server (NTRS)

Danehy, Paul M.; Alderfer, David W.; Inman, Jennifer A.; Berger, Karen T.; Buck, Gregory M.; Schwartz, Richard J.

2008-01-01

Reentry models for use in hypersonic wind tunnel tests were fabricated using a stereolithography apparatus. These models were produced in one day or less, which is a significant time savings compared to the manufacture of ceramic or metal models. The models were tested in the NASA Langley Research Center 31-Inch Mach 10 Air Tunnel. Only a few of the models survived repeated tests in the tunnel, and several failure modes of the models were identified. Planar laser-induced fluorescence (PLIF) of nitric oxide (NO) was used to visualize the flowfields in the wakes of these models. Pure NO was either seeded through tubes plumbed into the model or via a tube attached to the strut holding the model, which provided localized addition of NO into the model s wake through a porous metal cylinder attached to the end of the tube. Models included several 2- inch diameter Inflatable Reentry Vehicle Experiment (IRVE) models and 5-inch diameter Crew Exploration Vehicle (CEV) models. Various model configurations and NO seeding methods were used, including a new streamwise visualization method based on PLIF. Virtual Diagnostics Interface (ViDI) technology, developed at NASA Langley Research Center, was used to visualize the data sets in post processing. The use of calibration "dotcards" was investigated to correct for camera perspective and lens distortions in the PLIF images.

Scientific Visualization to Study Flux Transfer Events at the Community Coordinated Modeling Center

NASA Technical Reports Server (NTRS)

Rastatter, Lutz; Kuznetsova, Maria M.; Sibeck, David G.; Berrios, David H.

2011-01-01

In this paper we present results of modeling of reconnection at the dayside magnetopause with subsequent development of flux transfer event signatures. The tools used include new methods that have been added to the suite of visualization methods that are used at the Community Coordinated Modeling Center (CCMC). Flux transfer events result from localized reconnection that connect magnetosheath magnetic field and plasma with magnetospheric fields and plasma and results in flux rope structures that span the dayside magnetopause. The onset of flux rope formation and the three-dimensional structure of flux ropes are studied as they have been modeled by high-resolution magnetohydrodynamic simulations of the dayside magnetosphere of the Earth. We show that flux transfer events are complex three-dimensional structures that require modern visualization and analysis techniques. Two suites of visualization methods are presented and we demonstrate the usefulness of those methods through the CCMC web site to the general science user.

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.

Cortical connective field estimates from resting state fMRI activity.

PubMed

Gravel, Nicolás; Harvey, Ben; Nordhjem, Barbara; Haak, Koen V; Dumoulin, Serge O; Renken, Remco; Curčić-Blake, Branislava; Cornelissen, Frans W

2014-01-01

One way to study connectivity in visual cortical areas is by examining spontaneous neural activity. In the absence of visual input, such activity remains shaped by the underlying neural architecture and, presumably, may still reflect visuotopic organization. Here, we applied population connective field (CF) modeling to estimate the spatial profile of functional connectivity in the early visual cortex during resting state functional magnetic resonance imaging (RS-fMRI). This model-based analysis estimates the spatial integration between blood-oxygen level dependent (BOLD) signals in distinct cortical visual field maps using fMRI. Just as population receptive field (pRF) mapping predicts the collective neural activity in a voxel as a function of response selectivity to stimulus position in visual space, CF modeling predicts the activity of voxels in one visual area as a function of the aggregate activity in voxels in another visual area. In combination with pRF mapping, CF locations on the cortical surface can be interpreted in visual space, thus enabling reconstruction of visuotopic maps from resting state data. We demonstrate that V1 ➤ V2 and V1 ➤ V3 CF maps estimated from resting state fMRI data show visuotopic organization. Therefore, we conclude that-despite some variability in CF estimates between RS scans-neural properties such as CF maps and CF size can be derived from resting state data.

Modeling human perception and estimation of kinematic responses during aircraft landing

NASA Technical Reports Server (NTRS)

Schmidt, David K.; Silk, Anthony B.

1988-01-01

The thrust of this research is to determine estimation accuracy of aircraft responses based on observed cues. By developing the geometric relationships between the outside visual scene and the kinematics during landing, visual and kinesthetic cues available to the pilot were modeled. Both fovial and peripheral vision was examined. The objective was to first determine estimation accuracy in a variety of flight conditions, and second to ascertain which parameters are most important and lead to the best achievable accuracy in estimating the actual vehicle response. It was found that altitude estimation was very sensitive to the FOV. For this model the motion cue of perceived vertical acceleration was shown to be less important than the visual cues. The inclusion of runway geometry in the visual scene increased estimation accuracy in most cases. Finally, it was shown that for this model if the pilot has an incorrect internal model of the system kinematics the choice of observations thought to be 'optimal' may in fact be suboptimal.

Partial Membership Latent Dirichlet Allocation for Soft Image Segmentation.

PubMed

Chen, Chao; Zare, Alina; Trinh, Huy N; Omotara, Gbenga O; Cobb, James Tory; Lagaunne, Timotius A

2017-12-01

Topic models [e.g., probabilistic latent semantic analysis, latent Dirichlet allocation (LDA), and supervised LDA] have been widely used for segmenting imagery. However, these models are confined to crisp segmentation, forcing a visual word (i.e., an image patch) to belong to one and only one topic. Yet, there are many images in which some regions cannot be assigned a crisp categorical label (e.g., transition regions between a foggy sky and the ground or between sand and water at a beach). In these cases, a visual word is best represented with partial memberships across multiple topics. To address this, we present a partial membership LDA (PM-LDA) model and an associated parameter estimation algorithm. This model can be useful for imagery, where a visual word may be a mixture of multiple topics. Experimental results on visual and sonar imagery show that PM-LDA can produce both crisp and soft semantic image segmentations; a capability previous topic modeling methods do not have.

A linear model fails to predict orientation selectivity of cells in the cat visual cortex.

PubMed Central

Volgushev, M; Vidyasagar, T R; Pei, X

1996-01-01

1. Postsynaptic potentials (PSPs) evoked by visual stimulation in simple cells in the cat visual cortex were recorded using in vivo whole-cell technique. Responses to small spots of light presented at different positions over the receptive field and responses to elongated bars of different orientations centred on the receptive field were recorded. 2. To test whether a linear model can account for orientation selectivity of cortical neurones, responses to elongated bars were compared with responses predicted by a linear model from the receptive field map obtained from flashing spots. 3. The linear model faithfully predicted the preferred orientation, but not the degree of orientation selectivity or the sharpness of orientation tuning. The ratio of optimal to non-optimal responses was always underestimated by the model. 4. Thus non-linear mechanisms, which can include suppression of non-optimal responses and/or amplification of optimal responses, are involved in the generation of orientation selectivity in the primary visual cortex. PMID:8930828

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.

A model of microsaccade-related neural responses induced by short-term depression in thalamocortical synapses

PubMed Central

Yuan, Wu-Jie; Dimigen, Olaf; Sommer, Werner; Zhou, Changsong

2013-01-01

Microsaccades during fixation have been suggested to counteract visual fading. Recent experiments have also observed microsaccade-related neural responses from cellular record, scalp electroencephalogram (EEG), and functional magnetic resonance imaging (fMRI). The underlying mechanism, however, is not yet understood and highly debated. It has been proposed that the neural activity of primary visual cortex (V1) is a crucial component for counteracting visual adaptation. In this paper, we use computational modeling to investigate how short-term depression (STD) in thalamocortical synapses might affect the neural responses of V1 in the presence of microsaccades. Our model not only gives a possible synaptic explanation for microsaccades in counteracting visual fading, but also reproduces several features in experimental findings. These modeling results suggest that STD in thalamocortical synapses plays an important role in microsaccade-related neural responses and the model may be useful for further investigation of behavioral properties and functional roles of microsaccades. PMID:23630494

Visual Simulation The Old Way

NASA Astrophysics Data System (ADS)

Gomes, Gary G.

1986-05-01

A cost effective and supportable color visual system has been developed to provide the necessary visual cues to United States Air Force B-52 bomber pilots training to become proficient at the task of inflight refueling. This camera model visual system approach is not suitable for all simulation applications, but provides a cost effective alternative to digital image generation systems when high fidelity of a single movable object is required. The system consists of a three axis gimballed KC-l35 tanker model, a range carriage mounted color augmented monochrome television camera, interface electronics, a color light valve projector and an infinity optics display system.

Visualization of Stereoscopic Anatomic Models of the Paranasal Sinuses and Cervical Vertebrae from the Surgical and Procedural Perspective

ERIC Educational Resources Information Center

Chen, Jian; Smith, Andrew D.; Khan, Majid A.; Sinning, Allan R.; Conway, Marianne L.; Cui, Dongmei

2017-01-01

Recent improvements in three-dimensional (3D) virtual modeling software allows anatomists to generate high-resolution, visually appealing, colored, anatomical 3D models from computed tomography (CT) images. In this study, high-resolution CT images of a cadaver were used to develop clinically relevant anatomic models including facial skull, nasal…

Modeling and Visualization Process of the Curve of Pen Point by GeoGebra

ERIC Educational Resources Information Center

Aktümen, Muharem; Horzum, Tugba; Ceylan, Tuba

2013-01-01

This study describes the mathematical construction of a real-life model by means of parametric equations, as well as the two- and three-dimensional visualization of the model using the software GeoGebra. The model was initially considered as "determining the parametric equation of the curve formed on a plane by the point of a pen, positioned…

Visualization of RNA structure models within the Integrative Genomics Viewer.

PubMed

Busan, Steven; Weeks, Kevin M

2017-07-01

Analyses of the interrelationships between RNA structure and function are increasingly important components of genomic studies. The SHAPE-MaP strategy enables accurate RNA structure probing and realistic structure modeling of kilobase-length noncoding RNAs and mRNAs. Existing tools for visualizing RNA structure models are not suitable for efficient analysis of long, structurally heterogeneous RNAs. In addition, structure models are often advantageously interpreted in the context of other experimental data and gene annotation information, for which few tools currently exist. We have developed a module within the widely used and well supported open-source Integrative Genomics Viewer (IGV) that allows visualization of SHAPE and other chemical probing data, including raw reactivities, data-driven structural entropies, and data-constrained base-pair secondary structure models, in context with linear genomic data tracks. We illustrate the usefulness of visualizing RNA structure in the IGV by exploring structure models for a large viral RNA genome, comparing bacterial mRNA structure in cells with its structure under cell- and protein-free conditions, and comparing a noncoding RNA structure modeled using SHAPE data with a base-pairing model inferred through sequence covariation analysis. © 2017 Busan and Weeks; Published by Cold Spring Harbor Laboratory Press for the RNA Society.

The Visual System of Zebrafish and its Use to Model Human Ocular Diseases

PubMed Central

Gestri, Gaia; Link, Brian A; Neuhauss, Stephan CF

2011-01-01

Free swimming zebrafish larvae depend mainly on their sense of vision to evade predation and to catch prey. Hence there is strong selective pressure on the fast maturation of visual function and indeed the visual system already supports a number of visually-driven behaviors in the newly hatched larvae. The ability to exploit the genetic and embryonic accessibility of the zebrafish in combination with a behavioral assessment of visual system function has made the zebrafish a popular model to study vision and its diseases. Here, we review the anatomy, physiology and development of the zebrafish eye as the basis to relate the contributions of the zebrafish to our understanding of human ocular diseases. PMID:21595048

Advances in visual representation of molecular potentials.

PubMed

Du, Qi-Shi; Huang, Ri-Bo; Chou, Kuo-Chen

2010-06-01

The recent advances in visual representations of molecular properties in 3D space are summarized, and their applications in molecular modeling study and rational drug design are introduced. The visual representation methods provide us with detailed insights into protein-ligand interactions, and hence can play a major role in elucidating the structure or reactivity of a biomolecular system. Three newly developed computation and visualization methods for studying the physical and chemical properties of molecules are introduced, including their electrostatic potential, lipophilicity potential and excess chemical potential. The newest application examples of visual representations in structure-based rational drug are presented. The 3D electrostatic potentials, calculated using the empirical method (EM-ESP), in which the classical Coulomb equation and traditional atomic partial changes are discarded, are highly consistent with the results by the higher level quantum chemical method. The 3D lipophilicity potentials, computed by the heuristic molecular lipophilicity potential method based on the principles of quantum mechanics and statistical mechanics, are more accurate and reliable than those by using the traditional empirical methods. The 3D excess chemical potentials, derived by the reference interaction site model-hypernetted chain theory, provide a new tool for computational chemistry and molecular modeling. For structure-based drug design, the visual representations of molecular properties will play a significant role in practical applications. It is anticipated that the new advances in computational chemistry will stimulate the development of molecular modeling methods, further enriching the visual representation techniques for rational drug design, as well as other relevant fields in life science.

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.

Perceptual category learning and visual processing: An exercise in computational cognitive neuroscience.

PubMed

Cantwell, George; Riesenhuber, Maximilian; Roeder, Jessica L; Ashby, F Gregory

2017-05-01

The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning. Using bitmap images as inputs and by adjusting only a couple of learning-rate parameters, the new HMAX/COVIS model provides impressively good fits to human category-learning data from two qualitatively different experiments that used different types of category structures and different types of visual stimuli. Overall, the model provides a comprehensive neural and behavioral account of basal ganglia-mediated learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

An Integrated Web-Based 3d Modeling and Visualization Platform to Support Sustainable Cities

NASA Astrophysics Data System (ADS)

Amirebrahimi, S.; Rajabifard, A.

2012-07-01

Sustainable Development is found as the key solution to preserve the sustainability of cities in oppose to ongoing population growth and its negative impacts. This is complex and requires a holistic and multidisciplinary decision making. Variety of stakeholders with different backgrounds also needs to be considered and involved. Numerous web-based modeling and visualization tools have been designed and developed to support this process. There have been some success stories; however, majority failed to bring a comprehensive platform to support different aspects of sustainable development. In this work, in the context of SDI and Land Administration, CSDILA Platform - a 3D visualization and modeling platform -was proposed which can be used to model and visualize different dimensions to facilitate the achievement of sustainability, in particular, in urban context. The methodology involved the design of a generic framework for development of an analytical and visualization tool over the web. CSDILA Platform was then implemented via number of technologies based on the guidelines provided by the framework. The platform has a modular structure and uses Service-Oriented Architecture (SOA). It is capable of managing spatial objects in a 4D data store and can flexibly incorporate a variety of developed models using the platform's API. Development scenarios can be modeled and tested using the analysis and modeling component in the platform and the results are visualized in seamless 3D environment. The platform was further tested using number of scenarios and showed promising results and potentials to serve a wider need. In this paper, the design process of the generic framework, the implementation of CSDILA Platform and technologies used, and also findings and future research directions will be presented and discussed.

Conveying Clinical Reasoning Based on Visual Observation via Eye-Movement Modelling Examples

ERIC Educational Resources Information Center

Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nystrom, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit

2012-01-01

Complex perceptual tasks, like clinical reasoning based on visual observations of patients, require not only conceptual knowledge about diagnostic classes but also the skills to visually search for symptoms and interpret these observations. However, medical education so far has focused very little on how visual observation skills can be…

Multi-sensory landscape assessment: the contribution of acoustic perception to landscape evaluation.

PubMed

Gan, Yonghong; Luo, Tao; Breitung, Werner; Kang, Jian; Zhang, Tianhai

2014-12-01

In this paper, the contribution of visual and acoustic preference to multi-sensory landscape evaluation was quantitatively compared. The real landscapes were treated as dual-sensory ambiance and separated into visual landscape and soundscape. Both were evaluated by 63 respondents in laboratory conditions. The analysis of the relationship between respondent's visual and acoustic preference as well as their respective contribution to landscape preference showed that (1) some common attributes are universally identified in assessing visual, aural and audio-visual preference, such as naturalness or degree of human disturbance; (2) with acoustic and visual preferences as variables, a multi-variate linear regression model can satisfactorily predict landscape preference (R(2 )= 0.740), while the coefficients of determination for a unitary linear regression model were 0.345 and 0.720 for visual and acoustic preference as predicting factors, respectively; (3) acoustic preference played a much more important role in landscape evaluation than visual preference in this study (the former is about 4.5 times of the latter), which strongly suggests a rethinking of the role of soundscape in environment perception research and landscape planning practice.

Visual Field Map Clusters in Macaque Extrastriate Visual Cortex

PubMed Central

Kolster, Hauke; Mandeville, Joseph B.; Arsenault, John T.; Ekstrom, Leeland B.; Wald, Lawrence L.; Vanduffel, Wim

2009-01-01

The macaque visual cortex contains more than 30 different functional visual areas, yet surprisingly little is known about the underlying organizational principles that structure its components into a complete ‘visual’ unit. A recent model of visual cortical organization in humans suggests that visual field maps are organized as clusters. Clusters minimize axonal connections between individual field maps that represent common visual percepts, with different clusters thought to carry out different functions. Experimental support for this hypothesis, however, is lacking in macaques, leaving open the question of whether it is unique to humans or a more general model for primate vision. Here we show, using high-resolution BOLD fMRI data in the awake monkey at 7 Tesla, that area MT/V5 and its neighbors are organized as a cluster with a common foveal representation and a circular eccentricity map. This novel view on the functional topography of area MT/V5 and satellites indicates that field map clusters are evolutionarily preserved and may be a fundamental organizational principle of the old world primate visual cortex. PMID:19474330

Human infrared vision is triggered by two-photon chromophore isomerization

PubMed Central

Palczewska, Grazyna; Vinberg, Frans; Stremplewski, Patrycjusz; Bircher, Martin P.; Salom, David; Komar, Katarzyna; Zhang, Jianye; Cascella, Michele; Wojtkowski, Maciej; Kefalov, Vladimir J.; Palczewski, Krzysztof

2014-01-01

Vision relies on photoactivation of visual pigments in rod and cone photoreceptor cells of the retina. The human eye structure and the absorption spectra of pigments limit our visual perception of light. Our visual perception is most responsive to stimulating light in the 400- to 720-nm (visible) range. First, we demonstrate by psychophysical experiments that humans can perceive infrared laser emission as visible light. Moreover, we show that mammalian photoreceptors can be directly activated by near infrared light with a sensitivity that paradoxically increases at wavelengths above 900 nm, and display quadratic dependence on laser power, indicating a nonlinear optical process. Biochemical experiments with rhodopsin, cone visual pigments, and a chromophore model compound 11-cis-retinyl-propylamine Schiff base demonstrate the direct isomerization of visual chromophore by a two-photon chromophore isomerization. Indeed, quantum mechanics modeling indicates the feasibility of this mechanism. Together, these findings clearly show that human visual perception of near infrared light occurs by two-photon isomerization of visual pigments. PMID:25453064

Temporal precision in the visual pathway through the interplay of excitation and stimulus-driven suppression.

PubMed

Butts, Daniel A; Weng, Chong; Jin, Jianzhong; Alonso, Jose-Manuel; Paninski, Liam

2011-08-03

Visual neurons can respond with extremely precise temporal patterning to visual stimuli that change on much slower time scales. Here, we investigate how the precise timing of cat thalamic spike trains-which can have timing as precise as 1 ms-is related to the stimulus, in the context of both artificial noise and natural visual stimuli. Using a nonlinear modeling framework applied to extracellular data, we demonstrate that the precise timing of thalamic spike trains can be explained by the interplay between an excitatory input and a delayed suppressive input that resembles inhibition, such that neuronal responses only occur in brief windows where excitation exceeds suppression. The resulting description of thalamic computation resembles earlier models of contrast adaptation, suggesting a more general role for mechanisms of contrast adaptation in visual processing. Thus, we describe a more complex computation underlying thalamic responses to artificial and natural stimuli that has implications for understanding how visual information is represented in the early stages of visual processing.

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.

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

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.

Printing Space: Using 3D Printing of Digital Terrain Models in Geosciences Education and Research

ERIC Educational Resources Information Center

Horowitz, Seth S.; Schultz, Peter H.

2014-01-01

Data visualization is a core component of every scientific project; however, generation of physical models previously depended on expensive or labor-intensive molding, sculpting, or laser sintering techniques. Physical models have the advantage of providing not only visual but also tactile modes of inspection, thereby allowing easier visual…

Developmental Visual Dysfunction: Models for Assessment and Management.

ERIC Educational Resources Information Center

Erhardt, Rhoda Priest

This book describes transdisciplinary management of multiply disabled children with vision problems and presents four theoretical models of visual assessment and three illustrative case studies in a sequence appropriate to the learning process. The first three models are intended to lead to assessment and management of the child and the last to…

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.

Discrimination of numerical proportions: A comparison of binomial and Gaussian models.

PubMed

Raidvee, Aire; Lember, Jüri; Allik, Jüri

2017-01-01

Observers discriminated the numerical proportion of two sets of elements (N = 9, 13, 33, and 65) that differed either by color or orientation. According to the standard Thurstonian approach, the accuracy of proportion discrimination is determined by irreducible noise in the nervous system that stochastically transforms the number of presented visual elements onto a continuum of psychological states representing numerosity. As an alternative to this customary approach, we propose a Thurstonian-binomial model, which assumes discrete perceptual states, each of which is associated with a certain visual element. It is shown that the probability β with which each visual element can be noticed and registered by the perceptual system can explain data of numerical proportion discrimination at least as well as the continuous Thurstonian-Gaussian model, and better, if the greater parsimony of the Thurstonian-binomial model is taken into account using AIC model selection. We conclude that Gaussian and binomial models represent two different fundamental principles-internal noise vs. using only a fraction of available information-which are both plausible descriptions of visual perception.

Are visual peripheries forever young?

PubMed

Burnat, Kalina

2015-01-01

The paper presents a concept of lifelong plasticity of peripheral vision. Central vision processing is accepted as critical and irreplaceable for normal perception in humans. While peripheral processing chiefly carries information about motion stimuli features and redirects foveal attention to new objects, it can also take over functions typical for central vision. Here I review the data showing the plasticity of peripheral vision found in functional, developmental, and comparative studies. Even though it is well established that afferent projections from central and peripheral retinal regions are not established simultaneously during early postnatal life, central vision is commonly used as a general model of development of the visual system. Based on clinical studies and visually deprived animal models, I describe how central and peripheral visual field representations separately rely on early visual experience. Peripheral visual processing (motion) is more affected by binocular visual deprivation than central visual processing (spatial resolution). In addition, our own experimental findings show the possible recruitment of coarse peripheral vision for fine spatial analysis. Accordingly, I hypothesize that the balance between central and peripheral visual processing, established in the course of development, is susceptible to plastic adaptations during the entire life span, with peripheral vision capable of taking over central processing.

Vivaldi: visualization and validation of biomacromolecular NMR structures from the PDB.

PubMed

Hendrickx, Pieter M S; Gutmanas, Aleksandras; Kleywegt, Gerard J

2013-04-01

We describe Vivaldi (VIsualization and VALidation DIsplay; http://pdbe.org/vivaldi), a web-based service for the analysis, visualization, and validation of NMR structures in the Protein Data Bank (PDB). Vivaldi provides access to model coordinates and several types of experimental NMR data using interactive visualization tools, augmented with structural annotations and model-validation information. The service presents information about the modeled NMR ensemble, validation of experimental chemical shifts, residual dipolar couplings, distance and dihedral angle constraints, as well as validation scores based on empirical knowledge and databases. Vivaldi was designed for both expert NMR spectroscopists and casual non-expert users who wish to obtain a better grasp of the information content and quality of NMR structures in the public archive. Copyright © 2013 Wiley Periodicals, Inc.

Identifying the computational requirements of an integrated top-down-bottom-up model for overt visual attention within an active vision system.

PubMed

McBride, Sebastian; Huelse, Martin; Lee, Mark

2013-01-01

Computational visual attention systems have been constructed in order for robots and other devices to detect and locate regions of interest in their visual world. Such systems often attempt to take account of what is known of the human visual system and employ concepts, such as 'active vision', to gain various perceived advantages. However, despite the potential for gaining insights from such experiments, the computational requirements for visual attention processing are often not clearly presented from a biological perspective. This was the primary objective of this study, attained through two specific phases of investigation: 1) conceptual modeling of a top-down-bottom-up framework through critical analysis of the psychophysical and neurophysiological literature, 2) implementation and validation of the model into robotic hardware (as a representative of an active vision system). Seven computational requirements were identified: 1) transformation of retinotopic to egocentric mappings, 2) spatial memory for the purposes of medium-term inhibition of return, 3) synchronization of 'where' and 'what' information from the two visual streams, 4) convergence of top-down and bottom-up information to a centralized point of information processing, 5) a threshold function to elicit saccade action, 6) a function to represent task relevance as a ratio of excitation and inhibition, and 7) derivation of excitation and inhibition values from object-associated feature classes. The model provides further insight into the nature of data representation and transfer between brain regions associated with the vertebrate 'active' visual attention system. In particular, the model lends strong support to the functional role of the lateral intraparietal region of the brain as a primary area of information consolidation that directs putative action through the use of a 'priority map'.

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®.

Identifying the Computational Requirements of an Integrated Top-Down-Bottom-Up Model for Overt Visual Attention within an Active Vision System

PubMed Central

McBride, Sebastian; Huelse, Martin; Lee, Mark

2013-01-01

Computational visual attention systems have been constructed in order for robots and other devices to detect and locate regions of interest in their visual world. Such systems often attempt to take account of what is known of the human visual system and employ concepts, such as ‘active vision’, to gain various perceived advantages. However, despite the potential for gaining insights from such experiments, the computational requirements for visual attention processing are often not clearly presented from a biological perspective. This was the primary objective of this study, attained through two specific phases of investigation: 1) conceptual modeling of a top-down-bottom-up framework through critical analysis of the psychophysical and neurophysiological literature, 2) implementation and validation of the model into robotic hardware (as a representative of an active vision system). Seven computational requirements were identified: 1) transformation of retinotopic to egocentric mappings, 2) spatial memory for the purposes of medium-term inhibition of return, 3) synchronization of ‘where’ and ‘what’ information from the two visual streams, 4) convergence of top-down and bottom-up information to a centralized point of information processing, 5) a threshold function to elicit saccade action, 6) a function to represent task relevance as a ratio of excitation and inhibition, and 7) derivation of excitation and inhibition values from object-associated feature classes. The model provides further insight into the nature of data representation and transfer between brain regions associated with the vertebrate ‘active’ visual attention system. In particular, the model lends strong support to the functional role of the lateral intraparietal region of the brain as a primary area of information consolidation that directs putative action through the use of a ‘priority map’. PMID:23437044

Visual guidance of mobile platforms

NASA Astrophysics Data System (ADS)

Blissett, Rodney J.

1993-12-01

Two systems are described and results presented demonstrating aspects of real-time visual guidance of autonomous mobile platforms. The first approach incorporates prior knowledge in the form of rigid geometrical models linking visual references within the environment. The second approach is based on a continuous synthesis of information extracted from image tokens to generate a coarse-grained world model, from which potential obstacles are inferred. The use of these techniques in workplace applications is discussed.

What Makes a Message Stick? The Role of Content and Context in Social Media Epidemics

DTIC Science & Technology

2013-09-23

First, we propose visual memes , or frequently re-posted short video segments, for detecting and monitoring latent video interactions at scale. Content...interactions (such as quoting, or remixing, parts of a video). Visual memes are extracted by scalable detection algorithms that we develop, with...high accuracy. We further augment visual memes with text, via a statistical model of latent topics. We model content interactions on YouTube with

a Novel Ship Detection Method for Large-Scale Optical Satellite Images Based on Visual Lbp Feature and Visual Attention Model

NASA Astrophysics Data System (ADS)

Haigang, Sui; Zhina, Song

2016-06-01

Reliably ship detection in optical satellite images has a wide application in both military and civil fields. However, this problem is very difficult in complex backgrounds, such as waves, clouds, and small islands. Aiming at these issues, this paper explores an automatic and robust model for ship detection in large-scale optical satellite images, which relies on detecting statistical signatures of ship targets, in terms of biologically-inspired visual features. This model first selects salient candidate regions across large-scale images by using a mechanism based on biologically-inspired visual features, combined with visual attention model with local binary pattern (CVLBP). Different from traditional studies, the proposed algorithm is high-speed and helpful to focus on the suspected ship areas avoiding the separation step of land and sea. Largearea images are cut into small image chips and analyzed in two complementary ways: Sparse saliency using visual attention model and detail signatures using LBP features, thus accordant with sparseness of ship distribution on images. Then these features are employed to classify each chip as containing ship targets or not, using a support vector machine (SVM). After getting the suspicious areas, there are still some false alarms such as microwaves and small ribbon clouds, thus simple shape and texture analysis are adopted to distinguish between ships and nonships in suspicious areas. Experimental results show the proposed method is insensitive to waves, clouds, illumination and ship size.

Comparing visual representations across human fMRI and computational vision

PubMed Central

Leeds, Daniel D.; Seibert, Darren A.; Pyles, John A.; Tarr, Michael J.

2013-01-01

Feedforward visual object perception recruits a cortical network that is assumed to be hierarchical, progressing from basic visual features to complete object representations. However, the nature of the intermediate features related to this transformation remains poorly understood. Here, we explore how well different computer vision recognition models account for neural object encoding across the human cortical visual pathway as measured using fMRI. These neural data, collected during the viewing of 60 images of real-world objects, were analyzed with a searchlight procedure as in Kriegeskorte, Goebel, and Bandettini (2006): Within each searchlight sphere, the obtained patterns of neural activity for all 60 objects were compared to model responses for each computer recognition algorithm using representational dissimilarity analysis (Kriegeskorte et al., 2008). Although each of the computer vision methods significantly accounted for some of the neural data, among the different models, the scale invariant feature transform (Lowe, 2004), encoding local visual properties gathered from “interest points,” was best able to accurately and consistently account for stimulus representations within the ventral pathway. More generally, when present, significance was observed in regions of the ventral-temporal cortex associated with intermediate-level object perception. Differences in model effectiveness and the neural location of significant matches may be attributable to the fact that each model implements a different featural basis for representing objects (e.g., more holistic or more parts-based). Overall, we conclude that well-known computer vision recognition systems may serve as viable proxies for theories of intermediate visual object representation. PMID:24273227

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.

Integrating Visualizations into Modeling NEST Simulations

PubMed Central

Nowke, Christian; Zielasko, Daniel; Weyers, Benjamin; Peyser, Alexander; Hentschel, Bernd; Kuhlen, Torsten W.

2015-01-01

Modeling large-scale spiking neural networks showing realistic biological behavior in their dynamics is a complex and tedious task. Since these networks consist of millions of interconnected neurons, their simulation produces an immense amount of data. In recent years it has become possible to simulate even larger networks. However, solutions to assist researchers in understanding the simulation's complex emergent behavior by means of visualization are still lacking. While developing tools to partially fill this gap, we encountered the challenge to integrate these tools easily into the neuroscientists' daily workflow. To understand what makes this so challenging, we looked into the workflows of our collaborators and analyzed how they use the visualizations to solve their daily problems. We identified two major issues: first, the analysis process can rapidly change focus which requires to switch the visualization tool that assists in the current problem domain. Second, because of the heterogeneous data that results from simulations, researchers want to relate data to investigate these effectively. Since a monolithic application model, processing and visualizing all data modalities and reflecting all combinations of possible workflows in a holistic way, is most likely impossible to develop and to maintain, a software architecture that offers specialized visualization tools that run simultaneously and can be linked together to reflect the current workflow, is a more feasible approach. To this end, we have developed a software architecture that allows neuroscientists to integrate visualization tools more closely into the modeling tasks. In addition, it forms the basis for semantic linking of different visualizations to reflect the current workflow. In this paper, we present this architecture and substantiate the usefulness of our approach by common use cases we encountered in our collaborative work. PMID:26733860

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

Long-Lasting Crossmodal Cortical Reorganization Triggered by Brief Postnatal Visual Deprivation.

PubMed

Collignon, Olivier; Dormal, Giulia; de Heering, Adelaide; Lepore, Franco; Lewis, Terri L; Maurer, Daphne

2015-09-21

Animal and human studies have demonstrated that transient visual deprivation early in life, even for a very short period, permanently alters the response properties of neurons in the visual cortex and leads to corresponding behavioral visual deficits. While it is acknowledged that early-onset and longstanding blindness leads the occipital cortex to respond to non-visual stimulation, it remains unknown whether a short and transient period of postnatal visual deprivation is sufficient to trigger crossmodal reorganization that persists after years of visual experience. In the present study, we characterized brain responses to auditory stimuli in 11 adults who had been deprived of all patterned vision at birth by congenital cataracts in both eyes until they were treated at 9 to 238 days of age. When compared to controls with typical visual experience, the cataract-reversal group showed enhanced auditory-driven activity in focal visual regions. A combination of dynamic causal modeling with Bayesian model selection indicated that this auditory-driven activity in the occipital cortex was better explained by direct cortico-cortical connections with the primary auditory cortex than by subcortical connections. Thus, a short and transient period of visual deprivation early in life leads to enduring large-scale crossmodal reorganization of the brain circuitry typically dedicated to vision. Copyright © 2015 Elsevier Ltd. All rights reserved.

MBSE-Driven Visualization of Requirements Allocation and Traceability

NASA Technical Reports Server (NTRS)

Jackson, Maddalena; Wilkerson, Marcus

2016-01-01

In a Model Based Systems Engineering (MBSE) infusion effort, there is a usually a concerted effort to define the information architecture, ontologies, and patterns that drive the construction and architecture of MBSE models, but less attention is given to the logical follow-on of that effort: how to practically leverage the resulting semantic richness of a well-formed populated model to enable systems engineers to work more effectively, as MBSE promises. While ontologies and patterns are absolutely necessary, an MBSE effort must also design and provide practical demonstration of value (through human-understandable representations of model data that address stakeholder concerns) or it will not succeed. This paper will discuss opportunities that exist for visualization in making the richness of a well-formed model accessible to stakeholders, specifically stakeholders who rely on the model for their day-to-day work. This paper will discuss the value added by MBSE-driven visualizations in the context of a small case study of interactive visualizations created and used on NASA's proposed Europa Mission. The case study visualizations were created for the purpose of understanding and exploring targeted aspects of requirements flow, allocation, and comparing the structure of that flow-down to a conceptual project decomposition. The work presented in this paper is an example of a product that leverages the richness and formalisms of our knowledge representation while also responding to the quality attributes SEs care about.

The Attentional Field Revealed by Single-Voxel Modeling of fMRI Time Courses

PubMed Central

DeYoe, Edgar A.

2015-01-01

The spatial topography of visual attention is a distinguishing and critical feature of many theoretical models of visuospatial attention. Previous fMRI-based measurements of the topography of attention have typically been too crude to adequately test the predictions of different competing models. This study demonstrates a new technique to make detailed measurements of the topography of visuospatial attention from single-voxel, fMRI time courses. Briefly, this technique involves first estimating a voxel's population receptive field (pRF) and then “drifting” attention through the pRF such that the modulation of the voxel's fMRI time course reflects the spatial topography of attention. The topography of the attentional field (AF) is then estimated using a time-course modeling procedure. Notably, we are able to make these measurements in many visual areas including smaller, higher order areas, thus enabling a more comprehensive comparison of attentional mechanisms throughout the full hierarchy of human visual cortex. Using this technique, we show that the AF scales with eccentricity and varies across visual areas. We also show that voxels in multiple visual areas exhibit suppressive attentional effects that are well modeled by an AF having an enhancing Gaussian center with a suppressive surround. These findings provide extensive, quantitative neurophysiological data for use in modeling the psychological effects of visuospatial attention. PMID:25810532

Visual perception and appraisal of persons with impairments: a randomised controlled field experiment using photo elicitation.

PubMed

Reinhardt, Jan Dietrich; Ballert, Carolina Saskia; Fellinghauer, Bernd; Lötscher, Alexander; Gradinger, Felix; Hilfiker, Roger; Graf, Sibylle; Stucki, Gerold

2011-01-01

Visual cues from persons with impairments may trigger stereotypical generalisations that lead to prejudice and discrimination. The main objective of this pilot study is to examine whether visual stimuli of impairment activate latent prejudice against disability and whether this connection can be counteracted with priming strategies. In a field experiment, participants were asked to rate photographs showing models with mental impairments, wheelchair users with paraplegia, and persons without any visible impairment. Participants should appraise the models with regard to several features (e.g. communicativeness, intelligence). One hundred participants rated 12 photo models yielding a total of 1183 observations. One group of participants was primed with a cover story introducing visual perception of impairment as the study's gist, while controls received neutral information. Photo models with mental impairments were rated lowest and models without visible impairment highest. In participants who did not have prior contacts with persons with impairments, priming led to a levelling of scores of models with and without impairment. Prior contacts with persons with impairments created similar effects as the priming. Unexpectedly, a pattern of converse double discrimination to the disadvantage of men with mental impairments was revealed. Signs of stereotypical processing of visual cues of impairment have been found in participants of the Swiss general population. Personal contact with persons with impairments as well as priming participants seems to reduce stereotyping.

VISUALIZATION-BASED ANALYSIS FOR A MIXED-INHIBITION BINARY PBPK MODEL: DETERMINATION OF INHIBITION MECHANISM

EPA Science Inventory

A physiologically-based pharmacokinetic (PBPK) model incorporating mixed enzyme inhibition was used to determine the mechanism of metabolic interactions occurring during simultaneous exposures to the organic solvents chloroform and trichloroethylene (TCE). Visualization-based se...

Visual impairment in FOXG1-mutated individuals and mice.

PubMed

Boggio, E M; Pancrazi, L; Gennaro, M; Lo Rizzo, C; Mari, F; Meloni, I; Ariani, F; Panighini, A; Novelli, E; Biagioni, M; Strettoi, E; Hayek, J; Rufa, A; Pizzorusso, T; Renieri, A; Costa, M

2016-06-02

The Forkead Box G1 (FOXG1 in humans, Foxg1 in mice) gene encodes for a DNA-binding transcription factor, essential for the development of the telencephalon in mammalian forebrain. Mutations in FOXG1 have been reported to be involved in the onset of Rett Syndrome, for which sequence alterations of MECP2 and CDKL5 are known. While visual alterations are not classical hallmarks of Rett syndrome, an increasing body of evidence shows visual impairment in patients and in MeCP2 and CDKL5 animal models. Herein we focused on the functional role of FOXG1 in the visual system of animal models (Foxg1(+/Cre) mice) and of a cohort of subjects carrying FOXG1 mutations or deletions. Visual physiology of Foxg1(+/Cre) mice was assessed by visually evoked potentials, which revealed a significant reduction in response amplitude and visual acuity with respect to wild-type littermates. Morphological investigation showed abnormalities in the organization of excitatory/inhibitory circuits in the visual cortex. No alterations were observed in retinal structure. By examining a cohort of FOXG1-mutated individuals with a panel of neuro-ophthalmological assessments, we found that all of them exhibited visual alterations compatible with high-level visual dysfunctions. In conclusion our data show that Foxg1 haploinsufficiency results in an impairment of mouse and human visual cortical function. Copyright © 2016 IBRO. Published by Elsevier Ltd. All rights reserved.

Ambiguous science and the visual representation of the real

NASA Astrophysics Data System (ADS)

Newbold, Curtis Robert

The emergence of visual media as prominent and even expected forms of communication in nearly all disciplines, including those scientific, has raised new questions about how the art and science of communication epistemologically affect the interpretation of scientific phenomena. In this dissertation I explore how the influence of aesthetics in visual representations of science inevitably creates ambiguous meanings. As a means to improve visual literacy in the sciences, I call awareness to the ubiquity of visual ambiguity and its importance and relevance in scientific discourse. To do this, I conduct a literature review that spans interdisciplinary research in communication, science, art, and rhetoric. Furthermore, I create a paradoxically ambiguous taxonomy, which functions to exploit the nuances of visual ambiguities and their role in scientific communication. I then extrapolate the taxonomy of visual ambiguity and from it develop an ambiguous, rhetorical heuristic, the Tetradic Model of Visual Ambiguity. The Tetradic Model is applied to a case example of a scientific image as a demonstration of how scientific communicators may increase their awareness of the epistemological effects of ambiguity in the visual representations of science. I conclude by demonstrating how scientific communicators may make productive use of visual ambiguity, even in communications of objective science, and I argue how doing so strengthens scientific communicators' visual literacy skills and their ability to communicate more ethically and effectively.

Generalized information fusion and visualization using spatial voting and data modeling

NASA Astrophysics Data System (ADS)

Jaenisch, Holger M.; Handley, James W.

2013-05-01

We present a novel and innovative information fusion and visualization framework for multi-source intelligence (multiINT) data using Spatial Voting (SV) and Data Modeling. We describe how different sources of information can be converted into numerical form for further processing downstream, followed by a short description of how this information can be fused using the SV grid. As an illustrative example, we show the modeling of cyberspace as cyber layers for the purpose of tracking cyber personas. Finally we describe a path ahead for creating interactive agile networks through defender customized Cyber-cubes for network configuration and attack visualization.

Information processing occurs via critical avalanches in a model of the primary visual cortex

NASA Astrophysics Data System (ADS)

Bortolotto, G. S.; Girardi-Schappo, M.; Gonsalves, J. J.; Pinto, L. T.; Tragtenberg, M. H. R.

2016-01-01

We study a new biologically motivated model for the Macaque monkey primary visual cortex which presents power-law avalanches after a visual stimulus. The signal propagates through all the layers of the model via avalanches that depend on network structure and synaptic parameter. We identify four different avalanche profiles as a function of the excitatory postsynaptic potential. The avalanches follow a size-duration scaling relation and present critical exponents that match experiments. The structure of the network gives rise to a regime of two characteristic spatial scales, one of which vanishes in the thermodynamic limit.

The Effect of Visual Information on the Manual Approach and Landing

NASA Technical Reports Server (NTRS)

Wewerinke, P. H.

1982-01-01

The effect of visual information in combination with basic display information on the approach performance. A pre-experimental model analysis was performed in terms of the optimal control model. The resulting aircraft approach performance predictions were compared with the results of a moving base simulator program. The results illustrate that the model provides a meaningful description of the visual (scene) perception process involved in the complex (multi-variable, time varying) manual approach task with a useful predictive capability. The theoretical framework was shown to allow a straight-forward investigation of the complex interaction of a variety of task variables.

Improved contour detection model with spatial summation properties based on nonclassical receptive field

NASA Astrophysics Data System (ADS)

Lin, Chuan; Xu, Guili; Cao, Yijun; Liang, Chenghua; Li, Ya

2016-07-01

The responses of cortical neurons to a stimulus in a classical receptive field (CRF) can be modulated by stimulating the non-CRF (nCRF) of neurons in the primary visual cortex (V1). In the very early stages (at around 40 ms), a neuron in V1 exhibits strong responses to a small set of stimuli. Later, however (after 100 ms), the neurons in V1 become sensitive to the scene's global organization. As per these visual cortical mechanisms, a contour detection model based on the spatial summation properties is proposed. Unlike in previous studies, the responses of the nCRF to the higher visual cortex that results in the inhibition of the neuronal responses in the primary visual cortex by the feedback pathway are considered. In this model, the individual neurons in V1 receive global information from the higher visual cortex to participate in the inhibition process. Computationally, global Gabor energy features are involved, leading to the more coherent physiological characteristics of the nCRF. We conducted an experiment where we compared our model with those proposed by other researchers. Our model explains the role of the mutual inhibition of neurons in V1, together with an approach for object recognition in machine vision.

Research on strategy marine noise map based on i4ocean platform: Constructing flow and key approach

NASA Astrophysics Data System (ADS)

Huang, Baoxiang; Chen, Ge; Han, Yong

2016-02-01

Noise level in a marine environment has raised extensive concern in the scientific community. The research is carried out on i4Ocean platform following the process of ocean noise model integrating, noise data extracting, processing, visualizing, and interpreting, ocean noise map constructing and publishing. For the convenience of numerical computation, based on the characteristics of ocean noise field, a hybrid model related to spatial locations is suggested in the propagation model. The normal mode method K/I model is used for far field and ray method CANARY model is used for near field. Visualizing marine ambient noise data is critical to understanding and predicting marine noise for relevant decision making. Marine noise map can be constructed on virtual ocean scene. The systematic marine noise visualization framework includes preprocessing, coordinate transformation interpolation, and rendering. The simulation of ocean noise depends on realistic surface. Then the dynamic water simulation gird was improved with GPU fusion to achieve seamless combination with the visualization result of ocean noise. At the same time, the profile and spherical visualization include space, and time dimensionality were also provided for the vertical field characteristics of ocean ambient noise. Finally, marine noise map can be published with grid pre-processing and multistage cache technology to better serve the public.

Information measures for terrain visualization

NASA Astrophysics Data System (ADS)

Bonaventura, Xavier; Sima, Aleksandra A.; Feixas, Miquel; Buckley, Simon J.; Sbert, Mateu; Howell, John A.

2017-02-01

Many quantitative and qualitative studies in geoscience research are based on digital elevation models (DEMs) and 3D surfaces to aid understanding of natural and anthropogenically-influenced topography. As well as their quantitative uses, the visual representation of DEMs can add valuable information for identifying and interpreting topographic features. However, choice of viewpoints and rendering styles may not always be intuitive, especially when terrain data are augmented with digital image texture. In this paper, an information-theoretic framework for object understanding is applied to terrain visualization and terrain view selection. From a visibility channel between a set of viewpoints and the component polygons of a 3D terrain model, we obtain three polygonal information measures. These measures are used to visualize the information associated with each polygon of the terrain model. In order to enhance the perception of the terrain's shape, we explore the effect of combining the calculated information measures with the supplementary digital image texture. From polygonal information, we also introduce a method to select a set of representative views of the terrain model. Finally, we evaluate the behaviour of the proposed techniques using example datasets. A publicly available framework for both the visualization and the view selection of a terrain has been created in order to provide the possibility to analyse any terrain model.

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.

Visual prosthesis wireless energy transfer system optimal modeling.

PubMed

Li, Xueping; Yang, Yuan; Gao, Yong

2014-01-16

Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling's more accuracy for the actual application. The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system's further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application.

Advanced Technology for Portable Personal Visualization.

DTIC Science & Technology

1992-06-01

interactive radiosity . 6 Advanced Technology for Portable Personal Visualization Progress Report January-June 1992 9 2.5 Virtual-Environment Ultrasound...the system, with support for textures, model partitioning, more complex radiosity emitters, and the replacement of model parts with objects from our...model libraries. "* Add real-time, interactive radiosity to the display program on Pixel-Planes 5. "* Move the real-time model mesh-generation to the

Simple control-theoretic models of human steering activity in visually guided vehicle control

NASA Technical Reports Server (NTRS)

Hess, Ronald A.

1991-01-01

A simple control theoretic model of human steering or control activity in the lateral-directional control of vehicles such as automobiles and rotorcraft is discussed. The term 'control theoretic' is used to emphasize the fact that the model is derived from a consideration of well-known control system design principles as opposed to psychological theories regarding egomotion, etc. The model is employed to emphasize the 'closed-loop' nature of tasks involving the visually guided control of vehicles upon, or in close proximity to, the earth and to hypothesize how changes in vehicle dynamics can significantly alter the nature of the visual cues which a human might use in such tasks.

A Neural Marker of Medical Visual Expertise: Implications for Training

ERIC Educational Resources Information Center

Rourke, Liam; Cruikshank, Leanna C.; Shapke, Larissa; Singhal, Anthony

2016-01-01

Researchers have identified a component of the EEG that discriminates visual experts from novices. The marker indexes a comprehensive model of visual processing, and if it is apparent in physicians, it could be used to investigate the development and training of their visual expertise. The purpose of this study was to determine whether a neural…

Visual and Verbal Learning in a Genetic Metabolic Disorder

ERIC Educational Resources Information Center

Spilkin, Amy M.; Ballantyne, Angela O.; Trauner, Doris A.

2009-01-01

Visual and verbal learning in a genetic metabolic disorder (cystinosis) were examined in the following three studies. The goal of Study I was to provide a normative database and establish the reliability and validity of a new test of visual learning and memory (Visual Learning and Memory Test; VLMT) that was modeled after a widely used test of…

Symbolic modeling of human anatomy for visualization and simulation

NASA Astrophysics Data System (ADS)

Pommert, Andreas; Schubert, Rainer; Riemer, Martin; Schiemann, Thomas; Tiede, Ulf; Hoehne, Karl H.

1994-09-01

Visualization of human anatomy in a 3D atlas requires both spatial and more abstract symbolic knowledge. Within our 'intelligent volume' model which integrates these two levels, we developed and implemented a semantic network model for describing human anatomy. Concepts for structuring (abstraction levels, domains, views, generic and case-specific modeling, inheritance) are introduced. Model, tools for generation and exploration and applications in our 3D anatomical atlas are presented and discussed.

High resolution renderings and interactive visualization of the 2006 Huntington Beach experiment

NASA Astrophysics Data System (ADS)

Im, T.; Nayak, A.; Keen, C.; Samilo, D.; Matthews, J.

2006-12-01

The Visualization Center at the Scripps Institution of Oceanography investigates innovative ways to represent graphically interactive 3D virtual landscapes and to produce high resolution, high quality renderings of Earth sciences data and the sensors and instruments used to collect the data . Among the Visualization Center's most recent work is the visualization of the Huntington Beach experiment, a study launched in July 2006 by the Southern California Ocean Observing System (http://www.sccoos.org/) to record and synthesize data of the Huntington Beach coastal region. Researchers and students at the Visualization Center created visual presentations that combine bathymetric data provided by SCCOOS with USGS aerial photography and with 3D polygonal models of sensors created in Maya into an interactive 3D scene using the Fledermaus suite of visualization tools (http://www.ivs3d.com). In addition, the Visualization Center has produced high definition (HD) animations of SCCOOS sensor instruments (e.g. REMUS, drifters, spray glider, nearshore mooring, OCSD/USGS mooring and CDIP mooring) using the Maya modeling and animation software and rendered over multiple nodes of the OptIPuter Visualization Cluster at Scripps. These visualizations are aimed at providing researchers with a broader context of sensor locations relative to geologic characteristics, to promote their use as an educational resource for informal education settings and increasing public awareness, and also as an aid for researchers' proposals and presentations. These visualizations are available for download on the Visualization Center website at http://siovizcenter.ucsd.edu/sccoos/hb2006.php.

Visualization of the tire-soil interaction area by means of ObjectARX programming interface

NASA Astrophysics Data System (ADS)

Mueller, W.; Gruszczyński, M.; Raba, B.; Lewicki, A.; Przybył, K.; Zaborowicz, M.; Koszela, K.; Boniecki, P.

2014-04-01

The process of data visualization, important for their analysis, becomes problematic when large data sets generated via computer simulations are available. This problem concerns, among others, the models that describe the geometry of tire-soil interaction. For the purpose of a graphical representation of this area and implementation of various geometric calculations the authors have developed a plug-in application for AutoCAD, based on the latest technologies, including ObjectARX, LINQ and the use of Visual Studio platform. Selected programming tools offer a wide variety of IT structures that enable data visualization and data analysis and are important e.g. in model verification.

NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization

PubMed Central

Parraga, C. Alejandro; Akbarinia, Arash

2016-01-01

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms. PMID:26954691

Sparse coding can predict primary visual cortex receptive field changes induced by abnormal visual input.

PubMed

Hunt, Jonathan J; Dayan, Peter; Goodhill, Geoffrey J

2013-01-01

Receptive fields acquired through unsupervised learning of sparse representations of natural scenes have similar properties to primary visual cortex (V1) simple cell receptive fields. However, what drives in vivo development of receptive fields remains controversial. The strongest evidence for the importance of sensory experience in visual development comes from receptive field changes in animals reared with abnormal visual input. However, most sparse coding accounts have considered only normal visual input and the development of monocular receptive fields. Here, we applied three sparse coding models to binocular receptive field development across six abnormal rearing conditions. In every condition, the changes in receptive field properties previously observed experimentally were matched to a similar and highly faithful degree by all the models, suggesting that early sensory development can indeed be understood in terms of an impetus towards sparsity. As previously predicted in the literature, we found that asymmetries in inter-ocular correlation across orientations lead to orientation-specific binocular receptive fields. Finally we used our models to design a novel stimulus that, if present during rearing, is predicted by the sparsity principle to lead robustly to radically abnormal receptive fields.

Sparse Coding Can Predict Primary Visual Cortex Receptive Field Changes Induced by Abnormal Visual Input

PubMed Central

Hunt, Jonathan J.; Dayan, Peter; Goodhill, Geoffrey J.

2013-01-01

Receptive fields acquired through unsupervised learning of sparse representations of natural scenes have similar properties to primary visual cortex (V1) simple cell receptive fields. However, what drives in vivo development of receptive fields remains controversial. The strongest evidence for the importance of sensory experience in visual development comes from receptive field changes in animals reared with abnormal visual input. However, most sparse coding accounts have considered only normal visual input and the development of monocular receptive fields. Here, we applied three sparse coding models to binocular receptive field development across six abnormal rearing conditions. In every condition, the changes in receptive field properties previously observed experimentally were matched to a similar and highly faithful degree by all the models, suggesting that early sensory development can indeed be understood in terms of an impetus towards sparsity. As previously predicted in the literature, we found that asymmetries in inter-ocular correlation across orientations lead to orientation-specific binocular receptive fields. Finally we used our models to design a novel stimulus that, if present during rearing, is predicted by the sparsity principle to lead robustly to radically abnormal receptive fields. PMID:23675290

NICE: A Computational Solution to Close the Gap from Colour Perception to Colour Categorization.

PubMed

Parraga, C Alejandro; Akbarinia, Arash

2016-01-01

The segmentation of visible electromagnetic radiation into chromatic categories by the human visual system has been extensively studied from a perceptual point of view, resulting in several colour appearance models. However, there is currently a void when it comes to relate these results to the physiological mechanisms that are known to shape the pre-cortical and cortical visual pathway. This work intends to begin to fill this void by proposing a new physiologically plausible model of colour categorization based on Neural Isoresponsive Colour Ellipsoids (NICE) in the cone-contrast space defined by the main directions of the visual signals entering the visual cortex. The model was adjusted to fit psychophysical measures that concentrate on the categorical boundaries and are consistent with the ellipsoidal isoresponse surfaces of visual cortical neurons. By revealing the shape of such categorical colour regions, our measures allow for a more precise and parsimonious description, connecting well-known early visual processing mechanisms to the less understood phenomenon of colour categorization. To test the feasibility of our method we applied it to exemplary images and a popular ground-truth chart obtaining labelling results that are better than those of current state-of-the-art algorithms.

Hyperspectral image visualization based on a human visual model

NASA Astrophysics Data System (ADS)

Zhang, Hongqin; Peng, Honghong; Fairchild, Mark D.; Montag, Ethan D.

2008-02-01

Hyperspectral image data can provide very fine spectral resolution with more than 200 bands, yet presents challenges for visualization techniques for displaying such rich information on a tristimulus monitor. This study developed a visualization technique by taking advantage of both the consistent natural appearance of a true color image and the feature separation of a PCA image based on a biologically inspired visual attention model. The key part is to extract the informative regions in the scene. The model takes into account human contrast sensitivity functions and generates a topographic saliency map for both images. This is accomplished using a set of linear "center-surround" operations simulating visual receptive fields as the difference between fine and coarse scales. A difference map between the saliency map of the true color image and that of the PCA image is derived and used as a mask on the true color image to select a small number of interesting locations where the PCA image has more salient features than available in the visible bands. The resulting representations preserve hue for vegetation, water, road etc., while the selected attentional locations may be analyzed by more advanced algorithms.

Using a Three-Dimensional Interactive Model To Teach Environmental Concepts to Visually Impaired Children.

ERIC Educational Resources Information Center

Budd, Julia M.; LaGrow, Steven J.

2000-01-01

A study investigated the efficacy of using the Buddy Road Kit, an interactive, wooden model, to teach environmental concepts to 4 children with visual impairments ages 7 to 11 years old. Results indicate the model was effective in teaching environmental concepts and traffic safety to the children involved. (Contains references.) (CR)

Associating Animations with Concrete Models to Enhance Students' Comprehension of Different Visual Representations in Organic Chemistry

ERIC Educational Resources Information Center

Al-Balushi, Sulaiman M.; Al-Hajri, Sheikha H.

2014-01-01

The purpose of the current study is to explore the impact of associating animations with concrete models on eleventh-grade students' comprehension of different visual representations in organic chemistry. The study used a post-test control group quasi-experimental design. The experimental group (N = 28) used concrete models, submicroscopic…

An Integrated Visualization and Basic Molecular Modeling Laboratory for First-Year Undergraduate Medicinal Chemistry

ERIC Educational Resources Information Center

Hayes, Joseph M.

2014-01-01

A 3D model visualization and basic molecular modeling laboratory suitable for first-year undergraduates studying introductory medicinal chemistry is presented. The 2 h practical is embedded within a series of lectures on drug design, target-drug interactions, enzymes, receptors, nucleic acids, and basic pharmacokinetics. Serving as a teaching aid…

Exploring Students' Visual Conception of Matter: Towards Developing a Teaching Framework Using Models

ERIC Educational Resources Information Center

Espinosa, Allen A.; Marasigan, Arlyne C.; Datukan, Janir T.

2016-01-01

This study explored how students visualise the states and classifications of matter with the use of scientific models. Misconceptions of students in using scientific models were also identified to formulate a teaching framework. To elicit data in the study, a Visual Conception Questionnaire was administered to thirty-four (34), firstyear, general…

Visual Modeling as a Motivation for Studying Mathematics and Art

ERIC Educational Resources Information Center

Sendova, Evgenia; Grkovska, Slavica

2005-01-01

The paper deals with the possibility of enriching the curriculum in mathematics, informatics and art by means of visual modeling of abstract paintings. The authors share their belief that in building a computer model of a construct, one gains deeper insight into the construct, and is motivated to elaborate one's knowledge in mathematics and…

Recent Advances in Immersive Visualization of Ocean Data: Virtual Reality Through the Web on Your Laptop Computer

NASA Astrophysics Data System (ADS)

Hermann, A. J.; Moore, C.; Soreide, N. N.

2002-12-01

Ocean circulation is irrefutably three dimensional, and powerful new measurement technologies and numerical models promise to expand our three-dimensional knowledge of the dynamics further each year. Yet, most ocean data and model output is still viewed using two-dimensional maps. Immersive visualization techniques allow the investigator to view their data as a three dimensional world of surfaces and vectors which evolves through time. The experience is not unlike holding a part of the ocean basin in one's hand, turning and examining it from different angles. While immersive, three dimensional visualization has been possible for at least a decade, the technology was until recently inaccessible (both physically and financially) for most researchers. It is not yet fully appreciated by practicing oceanographers how new, inexpensive computing hardware and software (e.g. graphics cards and controllers designed for the huge PC gaming market) can be employed for immersive, three dimensional, color visualization of their increasingly huge datasets and model output. In fact, the latest developments allow immersive visualization through web servers, giving scientists the ability to "fly through" three-dimensional data stored half a world away. Here we explore what additional insight is gained through immersive visualization, describe how scientists of very modest means can easily avail themselves of the latest technology, and demonstrate its implementation on a web server for Pacific Ocean model output.

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.

Predicting Cortical Dark/Bright Asymmetries from Natural Image Statistics and Early Visual Transforms

PubMed Central

Cooper, Emily A.; Norcia, Anthony M.

2015-01-01

The nervous system has evolved in an environment with structure and predictability. One of the ubiquitous principles of sensory systems is the creation of circuits that capitalize on this predictability. Previous work has identified predictable non-uniformities in the distributions of basic visual features in natural images that are relevant to the encoding tasks of the visual system. Here, we report that the well-established statistical distributions of visual features -- such as visual contrast, spatial scale, and depth -- differ between bright and dark image components. Following this analysis, we go on to trace how these differences in natural images translate into different patterns of cortical input that arise from the separate bright (ON) and dark (OFF) pathways originating in the retina. We use models of these early visual pathways to transform natural images into statistical patterns of cortical input. The models include the receptive fields and non-linear response properties of the magnocellular (M) and parvocellular (P) pathways, with their ON and OFF pathway divisions. The results indicate that there are regularities in visual cortical input beyond those that have previously been appreciated from the direct analysis of natural images. In particular, several dark/bright asymmetries provide a potential account for recently discovered asymmetries in how the brain processes visual features, such as violations of classic energy-type models. On the basis of our analysis, we expect that the dark/bright dichotomy in natural images plays a key role in the generation of both cortical and perceptual asymmetries. PMID:26020624

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.

Visual prosthesis wireless energy transfer system optimal modeling

PubMed Central

2014-01-01

Background Wireless energy transfer system is an effective way to solve the visual prosthesis energy supply problems, theoretical modeling of the system is the prerequisite to do optimal energy transfer system design. Methods On the basis of the ideal model of the wireless energy transfer system, according to visual prosthesis application condition, the system modeling is optimized. During the optimal modeling, taking planar spiral coils as the coupling devices between energy transmitter and receiver, the effect of the parasitic capacitance of the transfer coil is considered, and especially the concept of biological capacitance is proposed to consider the influence of biological tissue on the energy transfer efficiency, resulting in the optimal modeling’s more accuracy for the actual application. Results The simulation data of the optimal model in this paper is compared with that of the previous ideal model, the results show that under high frequency condition, the parasitic capacitance of inductance and biological capacitance considered in the optimal model could have great impact on the wireless energy transfer system. The further comparison with the experimental data verifies the validity and accuracy of the optimal model proposed in this paper. Conclusions The optimal model proposed in this paper has a higher theoretical guiding significance for the wireless energy transfer system’s further research, and provide a more precise model reference for solving the power supply problem in visual prosthesis clinical application. PMID:24428906

Neural network modelling of the influence of channelopathies on reflex visual attention.

PubMed

Gravier, Alexandre; Quek, Chai; Duch, Włodzisław; Wahab, Abdul; Gravier-Rymaszewska, Joanna

2016-02-01

This paper introduces a model of Emergent Visual Attention in presence of calcium channelopathy (EVAC). By modelling channelopathy, EVAC constitutes an effort towards identifying the possible causes of autism. The network structure embodies the dual pathways model of cortical processing of visual input, with reflex attention as an emergent property of neural interactions. EVAC extends existing work by introducing attention shift in a larger-scale network and applying a phenomenological model of channelopathy. In presence of a distractor, the channelopathic network's rate of failure to shift attention is lower than the control network's, but overall, the control network exhibits a lower classification error rate. The simulation results also show differences in task-relative reaction times between control and channelopathic networks. The attention shift timings inferred from the model are consistent with studies of attention shift in autistic children.

Investigating the Use of 3d Geovisualizations for Urban Design in Informal Settlement Upgrading in South Africa

NASA Astrophysics Data System (ADS)

Rautenbach, V.; Coetzee, S.; Çöltekin, A.

2016-06-01

Informal settlements are a common occurrence in South Africa, and to improve in-situ circumstances of communities living in informal settlements, upgrades and urban design processes are necessary. Spatial data and maps are essential throughout these processes to understand the current environment, plan new developments, and communicate the planned developments. All stakeholders need to understand maps to actively participate in the process. However, previous research demonstrated that map literacy was relatively low for many planning professionals in South Africa, which might hinder effective planning. Because 3D visualizations resemble the real environment more than traditional maps, many researchers posited that they would be easier to interpret. Thus, our goal is to investigate the effectiveness of 3D geovisualizations for urban design in informal settlement upgrading in South Africa. We consider all involved processes: 3D modelling, visualization design, and cognitive processes during map reading. We found that procedural modelling is a feasible alternative to time-consuming manual modelling, and can produce high quality models. When investigating the visualization design, the visual characteristics of 3D models and relevance of a subset of visual variables for urban design activities of informal settlement upgrades were qualitatively assessed. The results of three qualitative user experiments contributed to understanding the impact of various levels of complexity in 3D city models and map literacy of future geoinformatics and planning professionals when using 2D maps and 3D models. The research results can assist planners in designing suitable 3D models that can be used throughout all phases of the process.

Neural dynamics of grouping and segmentation explain properties of visual crowding.

PubMed

Francis, Gregory; Manassi, Mauro; Herzog, Michael H

2017-07-01

Investigations of visual crowding, where a target is difficult to identify because of flanking elements, has largely used a theoretical perspective based on local interactions where flanking elements pool with or substitute for properties of the target. This successful theoretical approach has motivated a wide variety of empirical investigations to identify mechanisms that cause crowding, and it has suggested practical applications to mitigate crowding effects. However, this theoretical approach has been unable to account for a parallel set of findings that crowding is influenced by long-range perceptual grouping effects. When the target and flankers are perceived as part of separate visual groups, crowding tends to be quite weak. Here, we describe how theoretical mechanisms for grouping and segmentation in cortical neural circuits can account for a wide variety of these long-range grouping effects. Building on previous work, we explain how crowding occurs in the model and explain how grouping in the model involves connected boundary signals that represent a key aspect of visual information. We then introduce new circuits that allow nonspecific top-down selection signals to flow along connected boundaries or within a surface contained by boundaries and thereby induce a segmentation that can separate the visual information corresponding to the flankers from the visual information corresponding to the target. When such segmentation occurs, crowding is shown to be weak. We compare the model's behavior to 5 sets of experimental findings on visual crowding and show that the model does a good job explaining the key empirical findings. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Resource, Spring 2002

DTIC Science & Technology

2002-01-01

wrappers to other widely used languages, namely TCL/TK, Java, and Python . VTK is very powerful and covers polygonal models and image processing classes and...follows: � Large Data Visualization and Rendering � Information Visualization for Beginners � Rendering and Visualization in Parallel Environments

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.

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels

PubMed Central

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike’s information criterion (AICc) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis, the branchiopod water flea, Daphnia magna, normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus, which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei. The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography. PMID:28740757

Using electroretinograms and multi-model inference to identify spectral classes of photoreceptors and relative opsin expression levels.

PubMed

Lessios, Nicolas

2017-01-01

Understanding how individual photoreceptor cells factor in the spectral sensitivity of a visual system is essential to explain how they contribute to the visual ecology of the animal in question. Existing methods that model the absorption of visual pigments use templates which correspond closely to data from thin cross-sections of photoreceptor cells. However, few modeling approaches use a single framework to incorporate physical parameters of real photoreceptors, which can be fused, and can form vertical tiers. Akaike's information criterion (AIC c ) was used here to select absorptance models of multiple classes of photoreceptor cells that maximize information, given visual system spectral sensitivity data obtained using extracellular electroretinograms and structural parameters obtained by histological methods. This framework was first used to select among alternative hypotheses of photoreceptor number. It identified spectral classes from a range of dark-adapted visual systems which have between one and four spectral photoreceptor classes. These were the velvet worm, Principapillatus hitoyensis , the branchiopod water flea, Daphnia magna , normal humans, and humans with enhanced S-cone syndrome, a condition in which S-cone frequency is increased due to mutations in a transcription factor that controls photoreceptor expression. Data from the Asian swallowtail, Papilio xuthus , which has at least five main spectral photoreceptor classes in its compound eyes, were included to illustrate potential effects of model over-simplification on multi-model inference. The multi-model framework was then used with parameters of spectral photoreceptor classes and the structural photoreceptor array kept constant. The goal was to map relative opsin expression to visual pigment concentration. It identified relative opsin expression differences for two populations of the bluefin killifish, Lucania goodei . The modeling approach presented here will be useful in selecting the most likely alternative hypotheses of opsin-based spectral photoreceptor classes, using relative opsin expression and extracellular electroretinography.

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

An egalitarian network model for the emergence of simple and complex cells in visual cortex

PubMed Central

Tao, Louis; Shelley, Michael; McLaughlin, David; Shapley, Robert

2004-01-01

We explain how simple and complex cells arise in a large-scale neuronal network model of the primary visual cortex of the macaque. Our model consists of ≈4,000 integrate-and-fire, conductance-based point neurons, representing the cells in a small, 1-mm2 patch of an input layer of the primary visual cortex. In the model the local connections are isotropic and nonspecific, and convergent input from the lateral geniculate nucleus confers cortical cells with orientation and spatial phase preference. The balance between lateral connections and lateral geniculate nucleus drive determines whether individual neurons in this recurrent circuit are simple or complex. The model reproduces qualitatively the experimentally observed distributions of both extracellular and intracellular measures of simple and complex response. PMID:14695891

Improved CORF model of simple cell combined with non-classical receptive field and its application on edge detection

NASA Astrophysics Data System (ADS)

Sun, Xiao; Chai, Guobei; Liu, Wei; Bao, Wenzhuo; Zhao, Xiaoning; Ming, Delie

2018-02-01

Simple cells in primary visual cortex are believed to extract local edge information from a visual scene. In this paper, inspired by different receptive field properties and visual information flow paths of neurons, an improved Combination of Receptive Fields (CORF) model combined with non-classical receptive fields was proposed to simulate the responses of simple cell's receptive fields. Compared to the classical model, the proposed model is able to better imitate simple cell's physiologic structure with consideration of facilitation and suppression of non-classical receptive fields. And on this base, an edge detection algorithm as an application of the improved CORF model was proposed. Experimental results validate the robustness of the proposed algorithm to noise and background interference.

Modeling for Visual Feature Extraction Using Spiking Neural Networks

NASA Astrophysics Data System (ADS)

Kimura, Ichiro; Kuroe, Yasuaki; Kotera, Hiromichi; Murata, Tomoya

This paper develops models for “visual feature extraction” in biological systems by using “spiking neural network (SNN)”. The SNN is promising for developing the models because the information is encoded and processed by spike trains similar to biological neural networks. Two architectures of SNN are proposed for modeling the directionally selective and the motion parallax cell in neuro-sensory systems and they are trained so as to possess actual biological responses of each cell. To validate the developed models, their representation ability is investigated and their visual feature extraction mechanisms are discussed from the neurophysiological viewpoint. It is expected that this study can be the first step to developing a sensor system similar to the biological systems and also a complementary approach to investigating the function of the brain.

Analysis, simulation and visualization of 1D tapping via reduced dynamical models

NASA Astrophysics Data System (ADS)

Blackmore, Denis; Rosato, Anthony; Tricoche, Xavier; Urban, Kevin; Zou, Luo

2014-04-01

A low-dimensional center-of-mass dynamical model is devised as a simplified means of approximately predicting some important aspects of the motion of a vertical column comprised of a large number of particles subjected to gravity and periodic vertical tapping. This model is investigated first as a continuous dynamical system using analytical, simulation and visualization techniques. Then, by employing an approach analogous to that used to approximate the dynamics of a bouncing ball on an oscillating flat plate, it is modeled as a discrete dynamical system and analyzed to determine bifurcations and transitions to chaotic motion along with other properties. The predictions of the analysis are then compared-primarily qualitatively-with visualization and simulation results of the reduced continuous model, and ultimately with simulations of the complete system dynamics.

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.

Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation

PubMed Central

Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina

2017-01-01

Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this “online” multisensory improvement, there is evidence of long-lasting, “offline” effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced “online” effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations. PMID:29326578

Audiovisual Rehabilitation in Hemianopia: A Model-Based Theoretical Investigation.

PubMed

Magosso, Elisa; Cuppini, Cristiano; Bertini, Caterina

2017-01-01

Hemianopic patients exhibit visual detection improvement in the blind field when audiovisual stimuli are given in spatiotemporally coincidence. Beyond this "online" multisensory improvement, there is evidence of long-lasting, "offline" effects induced by audiovisual training: patients show improved visual detection and orientation after they were trained to detect and saccade toward visual targets given in spatiotemporal proximity with auditory stimuli. These effects are ascribed to the Superior Colliculus (SC), which is spared in these patients and plays a pivotal role in audiovisual integration and oculomotor behavior. Recently, we developed a neural network model of audiovisual cortico-collicular loops, including interconnected areas representing the retina, striate and extrastriate visual cortices, auditory cortex, and SC. The network simulated unilateral V1 lesion with possible spared tissue and reproduced "online" effects. Here, we extend the previous network to shed light on circuits, plastic mechanisms, and synaptic reorganization that can mediate the training effects and functionally implement visual rehabilitation. The network is enriched by the oculomotor SC-brainstem route, and Hebbian mechanisms of synaptic plasticity, and is used to test different training paradigms (audiovisual/visual stimulation in eye-movements/fixed-eyes condition) on simulated patients. Results predict different training effects and associate them to synaptic changes in specific circuits. Thanks to the SC multisensory enhancement, the audiovisual training is able to effectively strengthen the retina-SC route, which in turn can foster reinforcement of the SC-brainstem route (this occurs only in eye-movements condition) and reinforcement of the SC-extrastriate route (this occurs in presence of survived V1 tissue, regardless of eye condition). The retina-SC-brainstem circuit may mediate compensatory effects: the model assumes that reinforcement of this circuit can translate visual stimuli into short-latency saccades, possibly moving the stimuli into visual detection regions. The retina-SC-extrastriate circuit is related to restitutive effects: visual stimuli can directly elicit visual detection with no need for eye movements. Model predictions and assumptions are critically discussed in view of existing behavioral and neurophysiological data, forecasting that other oculomotor compensatory mechanisms, beyond short-latency saccades, are likely involved, and stimulating future experimental and theoretical investigations.

D Modelling and Visualization Based on the Unity Game Engine - Advantages and Challenges

NASA Astrophysics Data System (ADS)

Buyuksalih, I.; Bayburt, S.; Buyuksalih, G.; Baskaraca, A. P.; Karim, H.; Rahman, A. A.

2017-11-01

3D City modelling is increasingly popular and becoming valuable tools in managing big cities. Urban and energy planning, landscape, noise-sewage modelling, underground mapping and navigation are among the applications/fields which really depend on 3D modelling for their effectiveness operations. Several research areas and implementation projects had been carried out to provide the most reliable 3D data format for sharing and functionalities as well as visualization platform and analysis. For instance, BIMTAS company has recently completed a project to estimate potential solar energy on 3D buildings for the whole Istanbul and now focussing on 3D utility underground mapping for a pilot case study. The research and implementation standard on 3D City Model domain (3D data sharing and visualization schema) is based on CityGML schema version 2.0. However, there are some limitations and issues in implementation phase for large dataset. Most of the limitations were due to the visualization, database integration and analysis platform (Unity3D game engine) as highlighted in this paper.

Intuitive presentation of clinical forensic data using anonymous and person-specific 3D reference manikins.

PubMed

Urschler, Martin; Höller, Johannes; Bornik, Alexander; Paul, Tobias; Giretzlehner, Michael; Bischof, Horst; Yen, Kathrin; Scheurer, Eva

2014-08-01

The increasing use of CT/MR devices in forensic analysis motivates the need to present forensic findings from different sources in an intuitive reference visualization, with the aim of combining 3D volumetric images along with digital photographs of external findings into a 3D computer graphics model. This model allows a comprehensive presentation of forensic findings in court and enables comparative evaluation studies correlating data sources. The goal of this work was to investigate different methods to generate anonymous and patient-specific 3D models which may be used as reference visualizations. The issue of registering 3D volumetric as well as 2D photographic data to such 3D models is addressed to provide an intuitive context for injury documentation from arbitrary modalities. We present an image processing and visualization work-flow, discuss the major parts of this work-flow, compare the different investigated reference models, and show a number of cases studies that underline the suitability of the proposed work-flow for presenting forensically relevant information in 3D visualizations. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

Developing Local Scale, High Resolution, Data to Interface with Numerical Hurricane Models

NASA Astrophysics Data System (ADS)

Witkop, R.; Becker, A.

2017-12-01

In 2017, the University of Rhode Island's (URI's) Graduate School of Oceanography (GSO) developed hurricane models that specify wind speed, inundation, and erosion around Rhode Island with enough precision to incorporate impacts on individual facilities. At the same time, URI's Marine Affairs Visualization Lab (MAVL) developed a way to realistically visualize these impacts in 3-D. Since climate change visualizations and water resource simulations have been shown to promote resiliency action (Sheppard, 2015) and increase credibility (White et al., 2010) when local knowledge is incorporated, URI's hurricane models and visualizations may also more effectively enable hurricane resilience actions if they include Facility Manager (FM) and Emergency Manager (EM) perceived hurricane impacts. This study determines how FM's and EM's perceive their assets as being vulnerable to quantifiable hurricane-related forces at the individual facility scale while exploring methods to elicit this information from FMs and EMs in a format usable for incorporation into URI GSO's hurricane models.

Large-scale functional models of visual cortex for remote sensing

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

Brumby, Steven P; Kenyon, Garrett; Rasmussen, Craig E

Neuroscience has revealed many properties of neurons and of the functional organization of visual cortex that are believed to be essential to human vision, but are missing in standard artificial neural networks. Equally important may be the sheer scale of visual cortex requiring {approx}1 petaflop of computation. In a year, the retina delivers {approx}1 petapixel to the brain, leading to massively large opportunities for learning at many levels of the cortical system. We describe work at Los Alamos National Laboratory (LANL) to develop large-scale functional models of visual cortex on LANL's Roadrunner petaflop supercomputer. An initial run of a simplemore » region VI code achieved 1.144 petaflops during trials at the IBM facility in Poughkeepsie, NY (June 2008). Here, we present criteria for assessing when a set of learned local representations is 'complete' along with general criteria for assessing computer vision models based on their projected scaling behavior. Finally, we extend one class of biologically-inspired learning models to problems of remote sensing imagery.« less

Visual crowding illustrates the inadequacy of local vs. global and feedforward vs. feedback distinctions in modeling visual perception

PubMed Central

Clarke, Aaron M.; Herzog, Michael H.; Francis, Gregory

2014-01-01

Experimentalists tend to classify models of visual perception as being either local or global, and involving either feedforward or feedback processing. We argue that these distinctions are not as helpful as they might appear, and we illustrate these issues by analyzing models of visual crowding as an example. Recent studies have argued that crowding cannot be explained by purely local processing, but that instead, global factors such as perceptual grouping are crucial. Theories of perceptual grouping, in turn, often invoke feedback connections as a way to account for their global properties. We examined three types of crowding models that are representative of global processing models, and two of which employ feedback processing: a model based on Fourier filtering, a feedback neural network, and a specific feedback neural architecture that explicitly models perceptual grouping. Simulations demonstrate that crucial empirical findings are not accounted for by any of the models. We conclude that empirical investigations that reject a local or feedforward architecture offer almost no constraints for model construction, as there are an uncountable number of global and feedback systems. We propose that the identification of a system as being local or global and feedforward or feedback is less important than the identification of a system's computational details. Only the latter information can provide constraints on model development and promote quantitative explanations of complex phenomena. PMID:25374554

How to Make a Good Animation: A Grounded Cognition Model of How Visual Representation Design Affects the Construction of Abstract Physics Knowledge

ERIC Educational Resources Information Center

Chen, Zhongzhou; Gladding, Gary

2014-01-01

Visual representations play a critical role in teaching physics. However, since we do not have a satisfactory understanding of how visual perception impacts the construction of abstract knowledge, most visual representations used in instructions are either created based on existing conventions or designed according to the instructor's intuition,…

Asymmetrical Interhemispheric Connections Develop in Cat Visual Cortex after Early Unilateral Convergent Strabismus: Anatomy, Physiology, and Mechanisms

PubMed Central

Bui Quoc, Emmanuel; Ribot, Jérôme; Quenech’Du, Nicole; Doutremer, Suzette; Lebas, Nicolas; Grantyn, Alexej; Aushana, Yonane; Milleret, Chantal

2011-01-01

In the mammalian primary visual cortex, the corpus callosum contributes to the unification of the visual hemifields that project to the two hemispheres. Its development depends on visual experience. When this is abnormal, callosal connections must undergo dramatic anatomical and physiological changes. However, data concerning these changes are sparse and incomplete. Thus, little is known about the impact of abnormal postnatal visual experience on the development of callosal connections and their role in unifying representation of the two hemifields. Here, the effects of early unilateral convergent strabismus (a model of abnormal visual experience) were fully characterized with respect to the development of the callosal connections in cat visual cortex, an experimental model for humans. Electrophysiological responses and 3D reconstruction of single callosal axons show that abnormally asymmetrical callosal connections develop after unilateral convergent strabismus, resulting from an extension of axonal branches of specific orders in the hemisphere ipsilateral to the deviated eye and a decreased number of nodes and terminals in the other (ipsilateral to the non-deviated eye). Furthermore this asymmetrical organization prevents the establishment of a unifying representation of the two visual hemifields. As a general rule, we suggest that crossed and uncrossed retino-geniculo-cortical pathways contribute successively to the development of the callosal maps in visual cortex. PMID:22275883

A foreground object features-based stereoscopic image visual comfort assessment model

NASA Astrophysics Data System (ADS)

Jin, Xin; Jiang, G.; Ying, H.; Yu, M.; Ding, S.; Peng, Z.; Shao, F.

2014-11-01

Since stereoscopic images provide observers with both realistic and discomfort viewing experience, it is necessary to investigate the determinants of visual discomfort. By considering that foreground object draws most attention when human observing stereoscopic images. This paper proposes a new foreground object based visual comfort assessment (VCA) metric. In the first place, a suitable segmentation method is applied to disparity map and then the foreground object is ascertained as the one having the biggest average disparity. In the second place, three visual features being average disparity, average width and spatial complexity of foreground object are computed from the perspective of visual attention. Nevertheless, object's width and complexity do not consistently influence the perception of visual comfort in comparison with disparity. In accordance with this psychological phenomenon, we divide the whole images into four categories on the basis of different disparity and width, and exert four different models to more precisely predict its visual comfort in the third place. Experimental results show that the proposed VCA metric outperformance other existing metrics and can achieve a high consistency between objective and subjective visual comfort scores. The Pearson Linear Correlation Coefficient (PLCC) and Spearman Rank Order Correlation Coefficient (SROCC) are over 0.84 and 0.82, respectively.

Visual cognition

PubMed Central

Cavanagh, Patrick

2011-01-01

Visual cognition, high-level vision, mid-level vision and top-down processing all refer to decision-based scene analyses that combine prior knowledge with retinal input to generate representations. The label “visual cognition” is little used at present, but research and experiments on mid- and high-level, inference-based vision have flourished, becoming in the 21st century a significant, if often understated part, of current vision research. How does visual cognition work? What are its moving parts? This paper reviews the origins and architecture of visual cognition and briefly describes some work in the areas of routines, attention, surfaces, objects, and events (motion, causality, and agency). Most vision scientists avoid being too explicit when presenting concepts about visual cognition, having learned that explicit models invite easy criticism. What we see in the literature is ample evidence for visual cognition, but few or only cautious attempts to detail how it might work. This is the great unfinished business of vision research: at some point we will be done with characterizing how the visual system measures the world and we will have to return to the question of how vision constructs models of objects, surfaces, scenes, and events. PMID:21329719

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.

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.

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 Scientific Visualization with Blender

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2015-03-01

This is the first book written on using Blender (an open source visualization suite widely used in the entertainment and gaming industries) for scientific visualization. It is a practical and interesting introduction to Blender for understanding key parts of 3D rendering and animation that pertain to the sciences via step-by-step guided tutorials. 3D Scientific Visualization with Blender takes you through an understanding of 3D graphics and modelling for different visualization scenarios in the physical sciences.

Supplementation with macular carotenoids improves visual performance of transgenic mice.

PubMed

Li, Binxing; Rognon, Gregory T; Mattinson, Ty; Vachali, Preejith P; Gorusupudi, Aruna; Chang, Fu-Yen; Ranganathan, Arunkumar; Nelson, Kelly; George, Evan W; Frederick, Jeanne M; Bernstein, Paul S

2018-07-01

Carotenoid supplementation can improve human visual performance, but there is still no validated rodent model to test their effects on visual function in laboratory animals. We recently showed that mice deficient in β-carotene oxygenase 2 (BCO2) and/or β-carotene oxygenase 1 (BCO1) enzymes can accumulate carotenoids in their retinas, allowing us to investigate the effects of carotenoids on the visual performance of mice. Using OptoMotry, a device to measure visual function in rodents, we examined the effect of zeaxanthin, lutein, and β-carotene on visual performance of various BCO knockout mice. We then transgenically expressed the human zeaxanthin-binding protein GSTP1 (hGSTP1) in the rods of bco2 -/- mice to examine if delivering more zeaxanthin to retina will improve their visual function further. The visual performance of bco2 -/- mice fed with zeaxanthin or lutein was significantly improved relative to control mice fed with placebo beadlets. β-Carotene had no significant effect in bco2 -/- mice but modestly improved cone visual function of bco1 -/- mice. Expression of hGSTP1 in the rods of bco2 -/- mice resulted in a 40% increase of retinal zeaxanthin and further improvement of visual performance. This work demonstrates that these "macular pigment mice" may serve as animal models to study carotenoid function in the retina. Copyright © 2018 Elsevier Inc. All rights reserved.

Risk factors and visual fatigue of baggage X-ray security screeners: a structural equation modelling analysis.

PubMed

Yu, Rui-Feng; Yang, Lin-Dong; Wu, Xin

2017-05-01

This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue using structural equation modelling approach. Two hundred and five X-ray security screeners participated in a questionnaire survey. The result showed that satisfaction with the VDT's physical features and the work environment conditions were negatively correlated with the intensity of visual fatigue, whereas job stress and job burnout had direct positive influences. The path coefficient between the image quality of VDT and visual fatigue was not significant. The total effects of job burnout, job stress, the VDT's physical features and the work environment conditions on visual fatigue were 0.471, 0.469, -0.268 and -0.251 respectively. These findings indicated that both extrinsic factors relating to VDT and workplace environment and psychological factors including job burnout and job stress should be considered in the workplace design and work organisation of security screening tasks to reduce screeners' visual fatigue. Practitioner Summary: This study identified the risk factors influencing visual fatigue in baggage X-ray security screeners and estimated the strength of correlations between those factors and visual fatigue. The findings were of great importance to the workplace design and the work organisation of security screening tasks to reduce screeners' visual fatigue.

Spatial Visualization by Isometric View

ERIC Educational Resources Information Center

Yue, Jianping

2007-01-01

Spatial visualization is a fundamental skill in technical graphics and engineering designs. From conventional multiview drawing to modern solid modeling using computer-aided design, visualization skills have always been essential for representing three-dimensional objects and assemblies. Researchers have developed various types of tests to measure…

Investigation Of Integrating Three-Dimensional (3-D) Geometry Into The Visual Anatomical Injury Descriptor (Visual AID) Using WebGL

DTIC Science & Technology

2011-08-01

generated using the Zygote Human Anatomy 3-D model (3). Use of a reference anatomy independent of personal identification, such as Zygote, allows Visual...Zygote Human Anatomy 3D Model, 2010. http://www.zygote.com/ (accessed July 26, 2011). 4. Khronos Group Web site. Khronos to Create New Open Standard for...understanding of the information at hand. In order to fulfill the medical illustration track, I completed a concentration in science, focusing on human

Development of visual programming techniques to integrate theoretical modeling into the scientific planning and instrument operations environment of ISTP

NASA Technical Reports Server (NTRS)

Goodrich, Charles C.

1993-01-01

The goal of this project is to investigate the use of visualization software based on the visual programming and data-flow paradigms to meet the needs of the SPOF and through it the International Solar Terrestrial Physics (ISTP) science community. Specific needs we address include science planning, data interpretation, comparisons of data with simulation and model results, and data acquisition. Our accomplishments during the twelve month grant period are discussed below.

Learning Reverse Engineering and Simulation with Design Visualization

NASA Technical Reports Server (NTRS)

Hemsworth, Paul J.

2018-01-01

The Design Visualization (DV) group supports work at the Kennedy Space Center by utilizing metrology data with Computer-Aided Design (CAD) models and simulations to provide accurate visual representations that aid in decision-making. The capability to measure and simulate objects in real time helps to predict and avoid potential problems before they become expensive in addition to facilitating the planning of operations. I had the opportunity to work on existing and new models and simulations in support of DV and NASA’s Exploration Ground Systems (EGS).

Is nevtral NEUTRAL? Visual similarity effects in the early phases of written-word recognition.

PubMed

Marcet, Ana; Perea, Manuel

2017-08-01

For simplicity, contemporary models of written-word recognition and reading have unspecified feature/letter levels-they predict that the visually similar substituted-letter nonword PEQPLE is as effective at activating the word PEOPLE as the visually dissimilar substituted-letter nonword PEYPLE. Previous empirical evidence on the effects of visual similarly across letters during written-word recognition is scarce and nonconclusive. To examine whether visual similarity across letters plays a role early in word processing, we conducted two masked priming lexical decision experiments (stimulus-onset asynchrony = 50 ms). The substituted-letter primes were visually very similar to the target letters (u/v in Experiment 1 and i/j in Experiment 2; e.g., nevtral-NEUTRAL). For comparison purposes, we included an identity prime condition (neutral-NEUTRAL) and a dissimilar-letter prime condition (neztral-NEUTRAL). Results showed that the similar-letter prime condition produced faster word identification times than the dissimilar-letter prime condition. We discuss how models of written-word recognition should be amended to capture visual similarity effects across letters.

Perceptual learning in a non-human primate model of artificial vision

PubMed Central

Killian, Nathaniel J.; Vurro, Milena; Keith, Sarah B.; Kyada, Margee J.; Pezaris, John S.

2016-01-01

Visual perceptual grouping, the process of forming global percepts from discrete elements, is experience-dependent. Here we show that the learning time course in an animal model of artificial vision is predicted primarily from the density of visual elements. Three naïve adult non-human primates were tasked with recognizing the letters of the Roman alphabet presented at variable size and visualized through patterns of discrete visual elements, specifically, simulated phosphenes mimicking a thalamic visual prosthesis. The animals viewed a spatially static letter using a gaze-contingent pattern and then chose, by gaze fixation, between a matching letter and a non-matching distractor. Months of learning were required for the animals to recognize letters using simulated phosphene vision. Learning rates increased in proportion to the mean density of the phosphenes in each pattern. Furthermore, skill acquisition transferred from trained to untrained patterns, not depending on the precise retinal layout of the simulated phosphenes. Taken together, the findings suggest that learning of perceptual grouping in a gaze-contingent visual prosthesis can be described simply by the density of visual activation. PMID:27874058

Quantized visual awareness.

PubMed

Escobar, W A

2013-01-01

The proposed model holds that, at its most fundamental level, visual awareness is quantized. That is to say that visual awareness arises as individual bits of awareness through the action of neural circuits with hundreds to thousands of neurons in at least the human striate cortex. Circuits with specific topologies will reproducibly result in visual awareness that correspond to basic aspects of vision like color, motion, and depth. These quanta of awareness (qualia) are produced by the feedforward sweep that occurs through the geniculocortical pathway but are not integrated into a conscious experience until recurrent processing from centers like V4 or V5 select the appropriate qualia being produced in V1 to create a percept. The model proposed here has the potential to shift the focus of the search for visual awareness to the level of microcircuits and these likely exist across the kingdom Animalia. Thus establishing qualia as the fundamental nature of visual awareness will not only provide a deeper understanding of awareness, but also allow for a more quantitative understanding of the evolution of visual awareness throughout the animal kingdom.

Cognitive/emotional models for human behavior representation in 3D avatar simulations

NASA Astrophysics Data System (ADS)

Peterson, James K.

2004-08-01

Simplified models of human cognition and emotional response are presented which are based on models of auditory/ visual polymodal fusion. At the core of these models is a computational model of Area 37 of the temporal cortex which is based on new isocortex models presented recently by Grossberg. These models are trained using carefully chosen auditory (musical sequences), visual (paintings) and higher level abstract (meta level) data obtained from studies of how optimization strategies are chosen in response to outside managerial inputs. The software modules developed are then used as inputs to character generation codes in standard 3D virtual world simulations. The auditory and visual training data also enable the development of simple music and painting composition generators which significantly enhance one's ability to validate the cognitive model. The cognitive models are handled as interacting software agents implemented as CORBA objects to allow the use of multiple language coding choices (C++, Java, Python etc) and efficient use of legacy code.

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.

ACTIVIS: Visual Exploration of Industry-Scale Deep Neural Network Models.

PubMed

Kahng, Minsuk; Andrews, Pierre Y; Kalro, Aditya; Polo Chau, Duen Horng

2017-08-30

While deep learning models have achieved state-of-the-art accuracies for many prediction tasks, understanding these models remains a challenge. Despite the recent interest in developing visual tools to help users interpret deep learning models, the complexity and wide variety of models deployed in industry, and the large-scale datasets that they used, pose unique design challenges that are inadequately addressed by existing work. Through participatory design sessions with over 15 researchers and engineers at Facebook, we have developed, deployed, and iteratively improved ACTIVIS, an interactive visualization system for interpreting large-scale deep learning models and results. By tightly integrating multiple coordinated views, such as a computation graph overview of the model architecture, and a neuron activation view for pattern discovery and comparison, users can explore complex deep neural network models at both the instance- and subset-level. ACTIVIS has been deployed on Facebook's machine learning platform. We present case studies with Facebook researchers and engineers, and usage scenarios of how ACTIVIS may work with different models.

The utility of modeling word identification from visual input within models of eye movements in reading

PubMed Central

Bicknell, Klinton; Levy, Roger

2012-01-01

Decades of empirical work have shown that a range of eye movement phenomena in reading are sensitive to the details of the process of word identification. Despite this, major models of eye movement control in reading do not explicitly model word identification from visual input. This paper presents a argument for developing models of eye movements that do include detailed models of word identification. Specifically, we argue that insights into eye movement behavior can be gained by understanding which phenomena naturally arise from an account in which the eyes move for efficient word identification, and that one important use of such models is to test which eye movement phenomena can be understood this way. As an extended case study, we present evidence from an extension of a previous model of eye movement control in reading that does explicitly model word identification from visual input, Mr. Chips (Legge, Klitz, & Tjan, 1997), to test two proposals for the effect of using linguistic context on reading efficiency. PMID:23074362

Coastal Surveillance Baseline Model Development

DTIC Science & Technology

2015-02-27

In the current STK model, a set of areas was defined for two reasons: To provide visual assistance during ship and aircraft route planning; and To...RF), electro-optic (EO), infrared (IR), and visual Partially Met The free version of STK can only generate simple generic sensors RQ-04 The model...25 APPENDIX A PLATFORM OBJECT ROUTE PLANNING PROCEDURE ............. A-1 APPENDIX B STK INSTALLATION

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

Combining patient journey modelling and visual multi-agent computer simulation: a framework to improving knowledge translation in a healthcare environment.

PubMed

Curry, Joanne; Fitzgerald, Anneke; Prodan, Ante; Dadich, Ann; Sloan, Terry

2014-01-01

This article focuses on a framework that will investigate the integration of two disparate methodologies: patient journey modelling and visual multi-agent simulation, and its impact on the speed and quality of knowledge translation to healthcare stakeholders. Literature describes patient journey modelling and visual simulation as discrete activities. This paper suggests that their combination and their impact on translating knowledge to practitioners are greater than the sum of the two technologies. The test-bed is ambulatory care and the goal is to determine if this approach can improve health services delivery, workflow, and patient outcomes and satisfaction. The multidisciplinary research team is comprised of expertise in patient journey modelling, simulation, and knowledge translation.

Modeling global scene factors in attention

NASA Astrophysics Data System (ADS)

Torralba, Antonio

2003-07-01

Models of visual attention have focused predominantly on bottom-up approaches that ignored structured contextual and scene information. I propose a model of contextual cueing for attention guidance based on the global scene configuration. It is shown that the statistics of low-level features across the whole image can be used to prime the presence or absence of objects in the scene and to predict their location, scale, and appearance before exploring the image. In this scheme, visual context information can become available early in the visual processing chain, which allows modulation of the saliency of image regions and provides an efficient shortcut for object detection and recognition. 2003 Optical Society of America

A Bayesian model for visual space perception

NASA Technical Reports Server (NTRS)

Curry, R. E.

1972-01-01

A model for visual space perception is proposed that contains desirable features in the theories of Gibson and Brunswik. This model is a Bayesian processor of proximal stimuli which contains three important elements: an internal model of the Markov process describing the knowledge of the distal world, the a priori distribution of the state of the Markov process, and an internal model relating state to proximal stimuli. The universality of the model is discussed and it is compared with signal detection theory models. Experimental results of Kinchla are used as a special case.

[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.

You prime what you code: The fAIM model of priming of pop-out

PubMed Central

Meeter, Martijn

2017-01-01

Our visual brain makes use of recent experience to interact with the visual world, and efficiently select relevant information. This is exemplified by speeded search when target- and distractor features repeat across trials versus when they switch, a phenomenon referred to as intertrial priming. Here, we present fAIM, a computational model that demonstrates how priming can be explained by a simple feature-weighting mechanism integrated into an established model of bottom-up vision. In fAIM, such modulations in feature gains are widespread and not just restricted to one or a few features. Consequentially, priming effects result from the overall tuning of visual features to the task at hand. Such tuning allows the model to reproduce priming for different types of stimuli, including for typical stimulus dimensions such as ‘color’ and for less obvious dimensions such as ‘spikiness’ of shapes. Moreover, the model explains some puzzling findings from the literature: it shows how priming can be found for target-distractor stimulus relations rather than for their absolute stimulus values per se, without an explicit representation of relations. Similarly, it simulates effects that have been taken to reflect a modulation of priming by an observers’ goals—without any representation of goals in the model. We conclude that priming is best considered as a consequence of a general adaptation of the brain to visual input, and not as a peculiarity of visual search. PMID:29166386

The Diffusion Simulator - Teaching Geomorphic and Geologic Problems Visually.

ERIC Educational Resources Information Center

Gilbert, R.

1979-01-01

Describes a simple hydraulic simulator based on more complex models long used by engineers to develop approximate solutions. It allows students to visualize non-steady transfer, to apply a model to solve a problem, and to compare experimentally simulated information with calculated values. (Author/MA)

The Inversion of Sensory Processing by Feedback Pathways: A Model of Visual Cognitive Functions.

ERIC Educational Resources Information Center

Harth, E.; And Others

1987-01-01

Explains the hierarchic structure of the mammalian visual system. Proposes a model in which feedback pathways serve to modify sensory stimuli in ways that enhance and complete sensory input patterns. Investigates the functioning of the system through computer simulations. (ML)

Teaching Science through Pictorial Models during Read-Alouds

ERIC Educational Resources Information Center

Oliveira, Alandeom W.; Rivera, Seema; Glass, Rory; Mastroianni, Michael; Wizner, Francine; Amodeo, Vincent

2013-01-01

This study examines how three elementary teachers refer to pictorial models (photographs, drawings, and cartoons) during science read-alouds. While one teacher used realistic photographs for the purpose of visually verifying facts about crystals, another employed analytical diagrams as heuristic tools to help students visualize complex target…

Attention Gating in Short-Term Visual Memory.

ERIC Educational Resources Information Center

Reeves, Adam; Sperling, George

1986-01-01

An experiment is conducted showing that an attention shift to a stream of numerals presented in rapid serial visual presentation mode produces not a total loss, but a systematic distortion of order. An attention gating model (AGM) is developed from a more general attention model. (Author/LMO)

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

A computational model of visual marking using an inter-connected network of spiking neurons: the spiking search over time & space model (sSoTS).

PubMed

Mavritsaki, Eirini; Heinke, Dietmar; Humphreys, Glyn W; Deco, Gustavo

2006-01-01

In the real world, visual information is selected over time as well as space, when we prioritise new stimuli for attention. Watson and Humphreys [Watson, D., Humphreys, G.W., 1997. Visual marking: prioritizing selection for new objects by top-down attentional inhibition of old objects. Psychological Review 104, 90-122] presented evidence that new information in search tasks is prioritised by (amongst other processes) active ignoring of old items - a process they termed visual marking. In this paper we present, for the first time, an explicit computational model of visual marking using biologically plausible activation functions. The "spiking search over time and space" model (sSoTS) incorporates different synaptic components (NMDA, AMPA, GABA) and a frequency adaptation mechanism based on [Ca(2+)] sensitive K(+) current. This frequency adaptation current can act as a mechanism that suppresses the previously attended items. We show that, when coupled with a process of active inhibition applied to old items, frequency adaptation leads to old items being de-prioritised (and new items prioritised) across time in search. Furthermore, the time course of these processes mimics the time course of the preview effect in human search. The results indicate that the sSoTS model can provide a biologically plausible account of human search over time as well as space.

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.

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.

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

Explaining neural signals in human visual cortex with an associative learning model.

PubMed

Jiang, Jiefeng; Schmajuk, Nestor; Egner, Tobias

2012-08-01

"Predictive coding" models posit a key role for associative learning in visual cognition, viewing perceptual inference as a process of matching (learned) top-down predictions (or expectations) against bottom-up sensory evidence. At the neural level, these models propose that each region along the visual processing hierarchy entails one set of processing units encoding predictions of bottom-up input, and another set computing mismatches (prediction error or surprise) between predictions and evidence. This contrasts with traditional views of visual neurons operating purely as bottom-up feature detectors. In support of the predictive coding hypothesis, a recent human neuroimaging study (Egner, Monti, & Summerfield, 2010) showed that neural population responses to expected and unexpected face and house stimuli in the "fusiform face area" (FFA) could be well-described as a summation of hypothetical face-expectation and -surprise signals, but not by feature detector responses. Here, we used computer simulations to test whether these imaging data could be formally explained within the broader framework of a mathematical neural network model of associative learning (Schmajuk, Gray, & Lam, 1996). Results show that FFA responses could be fit very closely by model variables coding for conditional predictions (and their violations) of stimuli that unconditionally activate the FFA. These data document that neural population signals in the ventral visual stream that deviate from classic feature detection responses can formally be explained by associative prediction and surprise signals.

Representation of visual gravitational motion in the human vestibular cortex.

PubMed

Indovina, Iole; Maffei, Vincenzo; Bosco, Gianfranco; Zago, Myrka; Macaluso, Emiliano; Lacquaniti, Francesco

2005-04-15

How do we perceive the visual motion of objects that are accelerated by gravity? We propose that, because vision is poorly sensitive to accelerations, an internal model that calculates the effects of gravity is derived from graviceptive information, is stored in the vestibular cortex, and is activated by visual motion that appears to be coherent with natural gravity. The acceleration of visual targets was manipulated while brain activity was measured using functional magnetic resonance imaging. In agreement with the internal model hypothesis, we found that the vestibular network was selectively engaged when acceleration was consistent with natural gravity. These findings demonstrate that predictive mechanisms of physical laws of motion are represented in the human brain.

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.

Basic multisensory functions can be acquired after congenital visual pattern deprivation in humans.

PubMed

Putzar, Lisa; Gondan, Matthias; Röder, Brigitte

2012-01-01

People treated for bilateral congenital cataracts offer a model to study the influence of visual deprivation in early infancy on visual and multisensory development. We investigated cross-modal integration capabilities in cataract patients using a simple detection task that provided redundant information to two different senses. In both patients and controls, redundancy gains were consistent with coactivation models, indicating an integrated processing of modality-specific information. This finding is in contrast with recent studies showing impaired higher-level multisensory interactions in cataract patients. The present results suggest that basic cross-modal integrative processes for simple short stimuli do not depend on visual and/or crossmodal input since birth.

Verbal Modification via Visual Display

ERIC Educational Resources Information Center

Richmond, Edmun B.; Wallace-Childers, La Donna

1977-01-01

The inability of foreign language students to produce acceptable approximations of new vowel sounds initiated a study to devise a real-time visual display system whereby the students could match vowel production to a visual pedagogical model. The system used amateur radio equipment and a standard oscilloscope. (CHK)

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.

Building simple multiscale visualizations of outcrop geology using virtual reality modeling language (VRML)

NASA Astrophysics Data System (ADS)

Thurmond, John B.; Drzewiecki, Peter A.; Xu, Xueming

2005-08-01

Geological data collected from outcrop are inherently three-dimensional (3D) and span a variety of scales, from the megascopic to the microscopic. This presents challenges in both interpreting and communicating observations. The Virtual Reality Modeling Language provides an easy way for geoscientists to construct complex visualizations that can be viewed with free software. Field data in tabular form can be used to generate hierarchical multi-scale visualizations of outcrops, which can convey the complex relationships between a variety of data types simultaneously. An example from carbonate mud-mounds in southeastern New Mexico illustrates the embedding of three orders of magnitude of observation into a single visualization, for the purpose of interpreting depositional facies relationships in three dimensions. This type of raw data visualization can be built without software tools, yet is incredibly useful for interpreting and communicating data. Even simple visualizations can aid in the interpretation of complex 3D relationships that are frequently encountered in the geosciences.

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.

AstroBlend: An astrophysical visualization package for Blender

NASA Astrophysics Data System (ADS)

Naiman, J. P.

2016-04-01

The rapid growth in scale and complexity of both computational and observational astrophysics over the past decade necessitates efficient and intuitive methods for examining and visualizing large datasets. Here, I present AstroBlend, an open-source Python library for use within the three dimensional modeling software, Blender. While Blender has been a popular open-source software among animators and visual effects artists, in recent years it has also become a tool for visualizing astrophysical datasets. AstroBlend combines the three dimensional capabilities of Blender with the analysis tools of the widely used astrophysical toolset, yt, to afford both computational and observational astrophysicists the ability to simultaneously analyze their data and create informative and appealing visualizations. The introduction of this package includes a description of features, work flow, and various example visualizations. A website - www.astroblend.com - has been developed which includes tutorials, and a gallery of example images and movies, along with links to downloadable data, three dimensional artistic models, and various other resources.

Neuro-ophthalmic manifestations of cerebrovascular accidents.

PubMed

Ghannam, Alaa S Bou; Subramanian, Prem S

2017-11-01

Ocular functions can be affected in almost any type of cerebrovascular accident (CVA) creating a burden on the patient and family and limiting functionality. The present review summarizes the different ocular outcomes after stroke, divided into three categories: vision, ocular motility, and visual perception. We also discuss interventions that have been proposed to help restore vision and perception after CVA. Interventions that might help expand or compensate for visual field loss and visuospatial neglect include explorative saccade training, prisms, visual restoration therapy (VRT), and transcranial direct current stimulation (tDCS). VRT makes use of neuroplasticity, which has shown efficacy in animal models but remains controversial in human studies. CVAs can lead to decreased visual acuity, visual field loss, ocular motility abnormalities, and visuospatial perception deficits. Although ocular motility problems can be corrected with surgery, vision, and perception deficits are more difficult to overcome. Interventions to restore or compensate for visual field deficits are controversial despite theoretical underpinnings, animal model evidence, and case reports of their efficacies.

Getting signals into the brain: visual prosthetics through thalamic microstimulation.

PubMed

Pezaris, John S; Eskandar, Emad N

2009-07-01

Common causes of blindness are diseases that affect the ocular structures, such as glaucoma, retinitis pigmentosa, and macular degeneration, rendering the eyes no longer sensitive to light. The visual pathway, however, as a predominantly central structure, is largely spared in these cases. It is thus widely thought that a device-based prosthetic approach to restoration of visual function will be effective and will enjoy similar success as cochlear implants have for restoration of auditory function. In this article the authors review the potential locations for stimulation electrode placement for visual prostheses, assessing the anatomical and functional advantages and disadvantages of each. Of particular interest to the neurosurgical community is placement of deep brain stimulating electrodes in thalamic structures that has shown substantial promise in an animal model. The theory of operation of visual prostheses is discussed, along with a review of the current state of knowledge. Finally, the visual prosthesis is proposed as a model for a general high-fidelity machine-brain interface.

Stereoscopic applications for design visualization

NASA Astrophysics Data System (ADS)

Gilson, Kevin J.

2007-02-01

Advances in display technology and 3D design visualization applications have made real-time stereoscopic visualization of architectural and engineering projects a reality. Parsons Brinkerhoff (PB) is a transportation consulting firm that has used digital visualization tools from their inception and has helped pioneer the application of those tools to large scale infrastructure projects. PB is one of the first Architecture/Engineering/Construction (AEC) firms to implement a CAVE- an immersive presentation environment that includes stereoscopic rear-projection capability. The firm also employs a portable stereoscopic front-projection system, and shutter-glass systems for smaller groups. PB is using commercial real-time 3D applications in combination with traditional 3D modeling programs to visualize and present large AEC projects to planners, clients and decision makers in stereo. These presentations create more immersive and spatially realistic presentations of the proposed designs. This paper will present the basic display tools and applications, and the 3D modeling techniques PB is using to produce interactive stereoscopic content. The paper will discuss several architectural and engineering design visualizations we have produced.

Deep Residual Network Predicts Cortical Representation and Organization of Visual Features for Rapid Categorization.

PubMed

Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

2018-02-28

The brain represents visual objects with topographic cortical patterns. To address how distributed visual representations enable object categorization, we established predictive encoding models based on a deep residual network, and trained them to predict cortical responses to natural movies. Using this predictive model, we mapped human cortical representations to 64,000 visual objects from 80 categories with high throughput and accuracy. Such representations covered both the ventral and dorsal pathways, reflected multiple levels of object features, and preserved semantic relationships between categories. In the entire visual cortex, object representations were organized into three clusters of categories: biological objects, non-biological objects, and background scenes. In a finer scale specific to each cluster, object representations revealed sub-clusters for further categorization. Such hierarchical clustering of category representations was mostly contributed by cortical representations of object features from middle to high levels. In summary, this study demonstrates a useful computational strategy to characterize the cortical organization and representations of visual features for rapid categorization.

Electrooptical model of the first retina layers of a visual analyzer

NASA Technical Reports Server (NTRS)

Chibalashvili, Y. L.; Riabinin, A. D.; Svechnikov, S. V.; Chibalashvili, Y. L.; Shkvar, A. M.

1979-01-01

An electrooptical principle of converting and transmitting optical signals is proposed and used as the basis for constructing a model of the upper layers of the retina of the visual analyzer of animals. An evaluation of multichannel fibrous optical systems, in which the conversion of optical signals is based on the electrooptical principle, to model the upper retina layers is presented. The symbolic circuit of the model and its algorithm are discussed.

Measuring and modeling salience with the theory of visual attention.

PubMed

Krüger, Alexander; Tünnermann, Jan; Scharlau, Ingrid

2017-08-01

For almost three decades, the theory of visual attention (TVA) has been successful in mathematically describing and explaining a wide variety of phenomena in visual selection and recognition with high quantitative precision. Interestingly, the influence of feature contrast on attention has been included in TVA only recently, although it has been extensively studied outside the TVA framework. The present approach further develops this extension of TVA's scope by measuring and modeling salience. An empirical measure of salience is achieved by linking different (orientation and luminance) contrasts to a TVA parameter. In the modeling part, the function relating feature contrasts to salience is described mathematically and tested against alternatives by Bayesian model comparison. This model comparison reveals that the power function is an appropriate model of salience growth in the dimensions of orientation and luminance contrast. Furthermore, if contrasts from the two dimensions are combined, salience adds up additively.

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.

Considering the Spatial Layout Information of Bag of Features (BoF) Framework for Image Classification.

PubMed

Mu, Guangyu; Liu, Ying; Wang, Limin

2015-01-01

The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.

Cognitive search model and a new query paradigm

NASA Astrophysics Data System (ADS)

Xu, Zhonghui

2001-06-01

This paper proposes a cognitive model in which people begin to search pictures by using semantic content and find a right picture by judging whether its visual content is a proper visualization of the semantics desired. It is essential that human search is not just a process of matching computation on visual feature but rather a process of visualization of the semantic content known. For people to search electronic images in the way as they manually do in the model, we suggest that querying be a semantic-driven process like design. A query-by-design paradigm is prosed in the sense that what you design is what you find. Unlike query-by-example, query-by-design allows users to specify the semantic content through an iterative and incremental interaction process so that a retrieval can start with association and identification of the given semantic content and get refined while further visual cues are available. An experimental image retrieval system, Kuafu, has been under development using the query-by-design paradigm and an iconic language is adopted.

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.

Computer-aided light sheet flow visualization using photogrammetry

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1994-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and a visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) results, was chosen to interactively display the reconstructed light sheet images with the numerical surface geometry for the model or aircraft under study. The photogrammetric reconstruction technique and the image processing and computer graphics techniques and equipment are described. Results of the computer-aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images with CFD solutions in the same graphics environment is also demonstrated.

Computer-Aided Light Sheet Flow Visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

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

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).

Delta: a new web-based 3D genome visualization and analysis platform.

PubMed

Tang, Bixia; Li, Feifei; Li, Jing; Zhao, Wenming; Zhang, Zhihua

2018-04-15

Delta is an integrative visualization and analysis platform to facilitate visually annotating and exploring the 3D physical architecture of genomes. Delta takes Hi-C or ChIA-PET contact matrix as input and predicts the topologically associating domains and chromatin loops in the genome. It then generates a physical 3D model which represents the plausible consensus 3D structure of the genome. Delta features a highly interactive visualization tool which enhances the integration of genome topology/physical structure with extensive genome annotation by juxtaposing the 3D model with diverse genomic assay outputs. Finally, by visually comparing the 3D model of the β-globin gene locus and its annotation, we speculated a plausible transitory interaction pattern in the locus. Experimental evidence was found to support this speculation by literature survey. This served as an example of intuitive hypothesis testing with the help of Delta. Delta is freely accessible from http://delta.big.ac.cn, and the source code is available at https://github.com/zhangzhwlab/delta. zhangzhihua@big.ac.cn. Supplementary data are available at Bioinformatics online.

Computer-aided light sheet flow visualization

NASA Technical Reports Server (NTRS)

Stacy, Kathryn; Severance, Kurt; Childers, Brooks A.

1993-01-01

A computer-aided flow visualization process has been developed to analyze video images acquired from rotating and translating light sheet visualization systems. The computer process integrates a mathematical model for image reconstruction, advanced computer graphics concepts, and digital image processing to provide a quantitative and visual analysis capability. The image reconstruction model, based on photogrammetry, uses knowledge of the camera and light sheet locations and orientations to project two-dimensional light sheet video images into three-dimensional space. A sophisticated computer visualization package, commonly used to analyze computational fluid dynamics (CFD) data sets, was chosen to interactively display the reconstructed light sheet images, along with the numerical surface geometry for the model or aircraft under study. A description is provided of the photogrammetric reconstruction technique, and the image processing and computer graphics techniques and equipment. Results of the computer aided process applied to both a wind tunnel translating light sheet experiment and an in-flight rotating light sheet experiment are presented. The capability to compare reconstructed experimental light sheet images and CFD solutions in the same graphics environment is also demonstrated.

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.

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.

Modeling and visual simulation of Microalgae photobioreactor

NASA Astrophysics Data System (ADS)

Zhao, Ming; Hou, Dapeng; Hu, Dawei

Microalgae is a kind of nutritious and high photosynthetic efficiency autotrophic plant, which is widely distributed in the land and the sea. It can be extensively used in medicine, food, aerospace, biotechnology, environmental protection and other fields. Photobioreactor which is important equipment is mainly used to cultivate massive and high-density microalgae. In this paper, based on the mathematical model of microalgae which grew under different light intensity, three-dimensional visualization model was built and implemented in 3ds max, Virtools and some other three dimensional software. Microalgae is photosynthetic organism, it can efficiently produce oxygen and absorb carbon dioxide. The goal of the visual simulation is to display its change and impacting on oxygen and carbon dioxide intuitively. In this paper, different temperatures and light intensities were selected to control the photobioreactor, and dynamic change of microalgal biomass, Oxygen and carbon dioxide was observed with the aim of providing visualization support for microalgal and photobioreactor research.

Learning and disrupting invariance in visual recognition with a temporal association rule

PubMed Central

Isik, Leyla; Leibo, Joel Z.; Poggio, Tomaso

2012-01-01

Learning by temporal association rules such as Foldiak's trace rule is an attractive hypothesis that explains the development of invariance in visual recognition. Consistent with these rules, several recent experiments have shown that invariance can be broken at both the psychophysical and single cell levels. We show (1) that temporal association learning provides appropriate invariance in models of object recognition inspired by the visual cortex, (2) that we can replicate the “invariance disruption” experiments using these models with a temporal association learning rule to develop and maintain invariance, and (3) that despite dramatic single cell effects, a population of cells is very robust to these disruptions. We argue that these models account for the stability of perceptual invariance despite the underlying plasticity of the system, the variability of the visual world and expected noise in the biological mechanisms. PMID:22754523

Superior colliculus neurons encode a visual saliency map during free viewing of natural dynamic video

NASA Astrophysics Data System (ADS)

White, Brian J.; Berg, David J.; Kan, Janis Y.; Marino, Robert A.; Itti, Laurent; Munoz, Douglas P.

2017-01-01

Models of visual attention postulate the existence of a saliency map whose function is to guide attention and gaze to the most conspicuous regions in a visual scene. Although cortical representations of saliency have been reported, there is mounting evidence for a subcortical saliency mechanism, which pre-dates the evolution of neocortex. Here, we conduct a strong test of the saliency hypothesis by comparing the output of a well-established computational saliency model with the activation of neurons in the primate superior colliculus (SC), a midbrain structure associated with attention and gaze, while monkeys watched video of natural scenes. We find that the activity of SC superficial visual-layer neurons (SCs), specifically, is well-predicted by the model. This saliency representation is unlikely to be inherited from fronto-parietal cortices, which do not project to SCs, but may be computed in SCs and relayed to other areas via tectothalamic pathways.

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.

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

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

Khawli, Toufik Al; Eppelt, Urs; Hermanns, Torsten

2016-06-08

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part ismore » to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.« less

An integrated approach for the knowledge discovery in computer simulation models with a multi-dimensional parameter space

NASA Astrophysics Data System (ADS)

Khawli, Toufik Al; Gebhardt, Sascha; Eppelt, Urs; Hermanns, Torsten; Kuhlen, Torsten; Schulz, Wolfgang

2016-06-01

In production industries, parameter identification, sensitivity analysis and multi-dimensional visualization are vital steps in the planning process for achieving optimal designs and gaining valuable information. Sensitivity analysis and visualization can help in identifying the most-influential parameters and quantify their contribution to the model output, reduce the model complexity, and enhance the understanding of the model behavior. Typically, this requires a large number of simulations, which can be both very expensive and time consuming when the simulation models are numerically complex and the number of parameter inputs increases. There are three main constituent parts in this work. The first part is to substitute the numerical, physical model by an accurate surrogate model, the so-called metamodel. The second part includes a multi-dimensional visualization approach for the visual exploration of metamodels. In the third part, the metamodel is used to provide the two global sensitivity measures: i) the Elementary Effect for screening the parameters, and ii) the variance decomposition method for calculating the Sobol indices that quantify both the main and interaction effects. The application of the proposed approach is illustrated with an industrial application with the goal of optimizing a drilling process using a Gaussian laser beam.

COMICS: Cartoon Visualization of Omics Data in Spatial Context Using Anatomical Ontologies

PubMed Central

2017-01-01

COMICS is an interactive and open-access web platform for integration and visualization of molecular expression data in anatomograms of zebrafish, carp, and mouse model systems. Anatomical ontologies are used to map omics data across experiments and between an experiment and a particular visualization in a data-dependent manner. COMICS is built on top of several existing resources. Zebrafish and mouse anatomical ontologies with their controlled vocabulary (CV) and defined hierarchy are used with the ontoCAT R package to aggregate data for comparison and visualization. Libraries from the QGIS geographical information system are used with the R packages “maps” and “maptools” to visualize and interact with molecular expression data in anatomical drawings of the model systems. COMICS allows users to upload their own data from omics experiments, using any gene or protein nomenclature they wish, as long as CV terms are used to define anatomical regions or developmental stages. Common nomenclatures such as the ZFIN gene names and UniProt accessions are provided additional support. COMICS can be used to generate publication-quality visualizations of gene and protein expression across experiments. Unlike previous tools that have used anatomical ontologies to interpret imaging data in several animal models, including zebrafish, COMICS is designed to take spatially resolved data generated by dissection or fractionation and display this data in visually clear anatomical representations rather than large data tables. COMICS is optimized for ease-of-use, with a minimalistic web interface and automatic selection of the appropriate visual representation depending on the input data. PMID:29083911

COMICS: Cartoon Visualization of Omics Data in Spatial Context Using Anatomical Ontologies.

PubMed

Travin, Dmitrii; Popov, Iaroslav; Guler, Arzu Tugce; Medvedev, Dmitry; van der Plas-Duivesteijn, Suzanne; Varela, Monica; Kolder, Iris C R M; Meijer, Annemarie H; Spaink, Herman P; Palmblad, Magnus

2018-01-05

COMICS is an interactive and open-access web platform for integration and visualization of molecular expression data in anatomograms of zebrafish, carp, and mouse model systems. Anatomical ontologies are used to map omics data across experiments and between an experiment and a particular visualization in a data-dependent manner. COMICS is built on top of several existing resources. Zebrafish and mouse anatomical ontologies with their controlled vocabulary (CV) and defined hierarchy are used with the ontoCAT R package to aggregate data for comparison and visualization. Libraries from the QGIS geographical information system are used with the R packages "maps" and "maptools" to visualize and interact with molecular expression data in anatomical drawings of the model systems. COMICS allows users to upload their own data from omics experiments, using any gene or protein nomenclature they wish, as long as CV terms are used to define anatomical regions or developmental stages. Common nomenclatures such as the ZFIN gene names and UniProt accessions are provided additional support. COMICS can be used to generate publication-quality visualizations of gene and protein expression across experiments. Unlike previous tools that have used anatomical ontologies to interpret imaging data in several animal models, including zebrafish, COMICS is designed to take spatially resolved data generated by dissection or fractionation and display this data in visually clear anatomical representations rather than large data tables. COMICS is optimized for ease-of-use, with a minimalistic web interface and automatic selection of the appropriate visual representation depending on the input data.

Visualizing water

NASA Astrophysics Data System (ADS)

Baart, F.; van Gils, A.; Hagenaars, G.; Donchyts, G.; Eisemann, E.; van Velzen, J. W.

2016-12-01

A compelling visualization is captivating, beautiful and narrative. Here we show how melding the skills of computer graphics, art, statistics, and environmental modeling can be used to generate innovative, attractive and very informative visualizations. We focus on the topic of visualizing forecasts and measurements of water (water level, waves, currents, density, and salinity). For the field of computer graphics and arts, water is an important topic because it occurs in many natural scenes. For environmental modeling and statistics, water is an important topic because the water is essential for transport, a healthy environment, fruitful agriculture, and a safe environment.The different disciplines take different approaches to visualizing water. In computer graphics, one focusses on creating water as realistic looking as possible. The focus on realistic perception (versus the focus on the physical balance pursued by environmental scientists) resulted in fascinating renderings, as seen in recent games and movies. Visualization techniques for statistical results have benefited from the advancement in design and journalism, resulting in enthralling infographics. The field of environmental modeling has absorbed advances in contemporary cartography as seen in the latest interactive data-driven maps. We systematically review the design emerging types of water visualizations. The examples that we analyze range from dynamically animated forecasts, interactive paintings, infographics, modern cartography to web-based photorealistic rendering. By characterizing the intended audience, the design choices, the scales (e.g. time, space), and the explorability we provide a set of guidelines and genres. The unique contributions of the different fields show how the innovations in the current state of the art of water visualization have benefited from inter-disciplinary collaborations.

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

A visual-environment simulator with variable contrast

NASA Astrophysics Data System (ADS)

Gusarova, N. F.; Demin, A. V.; Polshchikov, G. V.

1987-01-01

A visual-environment simulator is proposed in which the image contrast can be varied continuously up to the reversal of the image. Contrast variability can be achieved by using two independently adjustable light sources to simultaneously illuminate the carrier of visual information (e.g., a slide or a cinematographic film). It is shown that such a scheme makes it possible to adequately model a complex visual environment.

3D Scientific Visualization with Blender

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2015-03-01

This is the first book written on using Blender for scientific visualization. It is a practical and interesting introduction to Blender for understanding key parts of 3D rendering and animation that pertain to the sciences via step-by-step guided tutorials. 3D Scientific Visualization with Blender takes you through an understanding of 3D graphics and modelling for different visualization scenarios in the physical sciences.

Visual Modelling of Data Warehousing Flows with UML Profiles

NASA Astrophysics Data System (ADS)

Pardillo, Jesús; Golfarelli, Matteo; Rizzi, Stefano; Trujillo, Juan

Data warehousing involves complex processes that transform source data through several stages to deliver suitable information ready to be analysed. Though many techniques for visual modelling of data warehouses from the static point of view have been devised, only few attempts have been made to model the data flows involved in a data warehousing process. Besides, each attempt was mainly aimed at a specific application, such as ETL, OLAP, what-if analysis, data mining. Data flows are typically very complex in this domain; for this reason, we argue, designers would greatly benefit from a technique for uniformly modelling data warehousing flows for all applications. In this paper, we propose an integrated visual modelling technique for data cubes and data flows. This technique is based on UML profiling; its feasibility is evaluated by means of a prototype implementation.

Visual recovery in cortical blindness is limited by high internal noise

PubMed Central

Cavanaugh, Matthew R.; Zhang, Ruyuan; Melnick, Michael D.; Das, Anasuya; Roberts, Mariel; Tadin, Duje; Carrasco, Marisa; Huxlin, Krystel R.

2015-01-01

Damage to the primary visual cortex typically causes cortical blindness (CB) in the hemifield contralateral to the damaged hemisphere. Recent evidence indicates that visual training can partially reverse CB at trained locations. Whereas training induces near-complete recovery of coarse direction and orientation discriminations, deficits in fine motion processing remain. Here, we systematically disentangle components of the perceptual inefficiencies present in CB fields before and after coarse direction discrimination training. In seven human CB subjects, we measured threshold versus noise functions before and after coarse direction discrimination training in the blind field and at corresponding intact field locations. Threshold versus noise functions were analyzed within the framework of the linear amplifier model and the perceptual template model. Linear amplifier model analysis identified internal noise as a key factor differentiating motion processing across the tested areas, with visual training reducing internal noise in the blind field. Differences in internal noise also explained residual perceptual deficits at retrained locations. These findings were confirmed with perceptual template model analysis, which further revealed that the major residual deficits between retrained and intact field locations could be explained by differences in internal additive noise. There were no significant differences in multiplicative noise or the ability to process external noise. Together, these results highlight the critical role of altered internal noise processing in mediating training-induced visual recovery in CB fields, and may explain residual perceptual deficits relative to intact regions of the visual field. PMID:26389544

Focal damage to macaque photoreceptors produces persistent visual loss

PubMed Central

Strazzeri, Jennifer M.; Hunter, Jennifer J.; Masella, Benjamin D.; Yin, Lu; Fischer, William S.; DiLoreto, David A.; Libby, Richard T.; Williams, David R.; Merigan, William H.

2014-01-01

Insertion of light-gated channels into inner retina neurons restores neural light responses, light evoked potentials, visual optomotor responses and visually-guided maze behavior in mice blinded by retinal degeneration. This method of vision restoration bypasses damaged outer retina, providing stimulation directly to retinal ganglion cells in inner retina. The approach is similar to that of electronic visual protheses, but may offer some advantages, such as avoidance of complex surgery and direct targeting of many thousands of neurons. However, the promise of this technique for restoring human vision remains uncertain because rodent animal models, in which it has been largely developed, are not ideal for evaluating visual perception. On the other hand, psychophysical vision studies in macaque can be used to evaluate different approaches to vision restoration in humans. Furthermore, it has not been possible to test vision restoration in macaques, the optimal model for human-like vision, because there has been no macaque model of outer retina degeneration. In this study, we describe development of a macaque model of photoreceptor degeneration that can in future studies be used to test restoration of perception by visual prostheses. Our results show that perceptual deficits caused by focal light damage are restricted to locations at which photoreceptors are damaged, that optical coherence tomography (OCT) can be used to track such lesions, and that adaptive optics retinal imaging, which we recently used for in vivo recording of ganglion cell function, can be used in future studies to examine these lesions. PMID:24316158

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

Interactive Visual Analysis within Dynamic Ocean Models

NASA Astrophysics Data System (ADS)

Butkiewicz, T.

2012-12-01

The many observation and simulation based ocean models available today can provide crucial insights for all fields of marine research and can serve as valuable references when planning data collection missions. However, the increasing size and complexity of these models makes leveraging their contents difficult for end users. Through a combination of data visualization techniques, interactive analysis tools, and new hardware technologies, the data within these models can be made more accessible to domain scientists. We present an interactive system that supports exploratory visual analysis within large-scale ocean flow models. The currents and eddies within the models are illustrated using effective, particle-based flow visualization techniques. Stereoscopic displays and rendering methods are employed to ensure that the user can correctly perceive the complex 3D structures of depth-dependent flow patterns. Interactive analysis tools are provided which allow the user to experiment through the introduction of their customizable virtual dye particles into the models to explore regions of interest. A multi-touch interface provides natural, efficient interaction, with custom multi-touch gestures simplifying the otherwise challenging tasks of navigating and positioning tools within a 3D environment. We demonstrate the potential applications of our visual analysis environment with two examples of real-world significance: Firstly, an example of using customized particles with physics-based behaviors to simulate pollutant release scenarios, including predicting the oil plume path for the 2010 Deepwater Horizon oil spill disaster. Secondly, an interactive tool for plotting and revising proposed autonomous underwater vehicle mission pathlines with respect to the surrounding flow patterns predicted by the model; as these survey vessels have extremely limited energy budgets, designing more efficient paths allows for greater survey areas.

Students' Different Understandings of Class Diagrams

ERIC Educational Resources Information Center

Boustedt, Jonas

2012-01-01

The software industry needs well-trained software designers and one important aspect of software design is the ability to model software designs visually and understand what visual models represent. However, previous research indicates that software design is a difficult task to many students. This article reports empirical findings from a…

Do Knowledge-Component Models Need to Incorporate Representational Competencies?

ERIC Educational Resources Information Center

Rau, Martina Angela

2017-01-01

Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…

Improving Image Segmentation with Adaptive, Recurrent, Spiking Neural Network Models of the Primary Visual Cortex

DTIC Science & Technology

2017-05-19

Vijay Singh, Martin Tchernookov, Rebecca Butterfield, Ilya Nemenman, Rongrong Ji. Director Field Model of the Primary Visual Cortex for Contour...FTE Equivalent: Total Number: DISCIPLINE Vijay Singh 40 Physics 0.40 1 PERCENT_SUPPORTEDNAME FTE Equivalent: Total Number: Martin Tchernookov 0.20

Numerical modeling of eastern connecticut's visual resources

Treesearch

Daniel L. Civco

1979-01-01

A numerical model capable of accurately predicting the preference for landscape photographs of selected points in eastern Connecticut is presented. A function of the social attitudes expressed toward thirty-two salient visual landscape features serves as the independent variable in predicting preferences. A technique for objectively assigning adjectives to landscape...

Quantification of visual clutter using a computation model of human perception : an application for head-up displays

DOT National Transportation Integrated Search

2004-03-20

A means of quantifying the cluttering effects of symbols is needed to evaluate the impact of displaying an increasing volume of information on aviation displays such as head-up displays. Human visual perception has been successfully modeled by algori...

Artist-Teachers' In-Action Mental Models While Teaching Visual Arts

ERIC Educational Resources Information Center

Russo-Zimet, Gila

2017-01-01

Studies have examined the assumption that teachers have previous perceptions, beliefs and knowledge about learning (Cochran-Smith & Villegas, 2015). This study presented the In-Action Mental Model of twenty leading artist-teachers while teaching Visual Arts in three Israeli art institutions of higher Education. Data was collected in two…

Virtual Manipulatives: Tools for Teaching Mathematics to Students with Learning Disabilities

ERIC Educational Resources Information Center

Shin, Mikyung; Bryant, Diane P.; Bryant, Brian R.; McKenna, John W.; Hou, Fangjuan; Ok, Min Wook

2017-01-01

Many students with learning disabilities demonstrate difficulty in developing a conceptual understanding of mathematical topics. Researchers recommend using visual models to support student learning of the concepts and skills necessary to complete abstract and symbolic mathematical problems. Virtual manipulatives (i.e., interactive visual models)…

Facilitative Orthographic Neighborhood Effects: The SERIOL Model Account

ERIC Educational Resources Information Center

Whitney, Carol; Lavidor, Michal

2005-01-01

A large orthographic neighborhood (N) facilitates lexical decision for central and left visual field/right hemisphere (LVF/RH) presentation, but not for right visual field/left hemisphere (RVF/LH) presentation. Based on the SERIOL model of letter-position encoding, this asymmetric N effect is explained by differential activation patterns at the…

Investigating Complexity Using Excel and Visual Basic.

ERIC Educational Resources Information Center

Zetie, K. P.

2001-01-01

Shows how some of the simple ideas in complexity can be investigated using a spreadsheet and a macro written in Visual Basic. Shows how the sandpile model of Bak, Chao, and Wiesenfeld can be simulated and animated. The model produces results that cannot easily be predicted from its properties. (Author/MM)

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

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.

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 framework for breast cancer visualization using augmented reality x-ray vision technique in mobile technology

NASA Astrophysics Data System (ADS)

Rahman, Hameedur; Arshad, Haslina; Mahmud, Rozi; Mahayuddin, Zainal Rasyid

2017-10-01

Breast Cancer patients who require breast biopsy has increased over the past years. Augmented Reality guided core biopsy of breast has become the method of choice for researchers. However, this cancer visualization has limitations to the extent of superimposing the 3D imaging data only. In this paper, we are introducing an Augmented Reality visualization framework that enables breast cancer biopsy image guidance by using X-Ray vision technique on a mobile display. This framework consists of 4 phases where it initially acquires the image from CT/MRI and process the medical images into 3D slices, secondly it will purify these 3D grayscale slices into 3D breast tumor model using 3D modeling reconstruction technique. Further, in visualization processing this virtual 3D breast tumor model has been enhanced using X-ray vision technique to see through the skin of the phantom and the final composition of it is displayed on handheld device to optimize the accuracy of the visualization in six degree of freedom. The framework is perceived as an improved visualization experience because the Augmented Reality x-ray vision allowed direct understanding of the breast tumor beyond the visible surface and direct guidance towards accurate biopsy targets.

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

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.

A workflow for the 3D visualization of meteorological data

NASA Astrophysics Data System (ADS)

Helbig, Carolin; Rink, Karsten

2014-05-01

In the future, climate change will strongly influence our environment and living conditions. To predict possible changes, climate models that include basic and process conditions have been developed and big data sets are produced as a result of simulations. The combination of various variables of climate models with spatial data from different sources helps to identify correlations and to study key processes. For our case study we use results of the weather research and forecasting (WRF) model of two regions at different scales that include various landscapes in Northern Central Europe and Baden-Württemberg. We visualize these simulation results in combination with observation data and geographic data, such as river networks, to evaluate processes and analyze if the model represents the atmospheric system sufficiently. For this purpose, a continuous workflow that leads from the integration of heterogeneous raw data to visualization using open source software (e.g. OpenGeoSys Data Explorer, ParaView) is developed. These visualizations can be displayed on a desktop computer or in an interactive virtual reality environment. We established a concept that includes recommended 3D representations and a color scheme for the variables of the data based on existing guidelines and established traditions in the specific domain. To examine changes over time in observation and simulation data, we added the temporal dimension to the visualization. In a first step of the analysis, the visualizations are used to get an overview of the data and detect areas of interest such as regions of convection or wind turbulences. Then, subsets of data sets are extracted and the included variables can be examined in detail. An evaluation by experts from the domains of visualization and atmospheric sciences establish if they are self-explanatory and clearly arranged. These easy-to-understand visualizations of complex data sets are the basis for scientific communication. In addition, they have become an essential medium for the evaluation and verification of models. Particularly in interdisciplinary research projects, they support the scientists in discussions and help to set a general level of knowledge.

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.

The Rising Landscape: A Visual Exploration of Superstring Revolutions in Physics.

ERIC Educational Resources Information Center

Chen, Chaomei; Kuljis, Jasna

2003-01-01

Discussion of knowledge domain visualization focuses on practical issues concerning modeling and visualizing scientific revolutions. Studies growth patterns of specialties derived from citation and cocitation data on string theory in physics, using the general framework of Thomas Kuhn's structure of scientific revolutions. (Author/LRW)

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…

Fitting the Jigsaw of Citation: Information Visualization in Domain Analysis.

ERIC Educational Resources Information Center

Chen, Chaomei; Paul, Ray J.; O'Keefe, Bob

2001-01-01

Discusses the role of information visualization in modeling and representing intellectual structures associated with scientific disciplines and visualizes the domain of computer graphics based on bibliographic data from author cocitation patterns. Highlights include author cocitation maps, citation time lines, animation of a high-dimensional…

Genomics Analogy Model for Educators (GAME): Fuzzy DNA Model to Enable the Learning of Gene Sequencing by Visually-Impaired and Blind Students

ERIC Educational Resources Information Center

Butler, Charles; Bello, Julia; York, Alan; Orvis, Kathryn; Pittendrigh, Barry R.

2008-01-01

Much of the general population is aware of terms such as biotechnology, genetic engineering, and genomics. However, there is a lack of understanding concerning these fields among many secondary school students. Few teaching models exist to explain concepts behind genomics and even less are available for teaching the visually impaired and blind.…

A Comparison between Elementary School Students' Mental Models and Visualizations in Textbooks for the Concept of Atom

ERIC Educational Resources Information Center

Polat-Yaseen, Zeynep

2012-01-01

This study was designed for two major goals, which are to describe students' mental models about atom concept from 6th to 8th grade and to compare students' mental models with visual representations of atom in textbooks. Qualitative and quantitative data were collected with 4 open-ended questions including drawings which were quantified using the…

Testing a Poisson Counter Model for Visual Identification of Briefly Presented, Mutually Confusable Single Stimuli in Pure Accuracy Tasks

ERIC Educational Resources Information Center

Kyllingsbaek, Soren; Markussen, Bo; Bundesen, Claus

2012-01-01

The authors propose and test a simple model of the time course of visual identification of briefly presented, mutually confusable single stimuli in pure accuracy tasks. The model implies that during stimulus analysis, tentative categorizations that stimulus i belongs to category j are made at a constant Poisson rate, v(i, j). The analysis is…

Narrative, Visual Model and Dragon Culture: A Narrative Analysis of Value Presentation in Two Movies Preferred by Chinese Adolescents. Research Bulletin 98.

ERIC Educational Resources Information Center

Jin, He

A narrative study was conducted of the visual models in two movies preferred by Chinese adolescents in two schools (n=152). The two movies studied were "Three Decisive Campaigns" (A Chinese Trilogy) and the American science fiction movie, "Jurassic Park." The modified approach from Bandura's modeling theory and film semiotics…

D Modelling and Interactive Web-Based Visualization of Cultural Heritage Objects

NASA Astrophysics Data System (ADS)

Koeva, M. N.

2016-06-01

Nowadays, there are rapid developments in the fields of photogrammetry, laser scanning, computer vision and robotics, together aiming to provide highly accurate 3D data that is useful for various applications. In recent years, various LiDAR and image-based techniques have been investigated for 3D modelling because of their opportunities for fast and accurate model generation. For cultural heritage preservation and the representation of objects that are important for tourism and their interactive visualization, 3D models are highly effective and intuitive for present-day users who have stringent requirements and high expectations. Depending on the complexity of the objects for the specific case, various technological methods can be applied. The selected objects in this particular research are located in Bulgaria - a country with thousands of years of history and cultural heritage dating back to ancient civilizations. This motivates the preservation, visualisation and recreation of undoubtedly valuable historical and architectural objects and places, which has always been a serious challenge for specialists in the field of cultural heritage. In the present research, comparative analyses regarding principles and technological processes needed for 3D modelling and visualization are presented. The recent problems, efforts and developments in interactive representation of precious objects and places in Bulgaria are presented. Three technologies based on real projects are described: (1) image-based modelling using a non-metric hand-held camera; (2) 3D visualization based on spherical panoramic images; (3) and 3D geometric and photorealistic modelling based on architectural CAD drawings. Their suitability for web-based visualization are demonstrated and compared. Moreover the possibilities for integration with additional information such as interactive maps, satellite imagery, sound, video and specific information for the objects are described. This comparative study discusses the advantages and disadvantages of these three approaches and their integration in multiple domains, such as web-based 3D city modelling, tourism and architectural 3D visualization. It was concluded that image-based modelling and panoramic visualisation are simple, fast and effective techniques suitable for simultaneous virtual representation of many objects. However, additional measurements or CAD information will be beneficial for obtaining higher accuracy.

Deep neural networks for modeling visual perceptual learning.

PubMed

Wenliang, Li; Seitz, Aaron R

2018-05-23

Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. While existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings. Here, we show that a well-known instance of deep neural network (DNN), while not designed specifically for VPL, provides a computational model of VPL with enough complexity to be studied at many levels of analyses. After learning a Gabor orientation discrimination task, the DNN model reproduced key behavioral results, including increasing specificity with higher task precision, and also suggested that learning precise discriminations could asymmetrically transfer to coarse discriminations when the stimulus conditions varied. In line with the behavioral findings, the distribution of plasticity moved towards lower layers when task precision increased, and this distribution was also modulated by tasks with different stimulus types. Furthermore, learning in the network units demonstrated close resemblance to extant electrophysiological recordings in monkey visual areas. Altogether, the DNN fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. Although the comparisons were mostly qualitative, the DNN provides a new method of studying VPL and can serve as a testbed for theories and assist in generating predictions for physiological investigations. SIGNIFICANCE STATEMENT Visual perceptual learning (VPL) has been found to cause changes at multiple stages of the visual hierarchy. We found that training a deep neural network (DNN) on an orientation discrimination task produced similar behavioral and physiological patterns found in human and monkey experiments. Unlike existing VPL models, the DNN was pre-trained on natural images to reach high performance in object recognition but was not designed specifically for VPL, and yet it fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. When used with care, this unbiased and deep-hierarchical model can provide new ways of studying VPL from behavior to physiology. Copyright © 2018 the authors.

Resolving the organization of the third tier visual cortex in primates: a hypothesis-based approach.

PubMed

Angelucci, Alessandra; Rosa, Marcello G P

2015-01-01

As highlighted by several contributions to this special issue, there is still ongoing debate about the number, exact location, and boundaries of the visual areas located in cortex immediately rostral to the second visual area (V2), i.e., the "third tier" visual cortex, in primates. In this review, we provide a historical overview of the main ideas that have led to four models of third tier cortex organization, which are at the center of today's debate. We formulate specific predictions of these models, and compare these predictions with experimental evidence obtained primarily in New World primates. From this analysis, we conclude that only one of these models (the "multiple-areas" model) can accommodate the breadth of available experimental evidence. According to this model, most of the third tier cortex in New World primates is occupied by two distinct areas, both representing the full contralateral visual quadrant: the dorsomedial area (DM), restricted to the dorsal half of the third visual complex, and the ventrolateral posterior area (VLP), occupying its ventral half and a substantial fraction of its dorsal half. DM belongs to the dorsal stream of visual processing, and overlaps with macaque parietooccipital (PO) area (or V6), whereas VLP belongs to the ventral stream and overlaps considerably with area V3 proposed by others. In contrast, there is substantial evidence that is inconsistent with the concept of a single elongated area V3 lining much of V2. We also review the experimental evidence from macaque monkey and humans, and propose that, once the data are interpreted within an evolutionary-developmental context, these species share a homologous (but not necessarily identical) organization of the third tier cortex as that observed in New World monkeys. Finally, we identify outstanding issues, and propose experiments to resolve them, highlighting in particular the need for more extensive, hypothesis-driven investigations in macaque and humans.