Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision.

PubMed

Zhong, Bineng; Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method.

Convolutional Deep Belief Networks for Single-Cell/Object Tracking in Computational Biology and Computer Vision

PubMed Central

Pan, Shengnan; Zhang, Hongbo; Wang, Tian; Du, Jixiang; Chen, Duansheng; Cao, Liujuan

2016-01-01

In this paper, we propose deep architecture to dynamically learn the most discriminative features from data for both single-cell and object tracking in computational biology and computer vision. Firstly, the discriminative features are automatically learned via a convolutional deep belief network (CDBN). Secondly, we design a simple yet effective method to transfer features learned from CDBNs on the source tasks for generic purpose to the object tracking tasks using only limited amount of training data. Finally, to alleviate the tracker drifting problem caused by model updating, we jointly consider three different types of positive samples. Extensive experiments validate the robustness and effectiveness of the proposed method. PMID:27847827

Lumber Grading With A Computer Vision System

Treesearch

Richard W. Conners; Tai-Hoon Cho; Philip A. Araman

1989-01-01

Over the past few years significant progress has been made in developing a computer vision system for locating and identifying defects on surfaced hardwood lumber. Unfortunately, until September of 1988 little research had gone into developing methods for analyzing rough lumber. This task is arguably more complex than the analysis of surfaced lumber. The prime...

Microscope self-calibration based on micro laser line imaging and soft computing algorithms

NASA Astrophysics Data System (ADS)

Apolinar Muñoz Rodríguez, J.

2018-06-01

A technique to perform microscope self-calibration via micro laser line and soft computing algorithms is presented. In this technique, the microscope vision parameters are computed by means of soft computing algorithms based on laser line projection. To implement the self-calibration, a microscope vision system is constructed by means of a CCD camera and a 38 μm laser line. From this arrangement, the microscope vision parameters are represented via Bezier approximation networks, which are accomplished through the laser line position. In this procedure, a genetic algorithm determines the microscope vision parameters by means of laser line imaging. Also, the approximation networks compute the three-dimensional vision by means of the laser line position. Additionally, the soft computing algorithms re-calibrate the vision parameters when the microscope vision system is modified during the vision task. The proposed self-calibration improves accuracy of the traditional microscope calibration, which is accomplished via external references to the microscope system. The capability of the self-calibration based on soft computing algorithms is determined by means of the calibration accuracy and the micro-scale measurement error. This contribution is corroborated by an evaluation based on the accuracy of the traditional microscope calibration.

Machine vision for real time orbital operations

NASA Technical Reports Server (NTRS)

Vinz, Frank L.

1988-01-01

Machine vision for automation and robotic operation of Space Station era systems has the potential for increasing the efficiency of orbital servicing, repair, assembly and docking tasks. A machine vision research project is described in which a TV camera is used for inputing visual data to a computer so that image processing may be achieved for real time control of these orbital operations. A technique has resulted from this research which reduces computer memory requirements and greatly increases typical computational speed such that it has the potential for development into a real time orbital machine vision system. This technique is called AI BOSS (Analysis of Images by Box Scan and Syntax).

Marking parts to aid robot vision

NASA Technical Reports Server (NTRS)

Bales, J. W.; Barker, L. K.

1981-01-01

The premarking of parts for subsequent identification by a robot vision system appears to be beneficial as an aid in the automation of certain tasks such as construction in space. A simple, color coded marking system is presented which allows a computer vision system to locate an object, calculate its orientation, and determine its identity. Such a system has the potential to operate accurately, and because the computer shape analysis problem has been simplified, it has the ability to operate in real time.

Military Vision Research Program

DTIC Science & Technology

2011-07-01

accomplishments emanating from this research . • 3 novel computer-based tasks have been developed that measure visual distortions • These tests are based...10-1-0392 TITLE: Military Vision Research Program PRINCIPAL INVESTIGATOR: Dr. Darlene Dartt...CONTRACTING ORGANIZATION: The Schepens Eye Research

Visualizing stressful aspects of repetitive motion tasks and opportunities for ergonomic improvements using computer vision.

PubMed

Greene, Runyu L; Azari, David P; Hu, Yu Hen; Radwin, Robert G

2017-11-01

Patterns of physical stress exposure are often difficult to measure, and the metrics of variation and techniques for identifying them is underdeveloped in the practice of occupational ergonomics. Computer vision has previously been used for evaluating repetitive motion tasks for hand activity level (HAL) utilizing conventional 2D videos. The approach was made practical by relaxing the need for high precision, and by adopting a semi-automatic approach for measuring spatiotemporal characteristics of the repetitive task. In this paper, a new method for visualizing task factors, using this computer vision approach, is demonstrated. After videos are made, the analyst selects a region of interest on the hand to track and the hand location and its associated kinematics are measured for every frame. The visualization method spatially deconstructs and displays the frequency, speed and duty cycle components of tasks that are part of the threshold limit value for hand activity for the purpose of identifying patterns of exposure associated with the specific job factors, as well as for suggesting task improvements. The localized variables are plotted as a heat map superimposed over the video, and displayed in the context of the task being performed. Based on the intensity of the specific variables used to calculate HAL, we can determine which task factors most contribute to HAL, and readily identify those work elements in the task that contribute more to increased risk for an injury. Work simulations and actual industrial examples are described. This method should help practitioners more readily measure and interpret temporal exposure patterns and identify potential task improvements. Copyright © 2017. Published by Elsevier Ltd.

Bag-of-visual-ngrams for histopathology image classification

NASA Astrophysics Data System (ADS)

López-Monroy, A. Pastor; Montes-y-Gómez, Manuel; Escalante, Hugo Jair; Cruz-Roa, Angel; González, Fabio A.

2013-11-01

This paper describes an extension of the Bag-of-Visual-Words (BoVW) representation for image categorization (IC) of histophatology images. This representation is one of the most used approaches in several high-level computer vision tasks. However, the BoVW representation has an important limitation: the disregarding of spatial information among visual words. This information may be useful to capture discriminative visual-patterns in specific computer vision tasks. In order to overcome this problem we propose the use of visual n-grams. N-grams based-representations are very popular in the field of natural language processing (NLP), in particular within text mining and information retrieval. We propose building a codebook of n-grams and then representing images by histograms of visual n-grams. We evaluate our proposal in the challenging task of classifying histopathology images. The novelty of our proposal lies in the fact that we use n-grams as attributes for a classification model (together with visual-words, i.e., 1-grams). This is common practice within NLP, although, to the best of our knowledge, this idea has not been explored yet within computer vision. We report experimental results in a database of histopathology images where our proposed method outperforms the traditional BoVWs formulation.

The Interdependence of Computers, Robots, and People.

ERIC Educational Resources Information Center

Ludden, Laverne; And Others

Computers and robots are becoming increasingly more advanced, with smaller and cheaper computers now doing jobs once reserved for huge multimillion dollar computers and with robots performing feats such as painting cars and using television cameras to simulate vision as they perform factory tasks. Technicians expect computers to become even more…

Neurovision processor for designing intelligent sensors

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1992-03-01

A programmable multi-task neuro-vision processor, called the Positive-Negative (PN) neural processor, is proposed as a plausible hardware mechanism for constructing robust multi-task vision sensors. The computational operations performed by the PN neural processor are loosely based on the neural activity fields exhibited by certain nervous tissue layers situated in the brain. The neuro-vision processor can be programmed to generate diverse dynamic behavior that may be used for spatio-temporal stabilization (STS), short-term visual memory (STVM), spatio-temporal filtering (STF) and pulse frequency modulation (PFM). A multi- functional vision sensor that performs a variety of information processing operations on time- varying two-dimensional sensory images can be constructed from a parallel and hierarchical structure of numerous individually programmed PN neural processors.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-01-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

The use of interactive computer vision and robot hand controllers for enhancing manufacturing safety

NASA Astrophysics Data System (ADS)

Marzwell, Neville I.; Jacobus, Charles J.; Peurach, Thomas M.; Mitchell, Brian T.

1994-02-01

Current available robotic systems provide limited support for CAD-based model-driven visualization, sensing algorithm development and integration, and automated graphical planning systems. This paper describes ongoing work which provides the functionality necessary to apply advanced robotics to automated manufacturing and assembly operations. An interface has been built which incorporates 6-DOF tactile manipulation, displays for three dimensional graphical models, and automated tracking functions which depend on automated machine vision. A set of tools for single and multiple focal plane sensor image processing and understanding has been demonstrated which utilizes object recognition models. The resulting tool will enable sensing and planning from computationally simple graphical objects. A synergistic interplay between human and operator vision is created from programmable feedback received from the controller. This approach can be used as the basis for implementing enhanced safety in automated robotics manufacturing, assembly, repair and inspection tasks in both ground and space applications. Thus, an interactive capability has been developed to match the modeled environment to the real task environment for safe and predictable task execution.

Quality Control by Artificial Vision

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

Lam, Edmond Y.; Gleason, Shaun Scott; Niel, Kurt S.

2010-01-01

Computational technology has fundamentally changed many aspects of our lives. One clear evidence is the development of artificial-vision systems, which have effectively automated many manual tasks ranging from quality inspection to quantitative assessment. In many cases, these machine-vision systems are even preferred over manual ones due to their repeatability and high precision. Such advantages come from significant research efforts in advancing sensor technology, illumination, computational hardware, and image-processing algorithms. Similar to the Special Section on Quality Control by Artificial Vision published two years ago in Volume 17, Issue 3 of the Journal of Electronic Imaging, the present one invited papersmore » relevant to fundamental technology improvements to foster quality control by artificial vision, and fine-tuned the technology for specific applications. We aim to balance both theoretical and applied work pertinent to this special section theme. Consequently, we have seven high-quality papers resulting from the stringent peer-reviewing process in place at the Journal of Electronic Imaging. Some of the papers contain extended treatment of the authors work presented at the SPIE Image Processing: Machine Vision Applications conference and the International Conference on Quality Control by Artificial Vision. On the broad application side, Liu et al. propose an unsupervised texture image segmentation scheme. Using a multilayer data condensation spectral clustering algorithm together with wavelet transform, they demonstrate the effectiveness of their approach on both texture and synthetic aperture radar images. A problem related to image segmentation is image extraction. For this, O'Leary et al. investigate the theory of polynomial moments and show how these moments can be compared to classical filters. They also show how to use the discrete polynomial-basis functions for the extraction of 3-D embossed digits, demonstrating superiority over Fourier-basis functions for this task. Image registration is another important task for machine vision. Bingham and Arrowood investigate the implementation and results in applying Fourier phase matching for projection registration, with a particular focus on nondestructive testing using computed tomography. Readers interested in enriching their arsenal of image-processing algorithms for machine-vision tasks should find these papers enriching. Meanwhile, we have four papers dealing with more specific machine-vision tasks. The first one, Yahiaoui et al., is quantitative in nature, using machine vision for real-time passenger counting. Occulsion is a common problem in counting objects and people, and they circumvent this issue with a dense stereovision system, achieving 97 to 99% accuracy in their tests. On the other hand, the second paper by Oswald-Tranta et al. focuses on thermographic crack detection. An infrared camera is used to detect inhomogeneities, which may indicate surface cracks. They describe the various steps in developing fully automated testing equipment aimed at a high throughput. Another paper describing an inspection system is Molleda et al., which handles flatness inspection of rolled products. They employ optical-laser triangulation and 3-D surface reconstruction for this task, showing how these can be achieved in real time. Last but not least, Presles et al. propose a way to monitor the particle-size distribution of batch crystallization processes. This is achieved through a new in situ imaging probe and image-analysis methods. While it is unlikely any reader may be working on these four specific problems at the same time, we are confident that readers will find these papers inspiring and potentially helpful to their own machine-vision system developments.« less

Quality grading of Atlantic salmon (Salmo salar) by computer vision.

PubMed

Misimi, E; Erikson, U; Skavhaug, A

2008-06-01

In this study, we present a promising method of computer vision-based quality grading of whole Atlantic salmon (Salmo salar). Using computer vision, it was possible to differentiate among different quality grades of Atlantic salmon based on the external geometrical information contained in the fish images. Initially, before the image acquisition, the fish were subjectively graded and labeled into grading classes by a qualified human inspector in the processing plant. Prior to classification, the salmon images were segmented into binary images, and then feature extraction was performed on the geometrical parameters of the fish from the grading classes. The classification algorithm was a threshold-based classifier, which was designed using linear discriminant analysis. The performance of the classifier was tested by using the leave-one-out cross-validation method, and the classification results showed a good agreement between the classification done by human inspectors and by the computer vision. The computer vision-based method classified correctly 90% of the salmon from the data set as compared with the classification by human inspector. Overall, it was shown that computer vision can be used as a powerful tool to grade Atlantic salmon into quality grades in a fast and nondestructive manner by a relatively simple classifier algorithm. The low cost of implementation of today's advanced computer vision solutions makes this method feasible for industrial purposes in fish plants as it can replace manual labor, on which grading tasks still rely.

Normative values for a tablet computer-based application to assess chromatic contrast sensitivity.

PubMed

Bodduluri, Lakshmi; Boon, Mei Ying; Ryan, Malcolm; Dain, Stephen J

2018-04-01

Tablet computer displays are amenable for the development of vision tests in a portable form. Assessing color vision using an easily accessible and portable test may help in the self-monitoring of vision-related changes in ocular/systemic conditions and assist in the early detection of disease processes. Tablet computer-based games were developed with different levels of gamification as a more portable option to assess chromatic contrast sensitivity. Game 1 was designed as a clinical version with no gaming elements. Game 2 was a gamified version of game 1 (added fun elements: feedback, scores, and sounds) and game 3 was a complete game with vision task nested within. The current study aimed to determine the normative values and evaluate repeatability of the tablet computer-based games in comparison with an established test, the Cambridge Colour Test (CCT) Trivector test. Normally sighted individuals [N = 100, median (range) age 19.0 years (18-56 years)] had their chromatic contrast sensitivity evaluated binocularly using the three games and the CCT. Games 1 and 2 and the CCT showed similar absolute thresholds and tolerance intervals, and game 3 had significantly lower values than games 1, 2, and the CCT, due to visual task differences. With the exception of game 3 for blue-yellow, the CCT and tablet computer-based games showed similar repeatability with comparable 95% limits of agreement. The custom-designed games are portable, rapid, and may find application in routine clinical practice, especially for testing younger populations.

Object recognition based on Google's reverse image search and image similarity

NASA Astrophysics Data System (ADS)

Horváth, András.

2015-12-01

Image classification is one of the most challenging tasks in computer vision and a general multiclass classifier could solve many different tasks in image processing. Classification is usually done by shallow learning for predefined objects, which is a difficult task and very different from human vision, which is based on continuous learning of object classes and one requires years to learn a large taxonomy of objects which are not disjunct nor independent. In this paper I present a system based on Google image similarity algorithm and Google image database, which can classify a large set of different objects in a human like manner, identifying related classes and taxonomies.

Novel techniques for data decomposition and load balancing for parallel processing of vision systems: Implementation and evaluation using a motion estimation system

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Computer vision systems employ a sequence of vision algorithms in which the output of an algorithm is the input of the next algorithm in the sequence. Algorithms that constitute such systems exhibit vastly different computational characteristics, and therefore, require different data decomposition techniques and efficient load balancing techniques for parallel implementation. However, since the input data for a task is produced as the output data of the previous task, this information can be exploited to perform knowledge based data decomposition and load balancing. Presented here are algorithms for a motion estimation system. The motion estimation is based on the point correspondence between the involved images which are a sequence of stereo image pairs. Researchers propose algorithms to obtain point correspondences by matching feature points among stereo image pairs at any two consecutive time instants. Furthermore, the proposed algorithms employ non-iterative procedures, which results in saving considerable amounts of computation time. The system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from consecutive time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters.

Analog "neuronal" networks in early vision.

PubMed Central

Koch, C; Marroquin, J; Yuille, A

1986-01-01

Many problems in early vision can be formulated in terms of minimizing a cost function. Examples are shape from shading, edge detection, motion analysis, structure from motion, and surface interpolation. As shown by Poggio and Koch [Poggio, T. & Koch, C. (1985) Proc. R. Soc. London, Ser. B 226, 303-323], quadratic variational problems, an important subset of early vision tasks, can be "solved" by linear, analog electrical, or chemical networks. However, in the presence of discontinuities, the cost function is nonquadratic, raising the question of designing efficient algorithms for computing the optimal solution. Recently, Hopfield and Tank [Hopfield, J. J. & Tank, D. W. (1985) Biol. Cybern. 52, 141-152] have shown that networks of nonlinear analog "neurons" can be effective in computing the solution of optimization problems. We show how these networks can be generalized to solve the nonconvex energy functionals of early vision. We illustrate this approach by implementing a specific analog network, solving the problem of reconstructing a smooth surface from sparse data while preserving its discontinuities. These results suggest a novel computational strategy for solving early vision problems in both biological and real-time artificial vision systems. PMID:3459172

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.

Computing Visible-Surface Representations,

DTIC Science & Technology

1985-03-01

Terzopoulos N00014-75-C-0643 9. PERFORMING ORGANIZATION NAME AMC ADDRESS 10. PROGRAM ELEMENT. PROJECT, TASK Artificial Inteligence Laboratory AREA A...Massachusetts Institute of lechnolog,. Support lbr the laboratory’s Artificial Intelligence research is provided in part by the Advanced Rtccarcl Proj...dynamically maintaining visible surface representations. Whether the intention is to model human vision or to design competent artificial vision systems

Connectionist Models and Parallelism in High Level Vision.

DTIC Science & Technology

1985-01-01

GRANT NUMBER(s) Jerome A. Feldman N00014-82-K-0193 9. PERFORMING ORGANIZATION NAME AND ADDRESS 10. PROGRAM ELEMENt. PROJECT, TASK Computer Science...Connectionist Models 2.1 Background and Overviev % Computer science is just beginning to look seriously at parallel computation : it may turn out that...the chair. The program includes intermediate level networks that compute more complex joints and ones that compute parallelograms in the image. These

Real-Time, Multiple, Pan/Tilt/Zoom, Computer Vision Tracking, and 3D Position Estimating System for Unmanned Aerial System Metrology

DTIC Science & Technology

2013-10-18

of the enclosed tasks plus the last parallel task for a total of five parallel tasks for one iteration, i). for j = 1…N for i = 1… 8 Figure...drizzling juices culminating in a state of salivating desire to cut a piece and enjoy. On the other hand, the smell could be that of a pungent, unpleasant

Video control system for a drilling in furniture workpiece

NASA Astrophysics Data System (ADS)

Khmelev, V. L.; Satarov, R. N.; Zavyalova, K. V.

2018-05-01

During last 5 years, Russian industry has being starting to be a robotic, therefore scientific groups got new tasks. One of new tasks is machine vision systems, which should solve problem of automatic quality control. This type of systems has a cost of several thousand dollars each. The price is impossible for regional small business. In this article, we describe principle and algorithm of cheap video control system, which one uses web-cameras and notebook or desktop computer as a computing unit.

Development of a Laparoscopic Box Trainer Based on Open Source Hardware and Artificial Intelligence for Objective Assessment of Surgical Psychomotor Skills.

PubMed

Alonso-Silverio, Gustavo A; Pérez-Escamirosa, Fernando; Bruno-Sanchez, Raúl; Ortiz-Simon, José L; Muñoz-Guerrero, Roberto; Minor-Martinez, Arturo; Alarcón-Paredes, Antonio

2018-05-01

A trainer for online laparoscopic surgical skills assessment based on the performance of experts and nonexperts is presented. The system uses computer vision, augmented reality, and artificial intelligence algorithms, implemented into a Raspberry Pi board with Python programming language. Two training tasks were evaluated by the laparoscopic system: transferring and pattern cutting. Computer vision libraries were used to obtain the number of transferred points and simulated pattern cutting trace by means of tracking of the laparoscopic instrument. An artificial neural network (ANN) was trained to learn from experts and nonexperts' behavior for pattern cutting task, whereas the assessment of transferring task was performed using a preestablished threshold. Four expert surgeons in laparoscopic surgery, from hospital "Raymundo Abarca Alarcón," constituted the experienced class for the ANN. Sixteen trainees (10 medical students and 6 residents) without laparoscopic surgical skills and limited experience in minimal invasive techniques from School of Medicine at Universidad Autónoma de Guerrero constituted the nonexperienced class. Data from participants performing 5 daily repetitions for each task during 5 days were used to build the ANN. The participants tend to improve their learning curve and dexterity with this laparoscopic training system. The classifier shows mean accuracy and receiver operating characteristic curve of 90.98% and 0.93, respectively. Moreover, the ANN was able to evaluate the psychomotor skills of users into 2 classes: experienced or nonexperienced. We constructed and evaluated an affordable laparoscopic trainer system using computer vision, augmented reality, and an artificial intelligence algorithm. The proposed trainer has the potential to increase the self-confidence of trainees and to be applied to programs with limited resources.

Factors influencing hand/eye synchronicity in the computer age.

PubMed

Grant, A H

1992-09-01

In using a computer, the relation of vision to hand/finger actuated keyboard usage in performing fine motor-coordinated functions is influenced by the physical location, size, and collective placement of the keys. Traditional nonprehensile flat/rectangular keyboard applications usually require a high and nearly constant level of visual attention. Biometrically shaped keyboards would allow for prehensile hand-posturing, thus affording better tactile familiarity with the keys, requiring less intense and less constant level of visual attention to the task, and providing a greater measure of freedom from having to visualize the key(s). Workpace and related physiological changes, aging, onset of monocularization (intermittent lapsing of binocularity for near vision) that accompanies presbyopia, tool colors, and background contrast are factors affecting constancy of visual attention to task performance. Capitas extension, excessive excyclotorsion, and repetitive strain injuries (such as carpal tunnel syndrome) are common and debilitating concomitants to computer usage. These problems can be remedied by improved keyboard design. The salutary role of mnemonics in minimizing visual dependency is discussed.

Vision-Aided Autonomous Landing and Ingress of Micro Aerial Vehicles

NASA Technical Reports Server (NTRS)

Brockers, Roland; Ma, Jeremy C.; Matthies, Larry H.; Bouffard, Patrick

2012-01-01

Micro aerial vehicles have limited sensor suites and computational power. For reconnaissance tasks and to conserve energy, these systems need the ability to autonomously land at vantage points or enter buildings (ingress). But for autonomous navigation, information is needed to identify and guide the vehicle to the target. Vision algorithms can provide egomotion estimation and target detection using input from cameras that are easy to include in miniature systems.

Use of 3D vision for fine robot motion

NASA Technical Reports Server (NTRS)

Lokshin, Anatole; Litwin, Todd

1989-01-01

An integration of 3-D vision systems with robot manipulators will allow robots to operate in a poorly structured environment by visually locating targets and obstacles. However, by using computer vision for objects acquisition makes the problem of overall system calibration even more difficult. Indeed, in a CAD based manipulation a control architecture has to find an accurate mapping between the 3-D Euclidean work space and a robot configuration space (joint angles). If a stereo vision is involved, then one needs to map a pair of 2-D video images directly into the robot configuration space. Neural Network approach aside, a common solution to this problem is to calibrate vision and manipulator independently, and then tie them via common mapping into the task space. In other words, both vision and robot refer to some common Absolute Euclidean Coordinate Frame via their individual mappings. This approach has two major difficulties. First a vision system has to be calibrated over the total work space. And second, the absolute frame, which is usually quite arbitrary, has to be the same with a high degree of precision for both robot and vision subsystem calibrations. The use of computer vision to allow robust fine motion manipulation in a poorly structured world which is currently in progress is described along with the preliminary results and encountered problems.

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

Blink rate, incomplete blinks and computer vision syndrome.

PubMed

Portello, Joan K; Rosenfield, Mark; Chu, Christina A

2013-05-01

Computer vision syndrome (CVS), a highly prevalent condition, is frequently associated with dry eye disorders. Furthermore, a reduced blink rate has been observed during computer use. The present study examined whether post task ocular and visual symptoms are associated with either a decreased blink rate or a higher prevalence of incomplete blinks. An additional trial tested whether increasing the blink rate would reduce CVS symptoms. Subjects (N = 21) were required to perform a continuous 15-minute reading task on a desktop computer at a viewing distance of 50 cm. Subjects were videotaped during the task to determine their blink rate and amplitude. Immediately after the task, subjects completed a questionnaire regarding ocular symptoms experienced during the trial. In a second session, the blink rate was increased by means of an audible tone that sounded every 4 seconds, with subjects being instructed to blink on hearing the tone. The mean blink rate during the task without the audible tone was 11.6 blinks per minute (SD, 7.84). The percentage of blinks deemed incomplete for each subject ranged from 0.9 to 56.5%, with a mean of 16.1% (SD, 15.7). A significant positive correlation was observed between the total symptom score and the percentage of incomplete blinks during the task (p = 0.002). Furthermore, a significant negative correlation was noted between the blink score and symptoms (p = 0.035). Increasing the mean blink rate to 23.5 blinks per minute by means of the audible tone did not produce a significant change in the symptom score. Whereas CVS symptoms are associated with a reduced blink rate, the completeness of the blink may be equally significant. Because instructing a patient to increase his or her blink rate may be ineffective or impractical, actions to achieve complete corneal coverage during blinking may be more helpful in alleviating symptoms during computer operation.

Computer vision syndrome in presbyopia and beginning presbyopia: effects of spectacle lens type.

PubMed

Jaschinski, Wolfgang; König, Mirjam; Mekontso, Tiofil M; Ohlendorf, Arne; Welscher, Monique

2015-05-01

This office field study investigated the effects of different types of spectacle lenses habitually worn by computer users with presbyopia and in the beginning stages of presbyopia. Computer vision syndrome was assessed through reported complaints and ergonomic conditions. A questionnaire regarding the type of habitually worn near-vision lenses at the workplace, visual conditions and the levels of different types of complaints was administered to 175 participants aged 35 years and older (mean ± SD: 52.0 ± 6.7 years). Statistical factor analysis identified five specific aspects of the complaints. Workplace conditions were analysed based on photographs taken in typical working conditions. In the subgroup of 25 users between the ages of 36 and 57 years (mean 44 ± 5 years), who wore distance-vision lenses and performed more demanding occupational tasks, the reported extents of 'ocular strain', 'musculoskeletal strain' and 'headache' increased with the daily duration of computer work and explained up to 44 per cent of the variance (rs = 0.66). In the other subgroups, this effect was smaller, while in the complete sample (n = 175), this correlation was approximately rs = 0.2. The subgroup of 85 general-purpose progressive lens users (mean age 54 years) adopted head inclinations that were approximately seven degrees more elevated than those of the subgroups with single vision lenses. The present questionnaire was able to assess the complaints of computer users depending on the type of spectacle lenses worn. A missing near-vision addition among participants in the early stages of presbyopia was identified as a risk factor for complaints among those with longer daily durations of demanding computer work. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Visual pathways from the perspective of cost functions and multi-task deep neural networks.

PubMed

Scholte, H Steven; Losch, Max M; Ramakrishnan, Kandan; de Haan, Edward H F; Bohte, Sander M

2018-01-01

Vision research has been shaped by the seminal insight that we can understand the higher-tier visual cortex from the perspective of multiple functional pathways with different goals. In this paper, we try to give a computational account of the functional organization of this system by reasoning from the perspective of multi-task deep neural networks. Machine learning has shown that tasks become easier to solve when they are decomposed into subtasks with their own cost function. We hypothesize that the visual system optimizes multiple cost functions of unrelated tasks and this causes the emergence of a ventral pathway dedicated to vision for perception, and a dorsal pathway dedicated to vision for action. To evaluate the functional organization in multi-task deep neural networks, we propose a method that measures the contribution of a unit towards each task, applying it to two networks that have been trained on either two related or two unrelated tasks, using an identical stimulus set. Results show that the network trained on the unrelated tasks shows a decreasing degree of feature representation sharing towards higher-tier layers while the network trained on related tasks uniformly shows high degree of sharing. We conjecture that the method we propose can be used to analyze the anatomical and functional organization of the visual system and beyond. We predict that the degree to which tasks are related is a good descriptor of the degree to which they share downstream cortical-units. Copyright © 2017 Elsevier Ltd. All rights reserved.

A FPGA-based architecture for real-time image matching

NASA Astrophysics Data System (ADS)

Wang, Jianhui; Zhong, Sheng; Xu, Wenhui; Zhang, Weijun; Cao, Zhiguo

2013-10-01

Image matching is a fundamental task in computer vision. It is used to establish correspondence between two images taken at different viewpoint or different time from the same scene. However, its large computational complexity has been a challenge to most embedded systems. This paper proposes a single FPGA-based image matching system, which consists of SIFT feature detection, BRIEF descriptor extraction and BRIEF matching. It optimizes the FPGA architecture for the SIFT feature detection to reduce the FPGA resources utilization. Moreover, we implement BRIEF description and matching on FPGA also. The proposed system can implement image matching at 30fps (frame per second) for 1280x720 images. Its processing speed can meet the demand of most real-life computer vision applications.

Computer vision applications for coronagraphic optical alignment and image processing.

PubMed

Savransky, Dmitry; Thomas, Sandrine J; Poyneer, Lisa A; Macintosh, Bruce A

2013-05-10

Modern coronagraphic systems require very precise alignment between optical components and can benefit greatly from automated image processing. We discuss three techniques commonly employed in the fields of computer vision and image analysis as applied to the Gemini Planet Imager, a new facility instrument for the Gemini South Observatory. We describe how feature extraction and clustering methods can be used to aid in automated system alignment tasks, and also present a search algorithm for finding regular features in science images used for calibration and data processing. Along with discussions of each technique, we present our specific implementation and show results of each one in operation.

Multitask neurovision processor with extensive feedback and feedforward connections

NASA Astrophysics Data System (ADS)

Gupta, Madan M.; Knopf, George K.

1991-11-01

A multi-task neuro-vision parameter which performs a variety of information processing operations associated with the early stages of biological vision is presented. The network architecture of this neuro-vision processor, called the positive-negative (PN) neural processor, is loosely based on the neural activity fields exhibited by thalamic and cortical nervous tissue layers. The computational operation performed by the processor arises from the strength of the recurrent feedback among the numerous positive and negative neural computing units. By adjusting the feedback connections it is possible to generate diverse dynamic behavior that may be used for short-term visual memory (STVM), spatio-temporal filtering (STF), and pulse frequency modulation (PFM). The information attributes that are to be processes may be regulated by modifying the feedforward connections from the signal space to the neural processor.

Infrared Cephalic-Vein to Assist Blood Extraction Tasks: Automatic Projection and Recognition

NASA Astrophysics Data System (ADS)

Lagüela, S.; Gesto, M.; Riveiro, B.; González-Aguilera, D.

2017-05-01

Thermal infrared band is not commonly used in photogrammetric and computer vision algorithms, mainly due to the low spatial resolution of this type of imagery. However, this band captures sub-superficial information, increasing the capabilities of visible bands regarding applications. This fact is especially important in biomedicine and biometrics, allowing the geometric characterization of interior organs and pathologies with photogrammetric principles, as well as the automatic identification and labelling using computer vision algorithms. This paper presents advances of close-range photogrammetry and computer vision applied to thermal infrared imagery, with the final application of Augmented Reality in order to widen its application in the biomedical field. In this case, the thermal infrared image of the arm is acquired and simultaneously projected on the arm, together with the identification label of the cephalic-vein. This way, blood analysts are assisted in finding the vein for blood extraction, especially in those cases where the identification by the human eye is a complex task. Vein recognition is performed based on the Gaussian temperature distribution in the area of the vein, while the calibration between projector and thermographic camera is developed through feature extraction and pattern recognition. The method is validated through its application to a set of volunteers, with different ages and genres, in such way that different conditions of body temperature and vein depth are covered for the applicability and reproducibility of the method.

Three-dimensional vision enhances task performance independently of the surgical method.

PubMed

Wagner, O J; Hagen, M; Kurmann, A; Horgan, S; Candinas, D; Vorburger, S A

2012-10-01

Within the next few years, the medical industry will launch increasingly affordable three-dimensional (3D) vision systems for the operating room (OR). This study aimed to evaluate the effect of two-dimensional (2D) and 3D visualization on surgical skills and task performance. In this study, 34 individuals with varying laparoscopic experience (18 inexperienced individuals) performed three tasks to test spatial relationships, grasping and positioning, dexterity, precision, and hand-eye and hand-hand coordination. Each task was performed in 3D using binocular vision for open performance, the Viking 3Di Vision System for laparoscopic performance, and the DaVinci robotic system. The same tasks were repeated in 2D using an eye patch for monocular vision, conventional laparoscopy, and the DaVinci robotic system. Loss of 3D vision significantly increased the perceived difficulty of a task and the time required to perform it, independently of the approach (P < 0.0001-0.02). Simple tasks took 25 % to 30 % longer to complete and more complex tasks took 75 % longer with 2D than with 3D vision. Only the difficult task was performed faster with the robot than with laparoscopy (P = 0.005). In every case, 3D robotic performance was superior to conventional laparoscopy (2D) (P < 0.001-0.015). The more complex the task, the more 3D vision accelerates task completion compared with 2D vision. The gain in task performance is independent of the surgical method.

Compact Microscope Imaging System with Intelligent Controls

NASA Technical Reports Server (NTRS)

McDowell, Mark

2004-01-01

The figure presents selected views of a compact microscope imaging system (CMIS) that includes a miniature video microscope, a Cartesian robot (a computer- controlled three-dimensional translation stage), and machine-vision and control subsystems. The CMIS was built from commercial off-the-shelf instrumentation, computer hardware and software, and custom machine-vision software. The machine-vision and control subsystems include adaptive neural networks that afford a measure of artificial intelligence. The CMIS can perform several automated tasks with accuracy and repeatability . tasks that, heretofore, have required the full attention of human technicians using relatively bulky conventional microscopes. In addition, the automation and control capabilities of the system inherently include a capability for remote control. Unlike human technicians, the CMIS is not at risk of becoming fatigued or distracted: theoretically, it can perform continuously at the level of the best human technicians. In its capabilities for remote control and for relieving human technicians of tedious routine tasks, the CMIS is expected to be especially useful in biomedical research, materials science, inspection of parts on industrial production lines, and space science. The CMIS can automatically focus on and scan a microscope sample, find areas of interest, record the resulting images, and analyze images from multiple samples simultaneously. Automatic focusing is an iterative process: The translation stage is used to move the microscope along its optical axis in a succession of coarse, medium, and fine steps. A fast Fourier transform (FFT) of the image is computed at each step, and the FFT is analyzed for its spatial-frequency content. The microscope position that results in the greatest dispersal of FFT content toward high spatial frequencies (indicating that the image shows the greatest amount of detail) is deemed to be the focal position.

Modeling of the First Layers in the Fly's Eye

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Towards photorealistic and immersive virtual-reality environments for simulated prosthetic vision: integrating recent breakthroughs in consumer hardware and software.

PubMed

Zapf, Marc P; Matteucci, Paul B; Lovell, Nigel H; Zheng, Steven; Suaning, Gregg J

2014-01-01

Simulated prosthetic vision (SPV) in normally sighted subjects is an established way of investigating the prospective efficacy of visual prosthesis designs in visually guided tasks such as mobility. To perform meaningful SPV mobility studies in computer-based environments, a credible representation of both the virtual scene to navigate and the experienced artificial vision has to be established. It is therefore prudent to make optimal use of existing hardware and software solutions when establishing a testing framework. The authors aimed at improving the realism and immersion of SPV by integrating state-of-the-art yet low-cost consumer technology. The feasibility of body motion tracking to control movement in photo-realistic virtual environments was evaluated in a pilot study. Five subjects were recruited and performed an obstacle avoidance and wayfinding task using either keyboard and mouse, gamepad or Kinect motion tracking. Walking speed and collisions were analyzed as basic measures for task performance. Kinect motion tracking resulted in lower performance as compared to classical input methods, yet results were more uniform across vision conditions. The chosen framework was successfully applied in a basic virtual task and is suited to realistically simulate real-world scenes under SPV in mobility research. Classical input peripherals remain a feasible and effective way of controlling the virtual movement. Motion tracking, despite its limitations and early state of implementation, is intuitive and can eliminate between-subject differences due to familiarity to established input methods.

Natural Tasking of Robots Based on Human Interaction Cues

DTIC Science & Technology

2005-06-01

MIT. • Matthew Marjanovic , researcher, ITA Software. • Brian Scasselatti, Assistant Professor of Computer Science, Yale. • Matthew Williamson...2004. 25 [74] Charlie C. Kemp. Shoes as a platform for vision. 7th IEEE International Symposium on Wearable Computers, 2004. [75] Matthew Marjanovic ...meso: Simulated muscles for a humanoid robot. Presentation for Humanoid Robotics Group, MIT AI Lab, August 2001. [76] Matthew J. Marjanovic . Teaching

FPGA-Based Multimodal Embedded Sensor System Integrating Low- and Mid-Level Vision

PubMed Central

Botella, Guillermo; Martín H., José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms. PMID:22164069

FPGA-based multimodal embedded sensor system integrating low- and mid-level vision.

PubMed

Botella, Guillermo; Martín H, José Antonio; Santos, Matilde; Meyer-Baese, Uwe

2011-01-01

Motion estimation is a low-level vision task that is especially relevant due to its wide range of applications in the real world. Many of the best motion estimation algorithms include some of the features that are found in mammalians, which would demand huge computational resources and therefore are not usually available in real-time. In this paper we present a novel bioinspired sensor based on the synergy between optical flow and orthogonal variant moments. The bioinspired sensor has been designed for Very Large Scale Integration (VLSI) using properties of the mammalian cortical motion pathway. This sensor combines low-level primitives (optical flow and image moments) in order to produce a mid-level vision abstraction layer. The results are described trough experiments showing the validity of the proposed system and an analysis of the computational resources and performance of the applied algorithms.

Supporting Advice Sharing for Technical Problems in Residential Settings

ERIC Educational Resources Information Center

Poole, Erika Shehan

2010-01-01

Visions of future computing in residential settings often come with assumptions of seamless, well-functioning, properly configured devices and network connectivity. In the near term, however, processes of setup, maintenance, and troubleshooting are fraught with difficulties; householders regularly report these tasks as confusing, frustrating, and…

Real-time tracking using stereo and motion: Visual perception for space robotics

NASA Technical Reports Server (NTRS)

Nishihara, H. Keith; Thomas, Hans; Huber, Eric; Reid, C. Ann

1994-01-01

The state-of-the-art in computing technology is rapidly attaining the performance necessary to implement many early vision algorithms at real-time rates. This new capability is helping to accelerate progress in vision research by improving our ability to evaluate the performance of algorithms in dynamic environments. In particular, we are becoming much more aware of the relative stability of various visual measurements in the presence of camera motion and system noise. This new processing speed is also allowing us to raise our sights toward accomplishing much higher-level processing tasks, such as figure-ground separation and active object tracking, in real-time. This paper describes a methodology for using early visual measurements to accomplish higher-level tasks; it then presents an overview of the high-speed accelerators developed at Teleos to support early visual measurements. The final section describes the successful deployment of a real-time vision system to provide visual perception for the Extravehicular Activity Helper/Retriever robotic system in tests aboard NASA's KC135 reduced gravity aircraft.

Deep Learning: A Primer for Radiologists.

PubMed

Chartrand, Gabriel; Cheng, Phillip M; Vorontsov, Eugene; Drozdzal, Michal; Turcotte, Simon; Pal, Christopher J; Kadoury, Samuel; Tang, An

2017-01-01

Deep learning is a class of machine learning methods that are gaining success and attracting interest in many domains, including computer vision, speech recognition, natural language processing, and playing games. Deep learning methods produce a mapping from raw inputs to desired outputs (eg, image classes). Unlike traditional machine learning methods, which require hand-engineered feature extraction from inputs, deep learning methods learn these features directly from data. With the advent of large datasets and increased computing power, these methods can produce models with exceptional performance. These models are multilayer artificial neural networks, loosely inspired by biologic neural systems. Weighted connections between nodes (neurons) in the network are iteratively adjusted based on example pairs of inputs and target outputs by back-propagating a corrective error signal through the network. For computer vision tasks, convolutional neural networks (CNNs) have proven to be effective. Recently, several clinical applications of CNNs have been proposed and studied in radiology for classification, detection, and segmentation tasks. This article reviews the key concepts of deep learning for clinical radiologists, discusses technical requirements, describes emerging applications in clinical radiology, and outlines limitations and future directions in this field. Radiologists should become familiar with the principles and potential applications of deep learning in medical imaging. © RSNA, 2017.

Knowledge-based vision and simple visual machines.

PubMed Central

Cliff, D; Noble, J

1997-01-01

The vast majority of work in machine vision emphasizes the representation of perceived objects and events: it is these internal representations that incorporate the 'knowledge' in knowledge-based vision or form the 'models' in model-based vision. In this paper, we discuss simple machine vision systems developed by artificial evolution rather than traditional engineering design techniques, and note that the task of identifying internal representations within such systems is made difficult by the lack of an operational definition of representation at the causal mechanistic level. Consequently, we question the nature and indeed the existence of representations posited to be used within natural vision systems (i.e. animals). We conclude that representations argued for on a priori grounds by external observers of a particular vision system may well be illusory, and are at best place-holders for yet-to-be-identified causal mechanistic interactions. That is, applying the knowledge-based vision approach in the understanding of evolved systems (machines or animals) may well lead to theories and models that are internally consistent, computationally plausible, and entirely wrong. PMID:9304684

Multicolour LEDs in educational demonstrations of physics and optometry

NASA Astrophysics Data System (ADS)

Paulins, Paulis; Ozolinsh, Maris

2014-07-01

LED light sources are used to design experimental setup for university courses teaching human color vision. The setup allows to demonstrate various vision characteristics and to apply for student practical exercises to study eye spectral sensitivity in different spectral range using heterochromatic flicker photometry. Technique can be used in laboratory works for students to acquire knowledge in visual perception, basics of electronics and measuring, or it can be applied as fully computer control experiment. Besides studies of the eye spectral sensitivity students can practice in trichromatic color matching and other visual perception tasks

Detecting target changes in multiple object tracking with peripheral vision: More pronounced eccentricity effects for changes in form than in motion.

PubMed

Vater, Christian; Kredel, Ralf; Hossner, Ernst-Joachim

2017-05-01

In the current study, dual-task performance is examined with multiple-object tracking as a primary task and target-change detection as a secondary task. The to-be-detected target changes in conditions of either change type (form vs. motion; Experiment 1) or change salience (stop vs. slowdown; Experiment 2), with changes occurring at either near (5°-10°) or far (15°-20°) eccentricities (Experiments 1 and 2). The aim of the study was to test whether changes can be detected solely with peripheral vision. By controlling for saccades and computing gaze distances, we could show that participants used peripheral vision to monitor the targets and, additionally, to perceive changes at both near and far eccentricities. Noticeably, gaze behavior was not affected by the actual target change. Detection rates as well as response times generally varied as a function of change condition and eccentricity, with faster detections for motion changes and near changes. However, in contrast to the effects found for motion changes, sharp declines in detection rates and increased response times were observed for form changes as a function of the eccentricities. This result can be ascribed to properties of the visual system, namely to the limited spatial acuity in the periphery and the comparably receptive motion sensitivity of peripheral vision. These findings show that peripheral vision is functional for simultaneous target monitoring and target-change detection as saccadic information suppression can be avoided and covert attention can be optimally distributed to all targets. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

An egocentric vision based assistive co-robot.

PubMed

Zhang, Jingzhe; Zhuang, Lishuo; Wang, Yang; Zhou, Yameng; Meng, Yan; Hua, Gang

2013-06-01

We present the prototype of an egocentric vision based assistive co-robot system. In this co-robot system, the user is wearing a pair of glasses with a forward looking camera, and is actively engaged in the control loop of the robot in navigational tasks. The egocentric vision glasses serve for two purposes. First, it serves as a source of visual input to request the robot to find a certain object in the environment. Second, the motion patterns computed from the egocentric video associated with a specific set of head movements are exploited to guide the robot to find the object. These are especially helpful for quadriplegic individuals who do not have needed hand functionality for interaction and control with other modalities (e.g., joystick). In our co-robot system, when the robot does not fulfill the object finding task in a pre-specified time window, it would actively solicit user controls for guidance. Then the users can use the egocentric vision based gesture interface to orient the robot towards the direction of the object. After that the robot will automatically navigate towards the object until it finds it. Our experiments validated the efficacy of the closed-loop design to engage the human in the loop.

Image-Based Modeling Techniques for Architectural Heritage 3d Digitalization: Limits and Potentialities

NASA Astrophysics Data System (ADS)

Santagati, C.; Inzerillo, L.; Di Paola, F.

2013-07-01

3D reconstruction from images has undergone a revolution in the last few years. Computer vision techniques use photographs from data set collection to rapidly build detailed 3D models. The simultaneous applications of different algorithms (MVS), the different techniques of image matching, feature extracting and mesh optimization are inside an active field of research in computer vision. The results are promising: the obtained models are beginning to challenge the precision of laser-based reconstructions. Among all the possibilities we can mainly distinguish desktop and web-based packages. Those last ones offer the opportunity to exploit the power of cloud computing in order to carry out a semi-automatic data processing, thus allowing the user to fulfill other tasks on its computer; whereas desktop systems employ too much processing time and hard heavy approaches. Computer vision researchers have explored many applications to verify the visual accuracy of 3D model but the approaches to verify metric accuracy are few and no one is on Autodesk 123D Catch applied on Architectural Heritage Documentation. Our approach to this challenging problem is to compare the 3Dmodels by Autodesk 123D Catch and 3D models by terrestrial LIDAR considering different object size, from the detail (capitals, moldings, bases) to large scale buildings for practitioner purpose.

Simplification of Visual Rendering in Simulated Prosthetic Vision Facilitates Navigation.

PubMed

Vergnieux, Victor; Macé, Marc J-M; Jouffrais, Christophe

2017-09-01

Visual neuroprostheses are still limited and simulated prosthetic vision (SPV) is used to evaluate potential and forthcoming functionality of these implants. SPV has been used to evaluate the minimum requirement on visual neuroprosthetic characteristics to restore various functions such as reading, objects and face recognition, object grasping, etc. Some of these studies focused on obstacle avoidance but only a few investigated orientation or navigation abilities with prosthetic vision. The resolution of current arrays of electrodes is not sufficient to allow navigation tasks without additional processing of the visual input. In this study, we simulated a low resolution array (15 × 18 electrodes, similar to a forthcoming generation of arrays) and evaluated the navigation abilities restored when visual information was processed with various computer vision algorithms to enhance the visual rendering. Three main visual rendering strategies were compared to a control rendering in a wayfinding task within an unknown environment. The control rendering corresponded to a resizing of the original image onto the electrode array size, according to the average brightness of the pixels. In the first rendering strategy, vision distance was limited to 3, 6, or 9 m, respectively. In the second strategy, the rendering was not based on the brightness of the image pixels, but on the distance between the user and the elements in the field of view. In the last rendering strategy, only the edges of the environments were displayed, similar to a wireframe rendering. All the tested renderings, except the 3 m limitation of the viewing distance, improved navigation performance and decreased cognitive load. Interestingly, the distance-based and wireframe renderings also improved the cognitive mapping of the unknown environment. These results show that low resolution implants are usable for wayfinding if specific computer vision algorithms are used to select and display appropriate information regarding the environment. © 2017 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Task-oriented situation recognition

NASA Astrophysics Data System (ADS)

Bauer, Alexander; Fischer, Yvonne

2010-04-01

From the advances in computer vision methods for the detection, tracking and recognition of objects in video streams, new opportunities for video surveillance arise: In the future, automated video surveillance systems will be able to detect critical situations early enough to enable an operator to take preventive actions, instead of using video material merely for forensic investigations. However, problems such as limited computational resources, privacy regulations and a constant change in potential threads have to be addressed by a practical automated video surveillance system. In this paper, we show how these problems can be addressed using a task-oriented approach. The system architecture of the task-oriented video surveillance system NEST and an algorithm for the detection of abnormal behavior as part of the system are presented and illustrated for the surveillance of guests inside a video-monitored building.

A Computational Model of Active Vision for Visual Search in Human-Computer Interaction

DTIC Science & Technology

2010-08-01

processors that interact with the production rules to produce behavior, and (c) parameters that constrain the behavior of the model (e.g., the...velocity of a saccadic eye movement). While the parameters can be task-specific, the majority of the parameters are usually fixed across a wide variety...previously estimated durations. Hooge and Erkelens (1996) review these four explanations of fixation duration control. A variety of research

Neurally and Ocularly Informed Graph-Based Models for Searching 3D Environments

DTIC Science & Technology

2014-06-03

hBCI = hybrid brain–computer interface, TAG = transductive annotation by graph, CV = computer vision, TSP = traveling salesman problem . are navigated...environment that are most likely to contain objects that the subject would like to visit. 2.9. Route planning A traveling salesman problem (TSP) solver...fixations in a visual search task using fixation-related potentials J. Vis. 13 Croes G 1958 A method for solving traveling - salesman problems Oper. Res

Fitts' Law in the Control of Isometric Grip Force With Naturalistic Targets.

PubMed

Thumser, Zachary C; Slifkin, Andrew B; Beckler, Dylan T; Marasco, Paul D

2018-01-01

Fitts' law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts' law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts' law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts' law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts' law (average r 2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts' law for explicit targets with vision ( r 2 = 0.96) and implicit targets ( r 2 = 0.89), but not as well-described for explicit targets without vision ( r 2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts' law to quantify the relative speed-accuracy relationship of any given grasper.

Human-Machine Cooperation in Large-Scale Multimedia Retrieval: A Survey

ERIC Educational Resources Information Center

Shirahama, Kimiaki; Grzegorzek, Marcin; Indurkhya, Bipin

2015-01-01

"Large-Scale Multimedia Retrieval" (LSMR) is the task to fast analyze a large amount of multimedia data like images or videos and accurately find the ones relevant to a certain semantic meaning. Although LSMR has been investigated for more than two decades in the fields of multimedia processing and computer vision, a more…

Computer vision for driver assistance systems

NASA Astrophysics Data System (ADS)

Handmann, Uwe; Kalinke, Thomas; Tzomakas, Christos; Werner, Martin; von Seelen, Werner

1998-07-01

Systems for automated image analysis are useful for a variety of tasks and their importance is still increasing due to technological advances and an increase of social acceptance. Especially in the field of driver assistance systems the progress in science has reached a level of high performance. Fully or partly autonomously guided vehicles, particularly for road-based traffic, pose high demands on the development of reliable algorithms due to the conditions imposed by natural environments. At the Institut fur Neuroinformatik, methods for analyzing driving relevant scenes by computer vision are developed in cooperation with several partners from the automobile industry. We introduce a system which extracts the important information from an image taken by a CCD camera installed at the rear view mirror in a car. The approach consists of a sequential and a parallel sensor and information processing. Three main tasks namely the initial segmentation (object detection), the object tracking and the object classification are realized by integration in the sequential branch and by fusion in the parallel branch. The main gain of this approach is given by the integrative coupling of different algorithms providing partly redundant information.

Machine Vision For Industrial Control:The Unsung Opportunity

NASA Astrophysics Data System (ADS)

Falkman, Gerald A.; Murray, Lawrence A.; Cooper, James E.

1984-05-01

Vision modules have primarily been developed to relieve those pressures newly brought into existence by Inspection (QUALITY) and Robotic (PRODUCTIVITY) mandates. Industrial Control pressure stems on the other hand from the older first industrial revolution mandate of throughput. Satisfying such pressure calls for speed in both imaging and decision making. Vision companies have, however, put speed on a backburner or ignore it entirely because most modules are computer/software based which limits their speed potential. Increasingly, the keynote being struck at machine vision seminars is that "Visual and Computational Speed Must Be Increased and Dramatically!" There are modular hardwired-logic systems that are fast but, all too often, they are not very bright. Such units: Measure the fill factor of bottles as they spin by, Read labels on cans, Count stacked plastic cups or Monitor the width of parts streaming past the camera. Many are only a bit more complex than a photodetector. Once in place, most of these units are incapable of simple upgrading to a new task and are Vision's analog to the robot industry's pick and place (RIA TYPE E) robot. Vision thus finds itself amidst the same quandries that once beset the Robot Industry of America when it tried to define a robot, excluded dumb ones, and was left with only slow machines whose unit volume potential is shatteringly low. This paper develops an approach to meeting the need of a vision system that cuts a swath into the terra incognita of intelligent, high-speed vision processing. Main attention is directed to vision for industrial control. Some presently untapped vision application areas that will be serviced include: Electronics, Food, Sports, Pharmaceuticals, Machine Tools and Arc Welding.

USC orthogonal multiprocessor for image processing with neural networks

NASA Astrophysics Data System (ADS)

Hwang, Kai; Panda, Dhabaleswar K.; Haddadi, Navid

1990-07-01

This paper presents the architectural features and imaging applications of the Orthogonal MultiProcessor (OMP) system, which is under construction at the University of Southern California with research funding from NSF and assistance from several industrial partners. The prototype OMP is being built with 16 Intel i860 RISC microprocessors and 256 parallel memory modules using custom-designed spanning buses, which are 2-D interleaved and orthogonally accessed without conflicts. The 16-processor OMP prototype is targeted to achieve 430 MIPS and 600 Mflops, which have been verified by simulation experiments based on the design parameters used. The prototype OMP machine will be initially applied for image processing, computer vision, and neural network simulation applications. We summarize important vision and imaging algorithms that can be restructured with neural network models. These algorithms can efficiently run on the OMP hardware with linear speedup. The ultimate goal is to develop a high-performance Visual Computer (Viscom) for integrated low- and high-level image processing and vision tasks.

Vision-guided gripping of a cylinder

NASA Technical Reports Server (NTRS)

Nicewarner, Keith E.; Kelley, Robert B.

1991-01-01

The motivation for vision-guided servoing is taken from tasks in automated or telerobotic space assembly and construction. Vision-guided servoing requires the ability to perform rapid pose estimates and provide predictive feature tracking. Monocular information from a gripper-mounted camera is used to servo the gripper to grasp a cylinder. The procedure is divided into recognition and servo phases. The recognition stage verifies the presence of a cylinder in the camera field of view. Then an initial pose estimate is computed and uncluttered scan regions are selected. The servo phase processes only the selected scan regions of the image. Given the knowledge, from the recognition phase, that there is a cylinder in the image and knowing the radius of the cylinder, 4 of the 6 pose parameters can be estimated with minimal computation. The relative motion of the cylinder is obtained by using the current pose and prior pose estimates. The motion information is then used to generate a predictive feature-based trajectory for the path of the gripper.

An Omnidirectional Vision Sensor Based on a Spherical Mirror Catadioptric System.

PubMed

Barone, Sandro; Carulli, Marina; Neri, Paolo; Paoli, Alessandro; Razionale, Armando Viviano

2018-01-31

The combination of mirrors and lenses, which defines a catadioptric sensor, is widely used in the computer vision field. The definition of a catadioptric sensors is based on three main features: hardware setup, projection modelling and calibration process. In this paper, a complete description of these aspects is given for an omnidirectional sensor based on a spherical mirror. The projection model of a catadioptric system can be described by the forward projection task (FP, from 3D scene point to 2D pixel coordinates) and backward projection task (BP, from 2D coordinates to 3D direction of the incident light). The forward projection of non-central catadioptric vision systems, typically obtained by using curved mirrors, is usually modelled by using a central approximation and/or by adopting iterative approaches. In this paper, an analytical closed-form solution to compute both forward and backward projection for a non-central catadioptric system with a spherical mirror is presented. In particular, the forward projection is reduced to a 4th order polynomial by determining the reflection point on the mirror surface through the intersection between a sphere and an ellipse. A matrix format of the implemented models, suitable for fast point clouds handling, is also described. A robust calibration procedure is also proposed and applied to calibrate a catadioptric sensor by determining the mirror radius and center with respect to the camera.

An Omnidirectional Vision Sensor Based on a Spherical Mirror Catadioptric System

PubMed Central

Barone, Sandro; Carulli, Marina; Razionale, Armando Viviano

2018-01-01

The combination of mirrors and lenses, which defines a catadioptric sensor, is widely used in the computer vision field. The definition of a catadioptric sensors is based on three main features: hardware setup, projection modelling and calibration process. In this paper, a complete description of these aspects is given for an omnidirectional sensor based on a spherical mirror. The projection model of a catadioptric system can be described by the forward projection task (FP, from 3D scene point to 2D pixel coordinates) and backward projection task (BP, from 2D coordinates to 3D direction of the incident light). The forward projection of non-central catadioptric vision systems, typically obtained by using curved mirrors, is usually modelled by using a central approximation and/or by adopting iterative approaches. In this paper, an analytical closed-form solution to compute both forward and backward projection for a non-central catadioptric system with a spherical mirror is presented. In particular, the forward projection is reduced to a 4th order polynomial by determining the reflection point on the mirror surface through the intersection between a sphere and an ellipse. A matrix format of the implemented models, suitable for fast point clouds handling, is also described. A robust calibration procedure is also proposed and applied to calibrate a catadioptric sensor by determining the mirror radius and center with respect to the camera. PMID:29385051

Parallel implementation and evaluation of motion estimation system algorithms on a distributed memory multiprocessor using knowledge based mappings

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi; Leung, Mun K.; Huang, Thomas S.; Patel, Janak H.

1989-01-01

Several techniques to perform static and dynamic load balancing techniques for vision systems are presented. These techniques are novel in the sense that they capture the computational requirements of a task by examining the data when it is produced. Furthermore, they can be applied to many vision systems because many algorithms in different systems are either the same, or have similar computational characteristics. These techniques are evaluated by applying them on a parallel implementation of the algorithms in a motion estimation system on a hypercube multiprocessor system. The motion estimation system consists of the following steps: (1) extraction of features; (2) stereo match of images in one time instant; (3) time match of images from different time instants; (4) stereo match to compute final unambiguous points; and (5) computation of motion parameters. It is shown that the performance gains when these data decomposition and load balancing techniques are used are significant and the overhead of using these techniques is minimal.

Vision function testing for a suprachoroidal retinal prosthesis: effects of image filtering

NASA Astrophysics Data System (ADS)

Barnes, Nick; Scott, Adele F.; Lieby, Paulette; Petoe, Matthew A.; McCarthy, Chris; Stacey, Ashley; Ayton, Lauren N.; Sinclair, Nicholas C.; Shivdasani, Mohit N.; Lovell, Nigel H.; McDermott, Hugh J.; Walker, Janine G.; BVA Consortium,the

2016-06-01

Objective. One strategy to improve the effectiveness of prosthetic vision devices is to process incoming images to ensure that key information can be perceived by the user. This paper presents the first comprehensive results of vision function testing for a suprachoroidal retinal prosthetic device utilizing of 20 stimulating electrodes. Further, we investigate whether using image filtering can improve results on a light localization task for implanted participants compared to minimal vision processing. No controlled implanted participant studies have yet investigated whether vision processing methods that are not task-specific can lead to improved results. Approach. Three participants with profound vision loss from retinitis pigmentosa were implanted with a suprachoroidal retinal prosthesis. All three completed multiple trials of a light localization test, and one participant completed multiple trials of acuity tests. The visual representations used were: Lanczos2 (a high quality Nyquist bandlimited downsampling filter); minimal vision processing (MVP); wide view regional averaging filtering (WV); scrambled; and, system off. Main results. Using Lanczos2, all three participants successfully completed a light localization task and obtained a significantly higher percentage of correct responses than using MVP (p≤slant 0.025) or with system off (p\\lt 0.0001). Further, in a preliminary result using Lanczos2, one participant successfully completed grating acuity and Landolt C tasks, and showed significantly better performance (p=0.004) compared to WV, scrambled and system off on the grating acuity task. Significance. Participants successfully completed vision tasks using a 20 electrode suprachoroidal retinal prosthesis. Vision processing with a Nyquist bandlimited image filter has shown an advantage for a light localization task. This result suggests that this and targeted, more advanced vision processing schemes may become important components of retinal prostheses to enhance performance. ClinicalTrials.gov Identifier: NCT01603576.

Multi-task learning with group information for human action recognition

NASA Astrophysics Data System (ADS)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

Effects of the removal of vision on body sway during different postures in elite gymnasts.

PubMed

Asseman, F; Caron, O; Crémieux, J

2005-03-01

The aim of this study was to analyse the effects of the removal of vision on postural performance and postural control in function of the difficulty and specificity of the posture. Twelve elite gymnasts were instructed to be as stable as possible with eyes open and eyes closed in three postures: bipedal, unipedal, and handstand ranked from the less difficult and less specific to the more difficult and more specific. The ratios eyes closed on eyes open, computed on CP surface and CP mean velocity, which respectively represents postural performance and postural control, were similar in the bipedal and handstand postures. They were highly increased in the unipedal one. The effect of the removal of vision and so the role of vision on body sway was not directly linked to the difficulty or specificity of the posture; other tasks' characteristics like the segments configuration also played a role.

Implementing An Image Understanding System Architecture Using Pipe

NASA Astrophysics Data System (ADS)

Luck, Randall L.

1988-03-01

This paper will describe PIPE and how it can be used to implement an image understanding system. Image understanding is the process of developing a description of an image in order to make decisions about its contents. The tasks of image understanding are generally split into low level vision and high level vision. Low level vision is performed by PIPE -a high performance parallel processor with an architecture specifically designed for processing video images at up to 60 fields per second. High level vision is performed by one of several types of serial or parallel computers - depending on the application. An additional processor called ISMAP performs the conversion from iconic image space to symbolic feature space. ISMAP plugs into one of PIPE's slots and is memory mapped into the high level processor. Thus it forms the high speed link between the low and high level vision processors. The mechanisms for bottom-up, data driven processing and top-down, model driven processing are discussed.

Computer and internet use by ophthalmologists and trainees in an academic centre.

PubMed

Somal, Kirandeep; Lam, Wai-Ching; Tam, Eric

2009-06-01

The purpose of this study was to determine computer, internet, and department web site use by members of the Department of Ophthalmology and Vision Sciences at the University of Toronto in Toronto, Ont. Cross-sectional analysis. Eighty-eight members of the Department of Ophthalmology and Vision Sciences who responded to a survey. One hundred forty-eight department members (93 staff, 24 residents, and 31 fellows) were invited via e-mail to complete an online survey looking at computer and internet use. Participation was voluntary. Individuals who did not fill in an online response were sent a paper copy of the survey. No identifying fields were used in the data analysis. A response rate of 59% (88/148) was obtained. Fifty-nine percent of respondents described their computer skill as "good" or better; 86.4% utilized a computer in their clinical practice. Performance of computer-related tasks included accessing e-mail (98.9%), accessing medical literature (87.5%), conducting personal affairs (83%), and accessing conference/round schedules (65.9%). The survey indicated that 89.1% of respondents accessed peer-reviewed material online, including eMedicine (60.2%) and UpToDate articles (48.9%). Thirty-three percent of department members reported never having visited the department web site. Impediments to web site use included information not up to date (27.3%), information not of interest (22.1%), and difficulty locating the web site (20.8%). The majority of ophthalmologists and trainees in an academic centre utilize computer and internet resources for various tasks. A weak linear correlation was found between lower age of respondent and higher self-evaluated experience with computers (r = -0.43). Although use of the current department web site was low, respondents were interested in seeing improvements to the web site to increase its utility.

Task-specific image partitioning.

PubMed

Kim, Sungwoong; Nowozin, Sebastian; Kohli, Pushmeet; Yoo, Chang D

2013-02-01

Image partitioning is an important preprocessing step for many of the state-of-the-art algorithms used for performing high-level computer vision tasks. Typically, partitioning is conducted without regard to the task in hand. We propose a task-specific image partitioning framework to produce a region-based image representation that will lead to a higher task performance than that reached using any task-oblivious partitioning framework and existing supervised partitioning framework, albeit few in number. The proposed method partitions the image by means of correlation clustering, maximizing a linear discriminant function defined over a superpixel graph. The parameters of the discriminant function that define task-specific similarity/dissimilarity among superpixels are estimated based on structured support vector machine (S-SVM) using task-specific training data. The S-SVM learning leads to a better generalization ability while the construction of the superpixel graph used to define the discriminant function allows a rich set of features to be incorporated to improve discriminability and robustness. We evaluate the learned task-aware partitioning algorithms on three benchmark datasets. Results show that task-aware partitioning leads to better labeling performance than the partitioning computed by the state-of-the-art general-purpose and supervised partitioning algorithms. We believe that the task-specific image partitioning paradigm is widely applicable to improving performance in high-level image understanding tasks.

The effects of induced oblique astigmatism on symptoms and reading performance while viewing a computer screen.

PubMed

Rosenfield, Mark; Hue, Jennifer E; Huang, Rae R; Bababekova, Yuliya

2012-03-01

Computer vision syndrome (CVS) is a complex of eye and vision problems related to computer use which has been reported in up to 90% of computer users. Ocular symptoms may include asthenopia, accommodative and vergence difficulties and dry eye. Previous studies have reported that uncorrected astigmatism may have a significant impact on symptoms of CVS. However, its effect on task performance is unclear. This study recorded symptoms after a 10 min period of reading from a computer monitor either through the habitual distance refractive correction or with a supplementary -1.00 or -2.00D oblique cylinder added over these lenses in 12 young, visually-normal subjects. Additionally, the distance correction condition was repeated to assess the repeatability of the symptom questionnaire. Subjects' reading speed and accuracy were monitored during the course of the 10 min trial. There was no significant difference in reading rate or the number of errors between the three astigmatic conditions. However, a significant change in symptoms was reported with the median total symptom scores for the 0, 1 and 2D astigmatic conditions being 2.0, 6.5 and 40.0, respectively (p < 0.0001). Further, the repeatability coefficient of the total symptom score following the repeated zero astigmatism condition was ± 13.46. The presence of induced astigmatism produced a significant increase in post-task symptoms but did not affect reading rate or the number of reading errors. The correction of small astigmatic refractive errors may be important in optimizing patient comfort during computer operation. Ophthalmic & Physiological Optics © 2011 The College of Optometrists.

The reliability of a VISION COACH task as a measure of psychomotor skills.

PubMed

Xi, Yubin; Rosopa, Patrick J; Mossey, Mary; Crisler, Matthew C; Drouin, Nathalie; Kopera, Kevin; Brooks, Johnell O

2014-10-01

The VISION COACH™ interactive light board is designed to test and enhance participants' psychomotor skills. The primary goal of this study was to examine the test-retest reliability of the Full Field 120 VISION COACH task. One hundred eleven male and 131 female adult participants completed six trials where they responded to 120 randomly distributed lights displayed on the VISION COACH interactive light board. The mean time required for a participant to complete a trial was 101 seconds. Intraclass correlation coefficients, ranging from 0.962 to 0.987 suggest the VISION COACH Full Field 120 task was a reliable task. Cohen's d's of adjacent pairs of trials suggest learning effects did not negatively affect reliability after the third trial.

Impact of Gamification of Vision Tests on the User Experience.

PubMed

Bodduluri, Lakshmi; Boon, Mei Ying; Ryan, Malcolm; Dain, Stephen J

2017-08-01

Gamification has been incorporated into vision tests and vision therapies in the expectation that it may increase the user experience and engagement with the task. The current study aimed to understand how gamification affects the user experience, specifically during the undertaking of psychophysical tasks designed to estimate vision thresholds (chromatic and achromatic contrast sensitivity). Three tablet computer-based games were developed with three levels of gaming elements. Game 1 was designed to be a simple clinical test (no gaming elements), game 2 was similar to game 1 but with added gaming elements (i.e., feedback, scores, and sounds), and game 3 was a complete game. Participants (N = 144, age: 9.9-42 years) played three games in random order. The user experience for each game was assessed using a Short Feedback Questionnaire. The median (interquartile range) fun level for the three games was 2.5 (1.6), 3.9 (1.7), and 2.5 (2.8), respectively. Overall, participants reported greater fun level and higher preparedness to play the game again for game 2 than games 1 and 3 (P < 0.05). There were significant positive correlations observed between fun level and preparedness to play the game again for all the games (p < 0.05). Engagement (assessed as completion rates) did not differ between the games. Gamified version (game 2) was preferred to the other two versions. Over the short term, the careful application of gaming elements to vision tests was found to increase the fun level of users, without affecting engagement with the vision test.

Simulated Prosthetic Vision: The Benefits of Computer-Based Object Recognition and Localization.

PubMed

Macé, Marc J-M; Guivarch, Valérian; Denis, Grégoire; Jouffrais, Christophe

2015-07-01

Clinical trials with blind patients implanted with a visual neuroprosthesis showed that even the simplest tasks were difficult to perform with the limited vision restored with current implants. Simulated prosthetic vision (SPV) is a powerful tool to investigate the putative functions of the upcoming generations of visual neuroprostheses. Recent studies based on SPV showed that several generations of implants will be required before usable vision is restored. However, none of these studies relied on advanced image processing. High-level image processing could significantly reduce the amount of information required to perform visual tasks and help restore visuomotor behaviors, even with current low-resolution implants. In this study, we simulated a prosthetic vision device based on object localization in the scene. We evaluated the usability of this device for object recognition, localization, and reaching. We showed that a very low number of electrodes (e.g., nine) are sufficient to restore visually guided reaching movements with fair timing (10 s) and high accuracy. In addition, performance, both in terms of accuracy and speed, was comparable with 9 and 100 electrodes. Extraction of high level information (object recognition and localization) from video images could drastically enhance the usability of current visual neuroprosthesis. We suggest that this method-that is, localization of targets of interest in the scene-may restore various visuomotor behaviors. This method could prove functional on current low-resolution implants. The main limitation resides in the reliability of the vision algorithms, which are improving rapidly. Copyright © 2015 International Center for Artificial Organs and Transplantation and Wiley Periodicals, Inc.

Humans and Deep Networks Largely Agree on Which Kinds of Variation Make Object Recognition Harder.

PubMed

Kheradpisheh, Saeed R; Ghodrati, Masoud; Ganjtabesh, Mohammad; Masquelier, Timothée

2016-01-01

View-invariant object recognition is a challenging problem that has attracted much attention among the psychology, neuroscience, and computer vision communities. Humans are notoriously good at it, even if some variations are presumably more difficult to handle than others (e.g., 3D rotations). Humans are thought to solve the problem through hierarchical processing along the ventral stream, which progressively extracts more and more invariant visual features. This feed-forward architecture has inspired a new generation of bio-inspired computer vision systems called deep convolutional neural networks (DCNN), which are currently the best models for object recognition in natural images. Here, for the first time, we systematically compared human feed-forward vision and DCNNs at view-invariant object recognition task using the same set of images and controlling the kinds of transformation (position, scale, rotation in plane, and rotation in depth) as well as their magnitude, which we call "variation level." We used four object categories: car, ship, motorcycle, and animal. In total, 89 human subjects participated in 10 experiments in which they had to discriminate between two or four categories after rapid presentation with backward masking. We also tested two recent DCNNs (proposed respectively by Hinton's group and Zisserman's group) on the same tasks. We found that humans and DCNNs largely agreed on the relative difficulties of each kind of variation: rotation in depth is by far the hardest transformation to handle, followed by scale, then rotation in plane, and finally position (much easier). This suggests that DCNNs would be reasonable models of human feed-forward vision. In addition, our results show that the variation levels in rotation in depth and scale strongly modulate both humans' and DCNNs' recognition performances. We thus argue that these variations should be controlled in the image datasets used in vision research.

What Aspects of Vision Facilitate Haptic Processing?

ERIC Educational Resources Information Center

Millar, Susanna; Al-Attar, Zainab

2005-01-01

We investigate how vision affects haptic performance when task-relevant visual cues are reduced or excluded. The task was to remember the spatial location of six landmarks that were explored by touch in a tactile map. Here, we use specially designed spectacles that simulate residual peripheral vision, tunnel vision, diffuse light perception, and…

Deep learning in the small sample size setting: cascaded feed forward neural networks for medical image segmentation

NASA Astrophysics Data System (ADS)

Gaonkar, Bilwaj; Hovda, David; Martin, Neil; Macyszyn, Luke

2016-03-01

Deep Learning, refers to large set of neural network based algorithms, have emerged as promising machine- learning tools in the general imaging and computer vision domains. Convolutional neural networks (CNNs), a specific class of deep learning algorithms, have been extremely effective in object recognition and localization in natural images. A characteristic feature of CNNs, is the use of a locally connected multi layer topology that is inspired by the animal visual cortex (the most powerful vision system in existence). While CNNs, perform admirably in object identification and localization tasks, typically require training on extremely large datasets. Unfortunately, in medical image analysis, large datasets are either unavailable or are extremely expensive to obtain. Further, the primary tasks in medical imaging are organ identification and segmentation from 3D scans, which are different from the standard computer vision tasks of object recognition. Thus, in order to translate the advantages of deep learning to medical image analysis, there is a need to develop deep network topologies and training methodologies, that are geared towards medical imaging related tasks and can work in a setting where dataset sizes are relatively small. In this paper, we present a technique for stacked supervised training of deep feed forward neural networks for segmenting organs from medical scans. Each `neural network layer' in the stack is trained to identify a sub region of the original image, that contains the organ of interest. By layering several such stacks together a very deep neural network is constructed. Such a network can be used to identify extremely small regions of interest in extremely large images, inspite of a lack of clear contrast in the signal or easily identifiable shape characteristics. What is even more intriguing is that the network stack achieves accurate segmentation even when it is trained on a single image with manually labelled ground truth. We validate this approach,using a publicly available head and neck CT dataset. We also show that a deep neural network of similar depth, if trained directly using backpropagation, cannot acheive the tasks achieved using our layer wise training paradigm.

Productivity associated with visual status of computer users.

PubMed

Daum, Kent M; Clore, Katherine A; Simms, Suzanne S; Vesely, Jon W; Wilczek, Dawn D; Spittle, Brian M; Good, Greg W

2004-01-01

The aim of this project is to examine the potential connection between the astigmatic refractive corrections of subjects using computers and their productivity and comfort. We hypothesize that improving the visual status of subjects using computers results in greater productivity, as well as improved visual comfort. Inclusion criteria required subjects 19 to 30 years of age with complete vision examinations before being enrolled. Using a double-masked, placebo-controlled, randomized design, subjects completed three experimental tasks calculated to assess the effects of refractive error on productivity (time to completion and the number of errors) at a computer. The tasks resembled those commonly undertaken by computer users and involved visual search tasks of: (1) counties and populations; (2) nonsense word search; and (3) a modified text-editing task. Estimates of productivity for time to completion varied from a minimum of 2.5% upwards to 28.7% with 2 D cylinder miscorrection. Assuming a conservative estimate of an overall 2.5% increase in productivity with appropriate astigmatic refractive correction, our data suggest a favorable cost-benefit ratio of at least 2.3 for the visual correction of an employee (total cost 268 dollars) with a salary of 25,000 dollars per year. We conclude that astigmatic refractive error affected both productivity and visual comfort under the conditions of this experiment. These data also suggest a favorable cost-benefit ratio for employers who provide computer-specific eyewear to their employees.

Demonstration of a Semi-Autonomous Hybrid Brain-Machine Interface using Human Intracranial EEG, Eye Tracking, and Computer Vision to Control a Robotic Upper Limb Prosthetic

PubMed Central

McMullen, David P.; Hotson, Guy; Katyal, Kapil D.; Wester, Brock A.; Fifer, Matthew S.; McGee, Timothy G.; Harris, Andrew; Johannes, Matthew S.; Vogelstein, R. Jacob; Ravitz, Alan D.; Anderson, William S.; Thakor, Nitish V.; Crone, Nathan E.

2014-01-01

To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 seconds for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs. PMID:24760914

Demonstration of a semi-autonomous hybrid brain-machine interface using human intracranial EEG, eye tracking, and computer vision to control a robotic upper limb prosthetic.

PubMed

McMullen, David P; Hotson, Guy; Katyal, Kapil D; Wester, Brock A; Fifer, Matthew S; McGee, Timothy G; Harris, Andrew; Johannes, Matthew S; Vogelstein, R Jacob; Ravitz, Alan D; Anderson, William S; Thakor, Nitish V; Crone, Nathan E

2014-07-01

To increase the ability of brain-machine interfaces (BMIs) to control advanced prostheses such as the modular prosthetic limb (MPL), we are developing a novel system: the Hybrid Augmented Reality Multimodal Operation Neural Integration Environment (HARMONIE). This system utilizes hybrid input, supervisory control, and intelligent robotics to allow users to identify an object (via eye tracking and computer vision) and initiate (via brain-control) a semi-autonomous reach-grasp-and-drop of the object by the MPL. Sequential iterations of HARMONIE were tested in two pilot subjects implanted with electrocorticographic (ECoG) and depth electrodes within motor areas. The subjects performed the complex task in 71.4% (20/28) and 67.7% (21/31) of trials after minimal training. Balanced accuracy for detecting movements was 91.1% and 92.9%, significantly greater than chance accuracies (p < 0.05). After BMI-based initiation, the MPL completed the entire task 100% (one object) and 70% (three objects) of the time. The MPL took approximately 12.2 s for task completion after system improvements implemented for the second subject. Our hybrid-BMI design prevented all but one baseline false positive from initiating the system. The novel approach demonstrated in this proof-of-principle study, using hybrid input, supervisory control, and intelligent robotics, addresses limitations of current BMIs.

Computer Vision Techniques for Transcatheter Intervention

PubMed Central

Zhao, Feng; Roach, Matthew

2015-01-01

Minimally invasive transcatheter technologies have demonstrated substantial promise for the diagnosis and the treatment of cardiovascular diseases. For example, transcatheter aortic valve implantation is an alternative to aortic valve replacement for the treatment of severe aortic stenosis, and transcatheter atrial fibrillation ablation is widely used for the treatment and the cure of atrial fibrillation. In addition, catheter-based intravascular ultrasound and optical coherence tomography imaging of coronary arteries provides important information about the coronary lumen, wall, and plaque characteristics. Qualitative and quantitative analysis of these cross-sectional image data will be beneficial to the evaluation and the treatment of coronary artery diseases such as atherosclerosis. In all the phases (preoperative, intraoperative, and postoperative) during the transcatheter intervention procedure, computer vision techniques (e.g., image segmentation and motion tracking) have been largely applied in the field to accomplish tasks like annulus measurement, valve selection, catheter placement control, and vessel centerline extraction. This provides beneficial guidance for the clinicians in surgical planning, disease diagnosis, and treatment assessment. In this paper, we present a systematical review on these state-of-the-art methods. We aim to give a comprehensive overview for researchers in the area of computer vision on the subject of transcatheter intervention. Research in medical computing is multi-disciplinary due to its nature, and hence, it is important to understand the application domain, clinical background, and imaging modality, so that methods and quantitative measurements derived from analyzing the imaging data are appropriate and meaningful. We thus provide an overview on the background information of the transcatheter intervention procedures, as well as a review of the computer vision techniques and methodologies applied in this area. PMID:27170893

Developing a Very Low Vision Orientation and Mobility Test Battery (O&M-VLV).

PubMed

Finger, Robert P; Ayton, Lauren N; Deverell, Lil; O'Hare, Fleur; McSweeney, Shane C; Luu, Chi D; Fenwick, Eva K; Keeffe, Jill E; Guymer, Robyn H; Bentley, Sharon A

2016-09-01

This study aimed to determine the feasibility of an assessment of vision-related orientation and mobility (O&M) tasks in persons with severe vision loss. These tasks may be used for future low vision rehabilitation clinical assessments or as outcome measures in vision restoration trials. Forty legally blind persons (mean visual acuity logMAR 2.3, or hand movements) with advanced retinitis pigmentosa participated in the Orientation & Mobility-Very Low Vision (O&M-VLV) subtests from the Low Vision Assessment of Daily Activities (LoVADA) protocol. Four categories of tasks were evaluated: route travel in three indoor hospital environments, a room orientation task (the "cafe"), a visual exploration task (the "gallery"), and a modified version of the Timed Up and Go (TUG) test, which assesses re-orientation and route travel. Spatial cognition was assessed using the Stuart Tactile Maps test. Visual acuity and visual fields were measured. A generalized linear regression model showed that a number of measures in the O&M-VLV tasks were related to residual visual function. The percentage of preferred walking speed without an aid on three travel routes was associated with visual field (p < 0.01 for all routes) whereas the number of contacts with obstacles during route travel was associated with acuity (p = 0.001). TUG-LV task time was associated with acuity (p = 0.003), as was the cafe time and distance traveled (p = 0.006 and p < 0.001, respectively). The gallery score was the only measure that was significantly associated with both residual acuity and fields (p < 0.001 and p = 0.001, respectively). The O&M-VLV was designed to capture key elements of O&M performance in persons with severe vision loss, which is a population not often studied previously. Performance on these tasks was associated with both binocular visual acuity and visual field. This new protocol includes assessments of orientation, which may be of benefit in vision restoration clinical trials.

Lingual electrotactile stimulation as an alternative sensory feedback pathway for brain-computer interface applications

NASA Astrophysics Data System (ADS)

Wilson, J. Adam; Walton, Léo M.; Tyler, Mitch; Williams, Justin

2012-08-01

This article describes a new method of providing feedback during a brain-computer interface movement task using a non-invasive, high-resolution electrotactile vision substitution system. We compared the accuracy and movement times during a center-out cursor movement task, and found that the task performance with tactile feedback was comparable to visual feedback for 11 participants. These subjects were able to modulate the chosen BCI EEG features during both feedback modalities, indicating that the type of feedback chosen does not matter provided that the task information is clearly conveyed through the chosen medium. In addition, we tested a blind subject with the tactile feedback system, and found that the training time, accuracy, and movement times were indistinguishable from results obtained from subjects using visual feedback. We believe that BCI systems with alternative feedback pathways should be explored, allowing individuals with severe motor disabilities and accompanying reduced visual and sensory capabilities to effectively use a BCI.

Practical color vision tests for air traffic control applicants: en route center and terminal facilities.

PubMed

Mertens, H W; Milburn, N J; Collins, W E

2000-12-01

Two practical color vision tests were developed and validated for use in screening Air Traffic Control Specialist (ATCS) applicants for work at en route center or terminal facilities. The development of the tests involved careful reproduction/simulation of color-coded materials from the most demanding, safety-critical color task performed in each type of facility. The tests were evaluated using 106 subjects with normal color vision and 85 with color vision deficiency. The en route center test, named the Flight Progress Strips Test (FPST), required the identification of critical red/black coding in computer printing and handwriting on flight progress strips. The terminal option test, named the Aviation Lights Test (ALT), simulated red/green/white aircraft lights that must be identified in night ATC tower operations. Color-coding is a non-redundant source of safety-critical information in both tasks. The FPST was validated by direct comparison of responses to strip reproductions with responses to the original flight progress strips and a set of strips selected independently. Validity was high; Kappa = 0.91 with original strips as the validation criterion and 0.86 with different strips. The light point stimuli of the ALT were validated physically with a spectroradiometer. The reliabilities of the FPST and ALT were estimated with Chronbach's alpha as 0.93 and 0.98, respectively. The high job-relevance, validity, and reliability of these tests increases the effectiveness and fairness of ATCS color vision testing.

The Impact of a Sports Vision Training Program in Youth Field Hockey Players

PubMed Central

Schwab, Sebastian; Memmert, Daniel

2012-01-01

The aim of this study was to investigate whether a sports vision training program improves the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training. The choice reaction time task at the D2 board (Learning Task I), the functional field of view task (Learning Task II) and the multiple object tracking (MOT) task (Transfer Task) were assessed before and after the intervention and again six weeks after the second test. Analyzes showed significant differences between the two groups for the choice reaction time task at the D2 board and the functional field of view task, with significant improvements for the intervention group and none for the control group. For the transfer task, we could not find statistically significant improvements for either group. The results of this study are discussed in terms of theoretical and practical implications. Key pointsPerceptual training with youth field hockey playersCan a sports vision training program improve the visual performance of youth male field hockey players, ages 12 to 16 years, after an intervention of six weeks compared to a control group with no specific sports vision training?The intervention was performed in the “VisuLab” as DynamicEye® SportsVision Training at the German Sport University Cologne.We ran a series of 3 two-factor univariate analysis of variance (ANOVA) with repeated measures on both within subject independent variables (group; measuring point) to examine the effects on central perception, peripheral perception and choice reaction time.The present study shows an improvement of certain visual abilities with the help of the sports vision training program. PMID:24150071

Fitts’ Law in the Control of Isometric Grip Force With Naturalistic Targets

PubMed Central

Thumser, Zachary C.; Slifkin, Andrew B.; Beckler, Dylan T.; Marasco, Paul D.

2018-01-01

Fitts’ law models the relationship between amplitude, precision, and speed of rapid movements. It is widely used to quantify performance in pointing tasks, study human-computer interaction, and generally to understand perceptual-motor information processes, including research to model performance in isometric force production tasks. Applying Fitts’ law to an isometric grip force task would allow for quantifying grasp performance in rehabilitative medicine and may aid research on prosthetic control and design. We examined whether Fitts’ law would hold when participants attempted to accurately produce their intended force output while grasping a manipulandum when presented with images of various everyday objects (we termed this the implicit task). Although our main interest was the implicit task, to benchmark it and establish validity, we examined performance against a more standard visual feedback condition via a digital force-feedback meter on a video monitor (explicit task). Next, we progressed from visual force feedback with force meter targets to the same targets without visual force feedback (operating largely on feedforward control with tactile feedback). This provided an opportunity to see if Fitts’ law would hold without vision, and allowed us to progress toward the more naturalistic implicit task (which does not include visual feedback). Finally, we changed the nature of the targets from requiring explicit force values presented as arrows on a force-feedback meter (explicit targets) to the more naturalistic and intuitive target forces implied by images of objects (implicit targets). With visual force feedback the relation between task difficulty and the time to produce the target grip force was predicted by Fitts’ law (average r2 = 0.82). Without vision, average grip force scaled accurately although force variability was insensitive to the target presented. In contrast, images of everyday objects generated more reliable grip forces without the visualized force meter. In sum, population means were well-described by Fitts’ law for explicit targets with vision (r2 = 0.96) and implicit targets (r2 = 0.89), but not as well-described for explicit targets without vision (r2 = 0.54). Implicit targets should provide a realistic see-object-squeeze-object test using Fitts’ law to quantify the relative speed-accuracy relationship of any given grasper. PMID:29773999

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors.

PubMed

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-05-28

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms.

Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping.

PubMed

Downey, John E; Weiss, Jeffrey M; Muelling, Katharina; Venkatraman, Arun; Valois, Jean-Sebastien; Hebert, Martial; Bagnell, J Andrew; Schwartz, Andrew B; Collinger, Jennifer L

2016-03-18

Recent studies have shown that brain-machine interfaces (BMIs) offer great potential for restoring upper limb function. However, grasping objects is a complicated task and the signals extracted from the brain may not always be capable of driving these movements reliably. Vision-guided robotic assistance is one possible way to improve BMI performance. We describe a method of shared control where the user controls a prosthetic arm using a BMI and receives assistance with positioning the hand when it approaches an object. Two human subjects with tetraplegia used a robotic arm to complete object transport tasks with and without shared control. The shared control system was designed to provide a balance between BMI-derived intention and computer assistance. An autonomous robotic grasping system identified and tracked objects and defined stable grasp positions for these objects. The system identified when the user intended to interact with an object based on the BMI-controlled movements of the robotic arm. Using shared control, BMI controlled movements and autonomous grasping commands were blended to ensure secure grasps. Both subjects were more successful on object transfer tasks when using shared control compared to BMI control alone. Movements made using shared control were more accurate, more efficient, and less difficult. One participant attempted a task with multiple objects and successfully lifted one of two closely spaced objects in 92 % of trials, demonstrating the potential for users to accurately execute their intention while using shared control. Integration of BMI control with vision-guided robotic assistance led to improved performance on object transfer tasks. Providing assistance while maintaining generalizability will make BMI systems more attractive to potential users. NCT01364480 and NCT01894802 .

Computational imaging of light in flight

NASA Astrophysics Data System (ADS)

Hullin, Matthias B.

2014-10-01

Many computer vision tasks are hindered by image formation itself, a process that is governed by the so-called plenoptic integral. By averaging light falling into the lens over space, angle, wavelength and time, a great deal of information is irreversibly lost. The emerging idea of transient imaging operates on a time resolution fast enough to resolve non-stationary light distributions in real-world scenes. It enables the discrimination of light contributions by the optical path length from light source to receiver, a dimension unavailable in mainstream imaging to date. Until recently, such measurements used to require high-end optical equipment and could only be acquired under extremely restricted lab conditions. To address this challenge, we introduced a family of computational imaging techniques operating on standard time-of-flight image sensors, for the first time allowing the user to "film" light in flight in an affordable, practical and portable way. Just as impulse responses have proven a valuable tool in almost every branch of science and engineering, we expect light-in-flight analysis to impact a wide variety of applications in computer vision and beyond.

Spatial learning while navigating with severely degraded viewing: The role of attention and mobility monitoring

PubMed Central

Rand, Kristina M.; Creem-Regehr, Sarah H.; Thompson, William B.

2015-01-01

The ability to navigate without getting lost is an important aspect of quality of life. In five studies, we evaluated how spatial learning is affected by the increased demands of keeping oneself safe while walking with degraded vision (mobility monitoring). We proposed that safe low-vision mobility requires attentional resources, providing competition for those needed to learn a new environment. In Experiments 1 and 2 participants navigated along paths in a real-world indoor environment with simulated degraded vision or normal vision. Memory for object locations seen along the paths was better with normal compared to degraded vision. With degraded vision, memory was better when participants were guided by an experimenter (low monitoring demands) versus unguided (high monitoring demands). In Experiments 3 and 4, participants walked while performing an auditory task. Auditory task performance was superior with normal compared to degraded vision. With degraded vision, auditory task performance was better when guided compared to unguided. In Experiment 5, participants performed both the spatial learning and auditory tasks under degraded vision. Results showed that attention mediates the relationship between mobility-monitoring demands and spatial learning. These studies suggest that more attention is required and spatial learning is impaired when navigating with degraded viewing. PMID:25706766

Understanding and preventing computer vision syndrome.

PubMed

Loh, Ky; Redd, Sc

2008-01-01

The invention of computer and advancement in information technology has revolutionized and benefited the society but at the same time has caused symptoms related to its usage such as ocular sprain, irritation, redness, dryness, blurred vision and double vision. This cluster of symptoms is known as computer vision syndrome which is characterized by the visual symptoms which result from interaction with computer display or its environment. Three major mechanisms that lead to computer vision syndrome are extraocular mechanism, accommodative mechanism and ocular surface mechanism. The visual effects of the computer such as brightness, resolution, glare and quality all are known factors that contribute to computer vision syndrome. Prevention is the most important strategy in managing computer vision syndrome. Modification in the ergonomics of the working environment, patient education and proper eye care are crucial in managing computer vision syndrome.

Design of a surgical robot with dynamic vision field control for Single Port Endoscopic Surgery.

PubMed

Kobayashi, Yo; Sekiguchi, Yuta; Tomono, Yu; Watanabe, Hiroki; Toyoda, Kazutaka; Konishi, Kozo; Tomikawa, Morimasa; Ieiri, Satoshi; Tanoue, Kazuo; Hashizume, Makoto; Fujie, Masaktsu G

2010-01-01

Recently, a robotic system was developed to assist Single Port Endoscopic Surgery (SPS). However, the existing system required a manual change of vision field, hindering the surgical task and increasing the degrees of freedom (DOFs) of the manipulator. We proposed a surgical robot for SPS with dynamic vision field control, the endoscope view being manipulated by a master controller. The prototype robot consisted of a positioning and sheath manipulator (6 DOF) for vision field control, and dual tool tissue manipulators (gripping: 5DOF, cautery: 3DOF). Feasibility of the robot was demonstrated in vitro. The "cut and vision field control" (using tool manipulators) is suitable for precise cutting tasks in risky areas while a "cut by vision field control" (using a vision field control manipulator) is effective for rapid macro cutting of tissues. A resection task was accomplished using a combination of both methods.

Foreword to the theme issue on geospatial computer vision

NASA Astrophysics Data System (ADS)

Wegner, Jan Dirk; Tuia, Devis; Yang, Michael; Mallet, Clement

2018-06-01

Geospatial Computer Vision has become one of the most prevalent emerging fields of investigation in Earth Observation in the last few years. In this theme issue, we aim at showcasing a number of works at the interface between remote sensing, photogrammetry, image processing, computer vision and machine learning. In light of recent sensor developments - both from the ground as from above - an unprecedented (and ever growing) quantity of geospatial data is available for tackling challenging and urgent tasks such as environmental monitoring (deforestation, carbon sequestration, climate change mitigation), disaster management, autonomous driving or the monitoring of conflicts. The new bottleneck for serving these applications is the extraction of relevant information from such large amounts of multimodal data. This includes sources, stemming from multiple sensors, that exhibit distinct physical nature of heterogeneous quality, spatial, spectral and temporal resolutions. They are as diverse as multi-/hyperspectral satellite sensors, color cameras on drones, laser scanning devices, existing open land-cover geodatabases and social media. Such core data processing is mandatory so as to generate semantic land-cover maps, accurate detection and trajectories of objects of interest, as well as by-products of superior added-value: georeferenced data, images with enhanced geometric and radiometric qualities, or Digital Surface and Elevation Models.

Automated design of image operators that detect interest points.

PubMed

Trujillo, Leonardo; Olague, Gustavo

2008-01-01

This work describes how evolutionary computation can be used to synthesize low-level image operators that detect interesting points on digital images. Interest point detection is an essential part of many modern computer vision systems that solve tasks such as object recognition, stereo correspondence, and image indexing, to name but a few. The design of the specialized operators is posed as an optimization/search problem that is solved with genetic programming (GP), a strategy still mostly unexplored by the computer vision community. The proposed approach automatically synthesizes operators that are competitive with state-of-the-art designs, taking into account an operator's geometric stability and the global separability of detected points during fitness evaluation. The GP search space is defined using simple primitive operations that are commonly found in point detectors proposed by the vision community. The experiments described in this paper extend previous results (Trujillo and Olague, 2006a,b) by presenting 15 new operators that were synthesized through the GP-based search. Some of the synthesized operators can be regarded as improved manmade designs because they employ well-known image processing techniques and achieve highly competitive performance. On the other hand, since the GP search also generates what can be considered as unconventional operators for point detection, these results provide a new perspective to feature extraction research.

Manifold learning in machine vision and robotics

NASA Astrophysics Data System (ADS)

Bernstein, Alexander

2017-02-01

Smart algorithms are used in Machine vision and Robotics to organize or extract high-level information from the available data. Nowadays, Machine learning is an essential and ubiquitous tool to automate extraction patterns or regularities from data (images in Machine vision; camera, laser, and sonar sensors data in Robotics) in order to solve various subject-oriented tasks such as understanding and classification of images content, navigation of mobile autonomous robot in uncertain environments, robot manipulation in medical robotics and computer-assisted surgery, and other. Usually such data have high dimensionality, however, due to various dependencies between their components and constraints caused by physical reasons, all "feasible and usable data" occupy only a very small part in high dimensional "observation space" with smaller intrinsic dimensionality. Generally accepted model of such data is manifold model in accordance with which the data lie on or near an unknown manifold (surface) of lower dimensionality embedded in an ambient high dimensional observation space; real-world high-dimensional data obtained from "natural" sources meet, as a rule, this model. The use of Manifold learning technique in Machine vision and Robotics, which discovers a low-dimensional structure of high dimensional data and results in effective algorithms for solving of a large number of various subject-oriented tasks, is the content of the conference plenary speech some topics of which are in the paper.

Flexible Wing Base Micro Aerial Vehicles: Towards Flight Autonomy: Vision-Based Horizon Detection for Micro Air Vehicles

NASA Technical Reports Server (NTRS)

Nechyba, Michael C.; Ettinger, Scott M.; Ifju, Peter G.; Wazak, Martin

2002-01-01

Recently substantial progress has been made towards design building and testifying remotely piloted Micro Air Vehicles (MAVs). This progress in overcoming the aerodynamic obstacles to flight at very small scales has, unfortunately, not been matched by similar progress in autonomous MAV flight. Thus, we propose a robust, vision-based horizon detection algorithm as the first step towards autonomous MAVs. In this paper, we first motivate the use of computer vision for the horizon detection task by examining the flight of birds (biological MAVs) and considering other practical factors. We then describe our vision-based horizon detection algorithm, which has been demonstrated at 30 Hz with over 99.9% correct horizon identification, over terrain that includes roads, buildings large and small, meadows, wooded areas, and a lake. We conclude with some sample horizon detection results and preview a companion paper, where the work discussed here forms the core of a complete autonomous flight stability system.

Conscious Vision Proceeds from Global to Local Content in Goal-Directed Tasks and Spontaneous Vision.

PubMed

Campana, Florence; Rebollo, Ignacio; Urai, Anne; Wyart, Valentin; Tallon-Baudry, Catherine

2016-05-11

The reverse hierarchy theory (Hochstein and Ahissar, 2002) makes strong, but so far untested, predictions on conscious vision. In this theory, local details encoded in lower-order visual areas are unconsciously processed before being automatically and rapidly combined into global information in higher-order visual areas, where conscious percepts emerge. Contingent on current goals, local details can afterward be consciously retrieved. This model therefore predicts that (1) global information is perceived faster than local details, (2) global information is computed regardless of task demands during early visual processing, and (3) spontaneous vision is dominated by global percepts. We designed novel textured stimuli that are, as opposed to the classic Navon's letters, truly hierarchical (i.e., where global information is solely defined by local information but where local and global orientations can still be manipulated separately). In line with the predictions, observers were systematically faster reporting global than local properties of those stimuli. Second, global information could be decoded from magneto-encephalographic data during early visual processing regardless of task demands. Last, spontaneous subjective reports were dominated by global information and the frequency and speed of spontaneous global perception correlated with the accuracy and speed in the global task. No such correlation was observed for local information. We therefore show that information at different levels of the visual hierarchy is not equally likely to become conscious; rather, conscious percepts emerge preferentially at a global level. We further show that spontaneous reports can be reliable and are tightly linked to objective performance at the global level. Is information encoded at different levels of the visual system (local details in low-level areas vs global shapes in high-level areas) equally likely to become conscious? We designed new hierarchical stimuli and provide the first empirical evidence based on behavioral and MEG data that global information encoded at high levels of the visual hierarchy dominates perception. This result held both in the presence and in the absence of task demands. The preferential emergence of percepts at high levels can account for two properties of conscious vision, namely, the dominance of global percepts and the feeling of visual richness reported independently of the perception of local details. Copyright © 2016 the authors 0270-6474/16/365200-14$15.00/0.

Development of Moire machine vision

NASA Technical Reports Server (NTRS)

Harding, Kevin G.

1987-01-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

Modeling Images of Natural 3D Surfaces: Overview and Potential Applications

NASA Technical Reports Server (NTRS)

Jalobeanu, Andre; Kuehnel, Frank; Stutz, John

2004-01-01

Generative models of natural images have long been used in computer vision. However, since they only describe the of 2D scenes, they fail to capture all the properties of the underlying 3D world. Even though such models are sufficient for many vision tasks a 3D scene model is when it comes to inferring a 3D object or its characteristics. In this paper, we present such a generative model, incorporating both a multiscale surface prior model for surface geometry and reflectance, and an image formation process model based on realistic rendering, the computation of the posterior model parameter densities, and on the critical aspects of the rendering. We also how to efficiently invert the model within a Bayesian framework. We present a few potential applications, such as asteroid modeling and Planetary topography recovery, illustrated by promising results on real images.

Real-time Accurate Surface Reconstruction Pipeline for Vision Guided Planetary Exploration Using Unmanned Ground and Aerial Vehicles

NASA Technical Reports Server (NTRS)

Almeida, Eduardo DeBrito

2012-01-01

This report discusses work completed over the summer at the Jet Propulsion Laboratory (JPL), California Institute of Technology. A system is presented to guide ground or aerial unmanned robots using computer vision. The system performs accurate camera calibration, camera pose refinement and surface extraction from images collected by a camera mounted on the vehicle. The application motivating the research is planetary exploration and the vehicles are typically rovers or unmanned aerial vehicles. The information extracted from imagery is used primarily for navigation, as robot location is the same as the camera location and the surfaces represent the terrain that rovers traverse. The processed information must be very accurate and acquired very fast in order to be useful in practice. The main challenge being addressed by this project is to achieve high estimation accuracy and high computation speed simultaneously, a difficult task due to many technical reasons.

Development of Moire machine vision

NASA Astrophysics Data System (ADS)

Harding, Kevin G.

1987-10-01

Three dimensional perception is essential to the development of versatile robotics systems in order to handle complex manufacturing tasks in future factories and in providing high accuracy measurements needed in flexible manufacturing and quality control. A program is described which will develop the potential of Moire techniques to provide this capability in vision systems and automated measurements, and demonstrate artificial intelligence (AI) techniques to take advantage of the strengths of Moire sensing. Moire techniques provide a means of optically manipulating the complex visual data in a three dimensional scene into a form which can be easily and quickly analyzed by computers. This type of optical data manipulation provides high productivity through integrated automation, producing a high quality product while reducing computer and mechanical manipulation requirements and thereby the cost and time of production. This nondestructive evaluation is developed to be able to make full field range measurement and three dimensional scene analysis.

Real time AI expert system for robotic applications

NASA Technical Reports Server (NTRS)

Follin, John F.

1987-01-01

A computer controlled multi-robot process cell to demonstrate advanced technologies for the demilitarization of obsolete chemical munitions was developed. The methods through which the vision system and other sensory inputs were used by the artificial intelligence to provide the information required to direct the robots to complete the desired task are discussed. The mechanisms that the expert system uses to solve problems (goals), the different rule data base, and the methods for adapting this control system to any device that can be controlled or programmed through a high level computer interface are discussed.

A Visual Database System for Image Analysis on Parallel Computers and its Application to the EOS Amazon Project

NASA Technical Reports Server (NTRS)

Shapiro, Linda G.; Tanimoto, Steven L.; Ahrens, James P.

1996-01-01

The goal of this task was to create a design and prototype implementation of a database environment that is particular suited for handling the image, vision and scientific data associated with the NASA's EOC Amazon project. The focus was on a data model and query facilities that are designed to execute efficiently on parallel computers. A key feature of the environment is an interface which allows a scientist to specify high-level directives about how query execution should occur.

What aspects of vision facilitate haptic processing?

PubMed

Millar, Susanna; Al-Attar, Zainab

2005-12-01

We investigate how vision affects haptic performance when task-relevant visual cues are reduced or excluded. The task was to remember the spatial location of six landmarks that were explored by touch in a tactile map. Here, we use specially designed spectacles that simulate residual peripheral vision, tunnel vision, diffuse light perception, and total blindness. Results for target locations differed, suggesting additional effects from adjacent touch cues. These are discussed. Touch with full vision was most accurate, as expected. Peripheral and tunnel vision, which reduce visuo-spatial cues, differed in error pattern. Both were less accurate than full vision, and significantly more accurate than touch with diffuse light perception, and touch alone. The important finding was that touch with diffuse light perception, which excludes spatial cues, did not differ from touch without vision in performance accuracy, nor in location error pattern. The contrast between spatially relevant versus spatially irrelevant vision provides new, rather decisive, evidence against the hypothesis that vision affects haptic processing even if it does not add task-relevant information. The results support optimal integration theories, and suggest that spatial and non-spatial aspects of vision need explicit distinction in bimodal studies and theories of spatial integration.

The role of vision processing in prosthetic vision.

PubMed

Barnes, Nick; He, Xuming; McCarthy, Chris; Horne, Lachlan; Kim, Junae; Scott, Adele; Lieby, Paulette

2012-01-01

Prosthetic vision provides vision which is reduced in resolution and dynamic range compared to normal human vision. This comes about both due to residual damage to the visual system from the condition that caused vision loss, and due to limitations of current technology. However, even with limitations, prosthetic vision may still be able to support functional performance which is sufficient for tasks which are key to restoring independent living and quality of life. Here vision processing can play a key role, ensuring that information which is critical to the performance of key tasks is available within the capability of the available prosthetic vision. In this paper, we frame vision processing for prosthetic vision, highlight some key areas which present problems in terms of quality of life, and present examples where vision processing can help achieve better outcomes.

The effects of advertisement location and familiarity on selective attention.

PubMed

Jessen, Tanja Lund; Rodway, Paul

2010-06-01

This study comprised two experiments to examine the distracting effects of advertisement familiarity, location, and onset on the performance of a selective attention task. In Exp. 1, familiar advertisements presented in peripheral vision disrupted selective attention when the attention task was more demanding, suggesting that the distracting effect of advertisements is a product of task demands and advertisement familiarity and location. In Exp. 2, the onset of the advertisement shortly before, or after, the attention task captured attention and disrupted attentional performance. The onset of the advertisement before the attention task reduced target response time without an increase in errors and therefore facilitated performance. Despite being instructed to ignore the advertisements, the participants were able to recall a substantial proportion of the familiar advertisements. Implications for the presentation of advertisements during human-computer interaction were discussed.

Monovision techniques for telerobots

NASA Technical Reports Server (NTRS)

Goode, P. W.; Carnils, K.

1987-01-01

The primary task of the vision sensor in a telerobotic system is to provide information about the position of the system's effector relative to objects of interest in its environment. The subtasks required to perform the primary task include image segmentation, object recognition, and object location and orientation in some coordinate system. The accomplishment of the vision task requires the appropriate processing tools and the system methodology to effectively apply the tools to the subtasks. The functional structure of the telerobotic vision system used in the Langley Research Center's Intelligent Systems Research Laboratory is discussed as well as two monovision techniques for accomplishing the vision subtasks.

A Unified Taxonomic Approach to the Laboratory Assessment of Visionic Devices

DTIC Science & Technology

2006-09-01

the ratification stage with member nations. Marasco and Task 4 presented a large array of tests applicable to image intensification-based visionic...aircraft.” In print. 4. Marasco , P. L., and Task, H. L. 1999. “Optical characterization of wide field-of-view night vision devices,” in

Improving the Aircraft Design Process Using Web-Based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.; Follen, Gregory J. (Technical Monitor)

2000-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and multifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Improving the Aircraft Design Process Using Web-based Modeling and Simulation

NASA Technical Reports Server (NTRS)

Reed, John A.; Follen, Gregory J.; Afjeh, Abdollah A.

2003-01-01

Designing and developing new aircraft systems is time-consuming and expensive. Computational simulation is a promising means for reducing design cycle times, but requires a flexible software environment capable of integrating advanced multidisciplinary and muitifidelity analysis methods, dynamically managing data across heterogeneous computing platforms, and distributing computationally complex tasks. Web-based simulation, with its emphasis on collaborative composition of simulation models, distributed heterogeneous execution, and dynamic multimedia documentation, has the potential to meet these requirements. This paper outlines the current aircraft design process, highlighting its problems and complexities, and presents our vision of an aircraft design process using Web-based modeling and simulation.

Towards an Autonomic Cluster Management System (ACMS) with Reflex Autonomicity

NASA Technical Reports Server (NTRS)

Truszkowski, Walt; Hinchey, Mike; Sterritt, Roy

2005-01-01

Cluster computing, whereby a large number of simple processors or nodes are combined together to apparently function as a single powerful computer, has emerged as a research area in its own right. The approach offers a relatively inexpensive means of providing a fault-tolerant environment and achieving significant computational capabilities for high-performance computing applications. However, the task of manually managing and configuring a cluster quickly becomes daunting as the cluster grows in size. Autonomic computing, with its vision to provide self-management, can potentially solve many of the problems inherent in cluster management. We describe the development of a prototype Autonomic Cluster Management System (ACMS) that exploits autonomic properties in automating cluster management and its evolution to include reflex reactions via pulse monitoring.

Brain functional network connectivity based on a visual task: visual information processing-related brain regions are significantly activated in the task state.

PubMed

Yang, Yan-Li; Deng, Hong-Xia; Xing, Gui-Yang; Xia, Xiao-Luan; Li, Hai-Fang

2015-02-01

It is not clear whether the method used in functional brain-network related research can be applied to explore the feature binding mechanism of visual perception. In this study, we investigated feature binding of color and shape in visual perception. Functional magnetic resonance imaging data were collected from 38 healthy volunteers at rest and while performing a visual perception task to construct brain networks active during resting and task states. Results showed that brain regions involved in visual information processing were obviously activated during the task. The components were partitioned using a greedy algorithm, indicating the visual network existed during the resting state. Z-values in the vision-related brain regions were calculated, confirming the dynamic balance of the brain network. Connectivity between brain regions was determined, and the result showed that occipital and lingual gyri were stable brain regions in the visual system network, the parietal lobe played a very important role in the binding process of color features and shape features, and the fusiform and inferior temporal gyri were crucial for processing color and shape information. Experimental findings indicate that understanding visual feature binding and cognitive processes will help establish computational models of vision, improve image recognition technology, and provide a new theoretical mechanism for feature binding in visual perception.

Computational approaches to vision

NASA Technical Reports Server (NTRS)

Barrow, H. G.; Tenenbaum, J. M.

1986-01-01

Vision is examined in terms of a computational process, and the competence, structure, and control of computer vision systems are analyzed. Theoretical and experimental data on the formation of a computer vision system are discussed. Consideration is given to early vision, the recovery of intrinsic surface characteristics, higher levels of interpretation, and system integration and control. A computational visual processing model is proposed and its architecture and operation are described. Examples of state-of-the-art vision systems, which include some of the levels of representation and processing mechanisms, are presented.

Automated detection and classification of dice

NASA Astrophysics Data System (ADS)

Correia, Bento A. B.; Silva, Jeronimo A.; Carvalho, Fernando D.; Guilherme, Rui; Rodrigues, Fernando C.; de Silva Ferreira, Antonio M.

1995-03-01

This paper describes a typical machine vision system in an unusual application, the automated visual inspection of a Casino's playing tables. The SORTE computer vision system was developed at INETI under a contract with the Portuguese Gaming Inspection Authorities IGJ. It aims to automate the tasks of detection and classification of the dice's scores on the playing tables of the game `Banca Francesa' (which means French Banking) in Casinos. The system is based on the on-line analysis of the images captured by a monochrome CCD camera placed over the playing tables, in order to extract relevant information concerning the score indicated by the dice. Image processing algorithms for real time automatic throwing detection and dice classification were developed and implemented.

Machine vision based teleoperation aid

NASA Technical Reports Server (NTRS)

Hoff, William A.; Gatrell, Lance B.; Spofford, John R.

1991-01-01

When teleoperating a robot using video from a remote camera, it is difficult for the operator to gauge depth and orientation from a single view. In addition, there are situations where a camera mounted for viewing by the teleoperator during a teleoperation task may not be able to see the tool tip, or the viewing angle may not be intuitive (requiring extensive training to reduce the risk of incorrect or dangerous moves by the teleoperator). A machine vision based teleoperator aid is presented which uses the operator's camera view to compute an object's pose (position and orientation), and then overlays onto the operator's screen information on the object's current and desired positions. The operator can choose to display orientation and translation information as graphics and/or text. This aid provides easily assimilated depth and relative orientation information to the teleoperator. The camera may be mounted at any known orientation relative to the tool tip. A preliminary experiment with human operators was conducted and showed that task accuracies were significantly greater with than without this aid.

Stereo Image Ranging For An Autonomous Robot Vision System

NASA Astrophysics Data System (ADS)

Holten, James R.; Rogers, Steven K.; Kabrisky, Matthew; Cross, Steven

1985-12-01

The principles of stereo vision for three-dimensional data acquisition are well-known and can be applied to the problem of an autonomous robot vehicle. Coincidental points in the two images are located and then the location of that point in a three-dimensional space can be calculated using the offset of the points and knowledge of the camera positions and geometry. This research investigates the application of artificial intelligence knowledge representation techniques as a means to apply heuristics to relieve the computational intensity of the low level image processing tasks. Specifically a new technique for image feature extraction is presented. This technique, the Queen Victoria Algorithm, uses formal language productions to process the image and characterize its features. These characterized features are then used for stereo image feature registration to obtain the required ranging information. The results can be used by an autonomous robot vision system for environmental modeling and path finding.

Knowledge-based vision for space station object motion detection, recognition, and tracking

NASA Technical Reports Server (NTRS)

Symosek, P.; Panda, D.; Yalamanchili, S.; Wehner, W., III

1987-01-01

Computer vision, especially color image analysis and understanding, has much to offer in the area of the automation of Space Station tasks such as construction, satellite servicing, rendezvous and proximity operations, inspection, experiment monitoring, data management and training. Knowledge-based techniques improve the performance of vision algorithms for unstructured environments because of their ability to deal with imprecise a priori information or inaccurately estimated feature data and still produce useful results. Conventional techniques using statistical and purely model-based approaches lack flexibility in dealing with the variabilities anticipated in the unstructured viewing environment of space. Algorithms developed under NASA sponsorship for Space Station applications to demonstrate the value of a hypothesized architecture for a Video Image Processor (VIP) are presented. Approaches to the enhancement of the performance of these algorithms with knowledge-based techniques and the potential for deployment of highly-parallel multi-processor systems for these algorithms are discussed.

A validation study regarding a generative approach in choosing appropriate colors for impaired users.

PubMed

Troiano, Luigi; Birtolo, Cosimo; Armenise, Roberto

2016-01-01

In many circumstances, concepts, ideas and emotions are mainly conveyed by colors. Color vision disorders can heavily limit the user experience in accessing Information Society. Therefore, color vision impairments should be taken into account in order to make information and services accessible to a broader audience. The task is not easy for designers that generally are not affected by any color vision disorder. In any case, the design of accessible user interfaces should not lead to to boring color schemes. The selection of appealing and harmonic color combinations should be preserved. In past research we investigated a generative approach led by evolutionary computing in supporting interface designers to make colors accessible to impaired users. This approach has also been followed by other authors. The contribution of this paper is to provide an experimental validation to the claim that this approach is actually beneficial to designers and users.

Can computational goals inform theories of vision?

PubMed

Anderson, Barton L

2015-04-01

One of the most lasting contributions of Marr's posthumous book is his articulation of the different "levels of analysis" that are needed to understand vision. Although a variety of work has examined how these different levels are related, there is comparatively little examination of the assumptions on which his proposed levels rest, or the plausibility of the approach Marr articulated given those assumptions. Marr placed particular significance on computational level theory, which specifies the "goal" of a computation, its appropriateness for solving a particular problem, and the logic by which it can be carried out. The structure of computational level theory is inherently teleological: What the brain does is described in terms of its purpose. I argue that computational level theory, and the reverse-engineering approach it inspires, requires understanding the historical trajectory that gave rise to functional capacities that can be meaningfully attributed with some sense of purpose or goal, that is, a reconstruction of the fitness function on which natural selection acted in shaping our visual abilities. I argue that this reconstruction is required to distinguish abilities shaped by natural selection-"natural tasks" -from evolutionary "by-products" (spandrels, co-optations, and exaptations), rather than merely demonstrating that computational goals can be embedded in a Bayesian model that renders a particular behavior or process rational. Copyright © 2015 Cognitive Science Society, Inc.

Center of Excellence in Aerospace Manufacturing Automation

DTIC Science & Technology

1983-11-01

affiliated industrial companies, who will pi,)vide financial support and ongoing guidance to the Institute. SIMA will encompass the design and management ...tactile sensing, intelligent systems for robot task management , and computer vision for robot management . We are addressing the question of how to provide...than anything today’s control systems could stably manage . To do this we have begun to develop a sequen- tial family of new manipulators that are

A Constraint Generation Approach to Learning Stable Linear Dynamical Systems

DTIC Science & Technology

2008-01-01

task of learning dynamic textures from image sequences as well as to modeling biosurveillance drug-sales data. The constraint generation approach...previous methods in our experiments. One application of LDSs in computer vision is learning dynamic textures from video data [8]. An advantage of...over-the-counter (OTC) drug sales for biosurveillance , and sunspot numbers from the UCR archive [9]. Comparison to the best alternative methods [7, 10

Comparison of progressive addition lenses for general purpose and for computer vision: an office field study.

PubMed

Jaschinski, Wolfgang; König, Mirjam; Mekontso, Tiofil M; Ohlendorf, Arne; Welscher, Monique

2015-05-01

Two types of progressive addition lenses (PALs) were compared in an office field study: 1. General purpose PALs with continuous clear vision between infinity and near reading distances and 2. Computer vision PALs with a wider zone of clear vision at the monitor and in near vision but no clear distance vision. Twenty-three presbyopic participants wore each type of lens for two weeks in a double-masked four-week quasi-experimental procedure that included an adaptation phase (Weeks 1 and 2) and a test phase (Weeks 3 and 4). Questionnaires on visual and musculoskeletal conditions as well as preferences regarding the type of lenses were administered. After eight more weeks of free use of the spectacles, the preferences were assessed again. The ergonomic conditions were analysed from photographs. Head inclination when looking at the monitor was significantly lower by 2.3 degrees with the computer vision PALs than with the general purpose PALs. Vision at the monitor was judged significantly better with computer PALs, while distance vision was judged better with general purpose PALs; however, the reported advantage of computer vision PALs differed in extent between participants. Accordingly, 61 per cent of the participants preferred the computer vision PALs, when asked without information about lens design. After full information about lens characteristics and additional eight weeks of free spectacle use, 44 per cent preferred the computer vision PALs. On average, computer vision PALs were rated significantly better with respect to vision at the monitor during the experimental part of the study. In the final forced-choice ratings, approximately half of the participants preferred either the computer vision PAL or the general purpose PAL. Individual factors seem to play a role in this preference and in the rated advantage of computer vision PALs. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Deep hierarchies in the primate visual cortex: what can we learn for computer vision?

PubMed

Krüger, Norbert; Janssen, Peter; Kalkan, Sinan; Lappe, Markus; Leonardis, Ales; Piater, Justus; Rodríguez-Sánchez, Antonio J; Wiskott, Laurenz

2013-08-01

Computational modeling of the primate visual system yields insights of potential relevance to some of the challenges that computer vision is facing, such as object recognition and categorization, motion detection and activity recognition, or vision-based navigation and manipulation. This paper reviews some functional principles and structures that are generally thought to underlie the primate visual cortex, and attempts to extract biological principles that could further advance computer vision research. Organized for a computer vision audience, we present functional principles of the processing hierarchies present in the primate visual system considering recent discoveries in neurophysiology. The hierarchical processing in the primate visual system is characterized by a sequence of different levels of processing (on the order of 10) that constitute a deep hierarchy in contrast to the flat vision architectures predominantly used in today's mainstream computer vision. We hope that the functional description of the deep hierarchies realized in the primate visual system provides valuable insights for the design of computer vision algorithms, fostering increasingly productive interaction between biological and computer vision research.

Egocentric daily activity recognition via multitask clustering.

PubMed

Yan, Yan; Ricci, Elisa; Liu, Gaowen; Sebe, Nicu

2015-10-01

Recognizing human activities from videos is a fundamental research problem in computer vision. Recently, there has been a growing interest in analyzing human behavior from data collected with wearable cameras. First-person cameras continuously record several hours of their wearers' life. To cope with this vast amount of unlabeled and heterogeneous data, novel algorithmic solutions are required. In this paper, we propose a multitask clustering framework for activity of daily living analysis from visual data gathered from wearable cameras. Our intuition is that, even if the data are not annotated, it is possible to exploit the fact that the tasks of recognizing everyday activities of multiple individuals are related, since typically people perform the same actions in similar environments, e.g., people working in an office often read and write documents). In our framework, rather than clustering data from different users separately, we propose to look for clustering partitions which are coherent among related tasks. In particular, two novel multitask clustering algorithms, derived from a common optimization problem, are introduced. Our experimental evaluation, conducted both on synthetic data and on publicly available first-person vision data sets, shows that the proposed approach outperforms several single-task and multitask learning methods.

Advanced biologically plausible algorithms for low-level image processing

NASA Astrophysics Data System (ADS)

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

1999-08-01

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

A cognitive approach to vision for a mobile robot

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Funk, Christopher; Lyons, Damian

2013-05-01

We describe a cognitive vision system for a mobile robot. This system works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion. These 3D models are embedded within an overall 3D model of the robot's environment. This approach turns the computer vision problem into a search problem, with the goal of constructing a physically realistic model of the entire environment. At each step, the vision system selects a point in the visual input to focus on. The distance, shape, texture and motion information are computed in a small region and used to build a mesh in a 3D virtual world. Background knowledge is used to extend this structure as appropriate, e.g. if a patch of wall is seen, it is hypothesized to be part of a large wall and the entire wall is created in the virtual world, or if part of an object is recognized, the whole object's mesh is retrieved from the library of objects and placed into the virtual world. The difference between the input from the real camera and from the virtual camera is compared using local Gaussians, creating an error mask that indicates the main differences between them. This is then used to select the next points to focus on. This approach permits us to use very expensive algorithms on small localities, thus generating very accurate models. It also is task-oriented, permitting the robot to use its knowledge about its task and goals to decide which parts of the environment need to be examined. The software components of this architecture include PhysX for the 3D virtual world, OpenCV and the Point Cloud Library for visual processing, and the Soar cognitive architecture, which controls the perceptual processing and robot planning. The hardware is a custom-built pan-tilt stereo color camera. We describe experiments using both static and moving objects.

Learning from vision-to-touch is different than learning from touch-to-vision.

PubMed

Wismeijer, Dagmar A; Gegenfurtner, Karl R; Drewing, Knut

2012-01-01

We studied whether vision can teach touch to the same extent as touch seems to teach vision. In a 2 × 2 between-participants learning study, we artificially correlated visual gloss cues with haptic compliance cues. In two "natural" tasks, we tested whether visual gloss estimations have an influence on haptic estimations of softness and vice versa. In two "novel" tasks, in which participants were either asked to haptically judge glossiness or to visually judge softness, we investigated how perceptual estimates transfer from one sense to the other. Our results showed that vision does not teach touch as efficient as touch seems to teach vision.

Low Vision: Assessment and Training for Mobility.

ERIC Educational Resources Information Center

Dodds, Allan G.; Davis, Denis P.

1987-01-01

To develop a battery of tasks to predict and improve mobility performance, a series of functional vision tasks (texural shearing, degraded images, embedded figures, and parafoveal attention) were generated by a microcomputer. Sixty visually impaired subjects given either computerized task training or real-life training improved their low vision…

A computer simulation experiment of supervisory control of remote manipulation. M.S. Thesis

NASA Technical Reports Server (NTRS)

Mccandlish, S. G.

1966-01-01

A computer simulation of a remote manipulation task and a rate-controlled manipulator is described. Some low-level automatic decision making ability which could be used at the operator's discretion to augment his direct continuous control was built into the manipulator. Experiments were made on the effect of transmission delay, dynamic lag, and intermittent vision on human manipulative ability. Delay does not make remote manipulation impossible. Intermittent visual feedback, and the absence of rate information in the display presented to the operator do not seem to impair the operator's performance. A small-capacity visual feedback channel may be sufficient for remote manipulation tasks, or one channel might be time-shared between several operators. In other experiments the operator called in sequence various on-site automatic control programs of the machine, and thereby acted as a supervisor. The supervisory mode of operation has some advantages when the task to be performed is difficult for a human controlling directly.

FLORA™: Phase I development of a functional vision assessment for prosthetic vision users

PubMed Central

Geruschat, Duane R; Flax, Marshall; Tanna, Nilima; Bianchi, Michelle; Fisher, Andy; Goldschmidt, Mira; Fisher, Lynne; Dagnelie, Gislin; Deremeik, Jim; Smith, Audrey; Anaflous, Fatima; Dorn, Jessy

2014-01-01

Background Research groups and funding agencies need a functional assessment suitable for an ultra-low vision population in order to evaluate the impact of new vision restoration treatments. The purpose of this study was to develop a pilot assessment to capture the functional vision ability and well-being of subjects whose vision has been partially restored with the Argus II Retinal Prosthesis System. Methods The Functional Low-Vision Observer Rated Assessment (FLORA) pilot assessment involved a self-report section, a list of functional vision tasks for observation of performance, and a case narrative summary. Results were analyzed to determine whether the interview questions and functional vision tasks were appropriate for this ultra-low vision population and whether the ratings suffered from floor or ceiling effects. Thirty subjects with severe to profound retinitis pigmentosa (bare light perception or worse in both eyes) were enrolled in a clinical trial and implanted with the Argus II System. From this population, twenty-six subjects were assessed with the FLORA. Seven different evaluators administered the assessment. Results All 14 interview questions were asked. All 35 functional vision tasks were selected for evaluation at least once, with an average of 20 subjects being evaluated for each test item. All four rating options -- impossible (33%), difficult (23%), moderate (24%) and easy (19%) -- were used by the evaluators. Evaluators also judged the amount of vision they observed the subjects using to complete the various tasks, with vision only occurring 75% on average with the System ON, and 29% with the System OFF. Conclusion The first version of the FLORA was found to contain useful elements for evaluation and to avoid floor and ceiling effects. The next phase of development will be to refine the assessment and to establish reliability and validity to increase its value as a functional vision and well-being assessment tool. PMID:25675964

Perceptual organization in computer vision - A review and a proposal for a classificatory structure

NASA Technical Reports Server (NTRS)

Sarkar, Sudeep; Boyer, Kim L.

1993-01-01

The evolution of perceptual organization in biological vision, and its necessity in advanced computer vision systems, arises from the characteristic that perception, the extraction of meaning from sensory input, is an intelligent process. This is particularly so for high order organisms and, analogically, for more sophisticated computational models. The role of perceptual organization in computer vision systems is explored. This is done from four vantage points. First, a brief history of perceptual organization research in both humans and computer vision is offered. Next, a classificatory structure in which to cast perceptual organization research to clarify both the nomenclature and the relationships among the many contributions is proposed. Thirdly, the perceptual organization work in computer vision in the context of this classificatory structure is reviewed. Finally, the array of computational techniques applied to perceptual organization problems in computer vision is surveyed.

A cost-effective intelligent robotic system with dual-arm dexterous coordination and real-time vision

NASA Technical Reports Server (NTRS)

Marzwell, Neville I.; Chen, Alexander Y. K.

1991-01-01

Dexterous coordination of manipulators based on the use of redundant degrees of freedom, multiple sensors, and built-in robot intelligence represents a critical breakthrough in development of advanced manufacturing technology. A cost-effective approach for achieving this new generation of robotics has been made possible by the unprecedented growth of the latest microcomputer and network systems. The resulting flexible automation offers the opportunity to improve the product quality, increase the reliability of the manufacturing process, and augment the production procedures for optimizing the utilization of the robotic system. Moreover, the Advanced Robotic System (ARS) is modular in design and can be upgraded by closely following technological advancements as they occur in various fields. This approach to manufacturing automation enhances the financial justification and ensures the long-term profitability and most efficient implementation of robotic technology. The new system also addresses a broad spectrum of manufacturing demand and has the potential to address both complex jobs as well as highly labor-intensive tasks. The ARS prototype employs the decomposed optimization technique in spatial planning. This technique is implemented to the framework of the sensor-actuator network to establish the general-purpose geometric reasoning system. The development computer system is a multiple microcomputer network system, which provides the architecture for executing the modular network computing algorithms. The knowledge-based approach used in both the robot vision subsystem and the manipulation control subsystems results in the real-time image processing vision-based capability. The vision-based task environment analysis capability and the responsive motion capability are under the command of the local intelligence centers. An array of ultrasonic, proximity, and optoelectronic sensors is used for path planning. The ARS currently has 18 degrees of freedom made up by two articulated arms, one movable robot head, and two charged coupled device (CCD) cameras for producing the stereoscopic views, and articulated cylindrical-type lower body, and an optional mobile base. A functional prototype is demonstrated.

A Linked List-Based Algorithm for Blob Detection on Embedded Vision-Based Sensors

PubMed Central

Acevedo-Avila, Ricardo; Gonzalez-Mendoza, Miguel; Garcia-Garcia, Andres

2016-01-01

Blob detection is a common task in vision-based applications. Most existing algorithms are aimed at execution on general purpose computers; while very few can be adapted to the computing restrictions present in embedded platforms. This paper focuses on the design of an algorithm capable of real-time blob detection that minimizes system memory consumption. The proposed algorithm detects objects in one image scan; it is based on a linked-list data structure tree used to label blobs depending on their shape and node information. An example application showing the results of a blob detection co-processor has been built on a low-powered field programmable gate array hardware as a step towards developing a smart video surveillance system. The detection method is intended for general purpose application. As such, several test cases focused on character recognition are also examined. The results obtained present a fair trade-off between accuracy and memory requirements; and prove the validity of the proposed approach for real-time implementation on resource-constrained computing platforms. PMID:27240382

Recognizing sights, smells, and sounds with gnostic fields.

PubMed

Kanan, Christopher

2013-01-01

Mammals rely on vision, audition, and olfaction to remotely sense stimuli in their environment. Determining how the mammalian brain uses this sensory information to recognize objects has been one of the major goals of psychology and neuroscience. Likewise, researchers in computer vision, machine audition, and machine olfaction have endeavored to discover good algorithms for stimulus classification. Almost 50 years ago, the neuroscientist Jerzy Konorski proposed a theoretical model in his final monograph in which competing sets of "gnostic" neurons sitting atop sensory processing hierarchies enabled stimuli to be robustly categorized, despite variations in their presentation. Much of what Konorski hypothesized has been remarkably accurate, and neurons with gnostic-like properties have been discovered in visual, aural, and olfactory brain regions. Surprisingly, there have not been any attempts to directly transform his theoretical model into a computational one. Here, I describe the first computational implementation of Konorski's theory. The model is not domain specific, and it surpasses the best machine learning algorithms on challenging image, music, and olfactory classification tasks, while also being simpler. My results suggest that criticisms of exemplar-based models of object recognition as being computationally intractable due to limited neural resources are unfounded.

Recognizing Sights, Smells, and Sounds with Gnostic Fields

PubMed Central

Kanan, Christopher

2013-01-01

Mammals rely on vision, audition, and olfaction to remotely sense stimuli in their environment. Determining how the mammalian brain uses this sensory information to recognize objects has been one of the major goals of psychology and neuroscience. Likewise, researchers in computer vision, machine audition, and machine olfaction have endeavored to discover good algorithms for stimulus classification. Almost 50 years ago, the neuroscientist Jerzy Konorski proposed a theoretical model in his final monograph in which competing sets of “gnostic” neurons sitting atop sensory processing hierarchies enabled stimuli to be robustly categorized, despite variations in their presentation. Much of what Konorski hypothesized has been remarkably accurate, and neurons with gnostic-like properties have been discovered in visual, aural, and olfactory brain regions. Surprisingly, there have not been any attempts to directly transform his theoretical model into a computational one. Here, I describe the first computational implementation of Konorski's theory. The model is not domain specific, and it surpasses the best machine learning algorithms on challenging image, music, and olfactory classification tasks, while also being simpler. My results suggest that criticisms of exemplar-based models of object recognition as being computationally intractable due to limited neural resources are unfounded. PMID:23365648

Hand-gesture-based sterile interface for the operating room using contextual cues for the navigation of radiological images

PubMed Central

Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A

2013-01-01

This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces. PMID:23250787

Hand-gesture-based sterile interface for the operating room using contextual cues for the navigation of radiological images.

PubMed

Jacob, Mithun George; Wachs, Juan Pablo; Packer, Rebecca A

2013-06-01

This paper presents a method to improve the navigation and manipulation of radiological images through a sterile hand gesture recognition interface based on attentional contextual cues. Computer vision algorithms were developed to extract intention and attention cues from the surgeon's behavior and combine them with sensory data from a commodity depth camera. The developed interface was tested in a usability experiment to assess the effectiveness of the new interface. An image navigation and manipulation task was performed, and the gesture recognition accuracy, false positives and task completion times were computed to evaluate system performance. Experimental results show that gesture interaction and surgeon behavior analysis can be used to accurately navigate, manipulate and access MRI images, and therefore this modality could replace the use of keyboard and mice-based interfaces.

Parametric Representation of the Speaker's Lips for Multimodal Sign Language and Speech Recognition

NASA Astrophysics Data System (ADS)

Ryumin, D.; Karpov, A. A.

2017-05-01

In this article, we propose a new method for parametric representation of human's lips region. The functional diagram of the method is described and implementation details with the explanation of its key stages and features are given. The results of automatic detection of the regions of interest are illustrated. A speed of the method work using several computers with different performances is reported. This universal method allows applying parametrical representation of the speaker's lipsfor the tasks of biometrics, computer vision, machine learning, and automatic recognition of face, elements of sign languages, and audio-visual speech, including lip-reading.

The Illinois Century Network: New Dimensions for Education in Illinois. A Vision for Communications and Computing Networking To Retain and Expand Illinois' Position as a World Leader by the Turn of the Century. Report and First-Phase Recommendations of the Higher Education Technology Task Force to the Illinois Board of Higher Education and the Illinois Community College Board.

ERIC Educational Resources Information Center

Illinois State Board of Higher Education, Springfield.

This proposal calls on the state of Illinois to initiate a statewide computing and telecommunications network that would give its residents access to higher education, advanced training, and electronic information resources. The proposed network, entitled Illinois Century Network, would link all higher education institutions in the state to…

Computer vision barrel inspection

NASA Astrophysics Data System (ADS)

Wolfe, William J.; Gunderson, James; Walworth, Matthew E.

1994-02-01

One of the Department of Energy's (DOE) ongoing tasks is the storage and inspection of a large number of waste barrels containing a variety of hazardous substances. Martin Marietta is currently contracted to develop a robotic system -- the Intelligent Mobile Sensor System (IMSS) -- for the automatic monitoring and inspection of these barrels. The IMSS is a mobile robot with multiple sensors: video cameras, illuminators, laser ranging and barcode reader. We assisted Martin Marietta in this task, specifically in the development of image processing algorithms that recognize and classify the barrel labels. Our subsystem uses video images to detect and locate the barcode, so that the barcode reader can be pointed at the barcode.

The Impact of Residual Vision in Spatial Skills of Individuals with Visual Impairments

ERIC Educational Resources Information Center

Papadopoulos, Konstantinos; Koustriava, Eleni; Kartasidou, Lefkothea

2011-01-01

Loss of vision is believed to have a great impact on the acquisition of spatial knowledge. The aims of the present study are to examine the performance of individuals with visual impairments on spatial tasks and the impact of residual vision on processing these tasks. In all, 28 individuals with visual impairments--blindness or low…

Feature Extraction and Machine Learning for the Classification of Brazilian Savannah Pollen Grains

PubMed Central

Souza, Junior Silva; da Silva, Gercina Gonçalves

2016-01-01

The classification of pollen species and types is an important task in many areas like forensic palynology, archaeological palynology and melissopalynology. This paper presents the first annotated image dataset for the Brazilian Savannah pollen types that can be used to train and test computer vision based automatic pollen classifiers. A first baseline human and computer performance for this dataset has been established using 805 pollen images of 23 pollen types. In order to access the computer performance, a combination of three feature extractors and four machine learning techniques has been implemented, fine tuned and tested. The results of these tests are also presented in this paper. PMID:27276196

Learning from vision-to-touch is different than learning from touch-to-vision

PubMed Central

Wismeijer, Dagmar A.; Gegenfurtner, Karl R.; Drewing, Knut

2012-01-01

We studied whether vision can teach touch to the same extent as touch seems to teach vision. In a 2 × 2 between-participants learning study, we artificially correlated visual gloss cues with haptic compliance cues. In two “natural” tasks, we tested whether visual gloss estimations have an influence on haptic estimations of softness and vice versa. In two “novel” tasks, in which participants were either asked to haptically judge glossiness or to visually judge softness, we investigated how perceptual estimates transfer from one sense to the other. Our results showed that vision does not teach touch as efficient as touch seems to teach vision. PMID:23181012

Advantages of computer cameras over video cameras/frame grabbers for high-speed vision applications

NASA Astrophysics Data System (ADS)

Olson, Gaylord G.; Walker, Jo N.

1997-09-01

Cameras designed to work specifically with computers can have certain advantages in comparison to the use of cameras loosely defined as 'video' cameras. In recent years the camera type distinctions have become somewhat blurred, with a great presence of 'digital cameras' aimed more at the home markets. This latter category is not considered here. The term 'computer camera' herein is intended to mean one which has low level computer (and software) control of the CCD clocking. These can often be used to satisfy some of the more demanding machine vision tasks, and in some cases with a higher rate of measurements than video cameras. Several of these specific applications are described here, including some which use recently designed CCDs which offer good combinations of parameters such as noise, speed, and resolution. Among the considerations for the choice of camera type in any given application would be such effects as 'pixel jitter,' and 'anti-aliasing.' Some of these effects may only be relevant if there is a mismatch between the number of pixels per line in the camera CCD and the number of analog to digital (A/D) sampling points along a video scan line. For the computer camera case these numbers are guaranteed to match, which alleviates some measurement inaccuracies and leads to higher effective resolution.

Progress in building a cognitive vision system

NASA Astrophysics Data System (ADS)

Benjamin, D. Paul; Lyons, Damian; Yue, Hong

2016-05-01

We are building a cognitive vision system for mobile robots that works in a manner similar to the human vision system, using saccadic, vergence and pursuit movements to extract information from visual input. At each fixation, the system builds a 3D model of a small region, combining information about distance, shape, texture and motion to create a local dynamic spatial model. These local 3D models are composed to create an overall 3D model of the robot and its environment. This approach turns the computer vision problem into a search problem whose goal is the acquisition of sufficient spatial understanding for the robot to succeed at its tasks. The research hypothesis of this work is that the movements of the robot's cameras are only those that are necessary to build a sufficiently accurate world model for the robot's current goals. For example, if the goal is to navigate through a room, the model needs to contain any obstacles that would be encountered, giving their approximate positions and sizes. Other information does not need to be rendered into the virtual world, so this approach trades model accuracy for speed.

Auto-SEIA: simultaneous optimization of image processing and machine learning algorithms

NASA Astrophysics Data System (ADS)

Negro Maggio, Valentina; Iocchi, Luca

2015-02-01

Object classification from images is an important task for machine vision and it is a crucial ingredient for many computer vision applications, ranging from security and surveillance to marketing. Image based object classification techniques properly integrate image processing and machine learning (i.e., classification) procedures. In this paper we present a system for automatic simultaneous optimization of algorithms and parameters for object classification from images. More specifically, the proposed system is able to process a dataset of labelled images and to return a best configuration of image processing and classification algorithms and of their parameters with respect to the accuracy of classification. Experiments with real public datasets are used to demonstrate the effectiveness of the developed system.

Home Lighting Assessment for Clients With Low Vision

PubMed Central

Bhorade, Anjali; Gordon, Mae; Hollingsworth, Holly; Engsberg, Jack E.; Baum, M. Carolyn

2013-01-01

OBJECTIVE. The goal was to develop an objective, comprehensive, near-task home lighting assessment for older adults with low vision. METHOD. A home lighting assessment was developed and tested with older adults with low vision. Interrater and test–retest reliability studies were conducted. Clinical utility was assessed by occupational therapists with expertise in low vision rehabilitation. RESULTS. Interrater reliability was high (intraclass correlation coefficient [ICC] = .83–1.0). Test–retest reliability was moderate (ICC = .67). Responses to a Clinical Utility Feedback Form developed for this study indicated that the Home Environment Lighting Assessment (HELA) has strong clinical utility. CONCLUSION. The HELA provides a structured tool to describe the quantitative and qualitative aspects of home lighting environments where near tasks are performed and can be used to plan lighting interventions. The HELA has the potential to affect assessment and intervention practices of rehabilitation professionals in the area of low vision and improve near-task performance of people with low vision. PMID:24195901

Interactive Tools for Measuring Visual Scanning Performance and Reaction Time

PubMed Central

Seeanner, Julia; Hennessy, Sarah; Manganelli, Joseph; Crisler, Matthew; Rosopa, Patrick; Jenkins, Casey; Anderson, Michael; Drouin, Nathalie; Belle, Leah; Truesdail, Constance; Tanner, Stephanie

2017-01-01

Occupational therapists are constantly searching for engaging, high-technology interactive tasks that provide immediate feedback to evaluate and train clients with visual scanning deficits. This study examined the relationship between two tools: the VISION COACH™ interactive light board and the Functional Object Detection© (FOD) Advanced driving simulator scenario. Fifty-four healthy drivers, ages 21–66 yr, were divided into three age groups. Participants performed braking response and visual target (E) detection tasks of the FOD Advanced driving scenario, followed by two sets of three trials using the VISION COACH Full Field 60 task. Results showed no significant effect of age on FOD Advanced performance but a significant effect of age on VISION COACH performance. Correlations showed that participants’ performance on both braking and E detection tasks were significantly positively correlated with performance on the VISION COACH (.37 < r < .40, p < .01). These tools provide new options for therapists. PMID:28218598

Body sway adaptation to addition but not withdrawal of stabilizing visual information is delayed by a concurrent cognitive task.

PubMed

Honeine, Jean-Louis; Crisafulli, Oscar; Schieppati, Marco

2017-02-01

The aim of this study was to test the effects of a concurrent cognitive task on the promptness of the sensorimotor integration and reweighting processes following addition and withdrawal of vision. Fourteen subjects stood in tandem while vision was passively added and removed. Subjects performed a cognitive task, consisting of counting backward in steps of three, or were "mentally idle." We estimated the time intervals following addition and withdrawal of vision at which body sway began to change. We also estimated the time constant of the exponential change in body oscillation until the new level of sway was reached, consistent with the current visual state. Under the mentally idle condition, mean latency was 0.67 and 0.46 s and the mean time constant was 1.27 and 0.59 s for vision addition and withdrawal, respectively. Following addition of vision, counting backward delayed the latency by about 300 ms, without affecting the time constant. Following withdrawal, counting backward had no significant effect on either latency or time constant. The extension by counting backward of the time interval to stabilization onset on addition of vision suggests a competition for allocation of cortical resources. Conversely, the absence of cognitive task effect on the rapid onset of destabilization on vision withdrawal, and on the relevant reweighting time course, advocates the intervention of a subcortical process. Diverting attention from a challenging standing task discloses a cortical supervision on the process of sensorimotor integration of new balance-stabilizing information. A subcortical process would instead organize the response to removal of the stabilizing sensory input. NEW & NOTEWORTHY This study is the first to test the effect of an arithmetic task on the time course of balance readjustment following visual withdrawal or addition. Performing such a cognitive task increases the time delay following addition of vision but has no effect on withdrawal dynamics. This suggests that sensorimotor integration following addition of a stabilizing signal is performed at a cortical level, whereas the response to its withdrawal is "automatic" and accomplished at a subcortical level. Copyright © 2017 the American Physiological Society.

Developing a 3D Gestural Interface for Anesthesia-Related Human-Computer Interaction Tasks Using Both Experts and Novices.

PubMed

Jurewicz, Katherina A; Neyens, David M; Catchpole, Ken; Reeves, Scott T

2018-06-01

The purpose of this research was to compare gesture-function mappings for experts and novices using a 3D, vision-based, gestural input system when exposed to the same context of anesthesia tasks in the operating room (OR). 3D, vision-based, gestural input systems can serve as a natural way to interact with computers and are potentially useful in sterile environments (e.g., ORs) to limit the spread of bacteria. Anesthesia providers' hands have been linked to bacterial transfer in the OR, but a gestural input system for anesthetic tasks has not been investigated. A repeated-measures study was conducted with two cohorts: anesthesia providers (i.e., experts) ( N = 16) and students (i.e., novices) ( N = 30). Participants chose gestures for 10 anesthetic functions across three blocks to determine intuitive gesture-function mappings. Reaction time was collected as a complementary measure for understanding the mappings. The two gesture-function mapping sets showed some similarities and differences. The gesture mappings of the anesthesia providers showed a relationship to physical components in the anesthesia environment that were not seen in the students' gestures. The students also exhibited evidence related to longer reaction times compared to the anesthesia providers. Domain expertise is influential when creating gesture-function mappings. However, both experts and novices should be able to use a gesture system intuitively, so development methods need to be refined for considering the needs of different user groups. The development of a touchless interface for perioperative anesthesia may reduce bacterial contamination and eventually offer a reduced risk of infection to patients.

Recent results in visual servoing

NASA Astrophysics Data System (ADS)

Chaumette, François

2008-06-01

Visual servoing techniques consist in using the data provided by a vision sensor in order to control the motions of a dynamic system. Such systems are usually robot arms, mobile robots, aerial robots,… but can also be virtual robots for applications in computer animation, or even a virtual camera for applications in computer vision and augmented reality. A large variety of positioning tasks, or mobile target tracking, can be implemented by controlling from one to all the degrees of freedom of the system. Whatever the sensor configuration, which can vary from one on-board camera on the robot end-effector to several free-standing cameras, a set of visual features has to be selected at best from the image measurements available, allowing to control the degrees of freedom desired. A control law has also to be designed so that these visual features reach a desired value, defining a correct realization of the task. With a vision sensor providing 2D measurements, potential visual features are numerous, since as well 2D data (coordinates of feature points in the image, moments, …) as 3D data provided by a localization algorithm exploiting the extracted 2D measurements can be considered. It is also possible to combine 2D and 3D visual features to take the advantages of each approach while avoiding their respective drawbacks. From the selected visual features, the behavior of the system will have particular properties as for stability, robustness with respect to noise or to calibration errors, robot 3D trajectory, etc. The talk will present the main basic aspects of visual servoing, as well as technical advances obtained recently in the field inside the Lagadic group at INRIA/INRISA Rennes. Several application results will be also described.

Automatic image orientation detection via confidence-based integration of low-level and semantic cues.

PubMed

Luo, Jiebo; Boutell, Matthew

2005-05-01

Automatic image orientation detection for natural images is a useful, yet challenging research topic. Humans use scene context and semantic object recognition to identify the correct image orientation. However, it is difficult for a computer to perform the task in the same way because current object recognition algorithms are extremely limited in their scope and robustness. As a result, existing orientation detection methods were built upon low-level vision features such as spatial distributions of color and texture. Discrepant detection rates have been reported for these methods in the literature. We have developed a probabilistic approach to image orientation detection via confidence-based integration of low-level and semantic cues within a Bayesian framework. Our current accuracy is 90 percent for unconstrained consumer photos, impressive given the findings of a psychophysical study conducted recently. The proposed framework is an attempt to bridge the gap between computer and human vision systems and is applicable to other problems involving semantic scene content understanding.

Traffic light detection and intersection crossing using mobile computer vision

NASA Astrophysics Data System (ADS)

Grewei, Lynne; Lagali, Christopher

2017-05-01

The solution for Intersection Detection and Crossing to support the development of blindBike an assisted biking system for the visually impaired is discussed. Traffic light detection and intersection crossing are key needs in the task of biking. These problems are tackled through the use of mobile computer vision, in the form of a mobile application on an Android phone. This research builds on previous Traffic Light detection algorithms with a focus on efficiency and compatibility on a resource-limited platform. Light detection is achieved through blob detection algorithms utilizing training data to detect patterns of Red, Green and Yellow in complex real world scenarios where multiple lights may be present. Also, issues of obscurity and scale are addressed. Safe Intersection crossing in blindBike is also discussed. This module takes a conservative "assistive" technology approach. To achieve this blindBike use's not only the Android device but, an external bike cadence Bluetooth/Ant enabled sensor. Real world testing results are given and future work is discussed.

Computer vision syndrome: a review.

PubMed

Blehm, Clayton; Vishnu, Seema; Khattak, Ashbala; Mitra, Shrabanee; Yee, Richard W

2005-01-01

As computers become part of our everyday life, more and more people are experiencing a variety of ocular symptoms related to computer use. These include eyestrain, tired eyes, irritation, redness, blurred vision, and double vision, collectively referred to as computer vision syndrome. This article describes both the characteristics and treatment modalities that are available at this time. Computer vision syndrome symptoms may be the cause of ocular (ocular-surface abnormalities or accommodative spasms) and/or extraocular (ergonomic) etiologies. However, the major contributor to computer vision syndrome symptoms by far appears to be dry eye. The visual effects of various display characteristics such as lighting, glare, display quality, refresh rates, and radiation are also discussed. Treatment requires a multidirectional approach combining ocular therapy with adjustment of the workstation. Proper lighting, anti-glare filters, ergonomic positioning of computer monitor and regular work breaks may help improve visual comfort. Lubricating eye drops and special computer glasses help relieve ocular surface-related symptoms. More work needs to be done to specifically define the processes that cause computer vision syndrome and to develop and improve effective treatments that successfully address these causes.

A Practical Solution Using A New Approach To Robot Vision

NASA Astrophysics Data System (ADS)

Hudson, David L.

1984-01-01

Up to now, robot vision systems have been designed to serve both application development and operational needs in inspection, assembly and material handling. This universal approach to robot vision is too costly for many practical applications. A new industrial vision system separates the function of application program development from on-line operation. A Vision Development System (VDS) is equipped with facilities designed to simplify and accelerate the application program development process. A complimentary but lower cost Target Application System (TASK) runs the application program developed with the VDS. This concept is presented in the context of an actual robot vision application that improves inspection and assembly for a manufacturer of electronic terminal keyboards. Applications developed with a VDS experience lower development cost when compared with conventional vision systems. Since the TASK processor is not burdened with development tools, it can be installed at a lower cost than comparable "universal" vision systems that are intended to be used for both development and on-line operation. The VDS/TASK approach opens more industrial applications to robot vision that previously were not practical because of the high cost of vision systems. Although robot vision is a new technology, it has been applied successfully to a variety of industrial needs in inspection, manufacturing, and material handling. New developments in robot vision technology are creating practical, cost effective solutions for a variety of industrial needs. A year or two ago, researchers and robot manufacturers interested in implementing a robot vision application could take one of two approaches. The first approach was to purchase all the necessary vision components from various sources. That meant buying an image processor from one company, a camera from another and lens and light sources from yet others. The user then had to assemble the pieces, and in most instances he had to write all of his own software to test, analyze and process the vision application. The second and most common approach was to contract with the vision equipment vendor for the development and installation of a turnkey inspection or manufacturing system. The robot user and his company paid a premium for their vision system in an effort to assure the success of the system. Since 1981, emphasis on robotics has skyrocketed. New groups have been formed in many manufacturing companies with the charter to learn about, test and initially apply new robot and automation technologies. Machine vision is one of new technologies being tested and applied. This focused interest has created a need for a robot vision system that makes it easy for manufacturing engineers to learn about, test, and implement a robot vision application. A newly developed vision system addresses those needs. Vision Development System (VDS) is a complete hardware and software product for the development and testing of robot vision applications. A complimentary, low cost Target Application System (TASK) runs the application program developed with the VDS. An actual robot vision application that demonstrates inspection and pre-assembly for keyboard manufacturing is used to illustrate the VDS/TASK approach.

Quaternions in computer vision and robotics

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

Pervin, E.; Webb, J.A.

1982-01-01

Computer vision and robotics suffer from not having good tools for manipulating three-dimensional objects. Vectors, coordinate geometry, and trigonometry all have deficiencies. Quaternions can be used to solve many of these problems. Many properties of quaternions that are relevant to computer vision and robotics are developed. Examples are given showing how quaternions can be used to simplify derivations in computer vision and robotics.

Peripheral Vision of Youths with Low Vision: Motion Perception, Crowding, and Visual Search

PubMed Central

Tadin, Duje; Nyquist, Jeffrey B.; Lusk, Kelly E.; Corn, Anne L.; Lappin, Joseph S.

2012-01-01

Purpose. Effects of low vision on peripheral visual function are poorly understood, especially in children whose visual skills are still developing. The aim of this study was to measure both central and peripheral visual functions in youths with typical and low vision. Of specific interest was the extent to which measures of foveal function predict performance of peripheral tasks. Methods. We assessed central and peripheral visual functions in youths with typical vision (n = 7, ages 10–17) and low vision (n = 24, ages 9–18). Experimental measures used both static and moving stimuli and included visual crowding, visual search, motion acuity, motion direction discrimination, and multitarget motion comparison. Results. In most tasks, visual function was impaired in youths with low vision. Substantial differences, however, were found both between participant groups and, importantly, across different tasks within participant groups. Foveal visual acuity was a modest predictor of peripheral form vision and motion sensitivity in either the central or peripheral field. Despite exhibiting normal motion discriminations in fovea, motion sensitivity of youths with low vision deteriorated in the periphery. This contrasted with typically sighted participants, who showed improved motion sensitivity with increasing eccentricity. Visual search was greatly impaired in youths with low vision. Conclusions. Our results reveal a complex pattern of visual deficits in peripheral vision and indicate a significant role of attentional mechanisms in observed impairments. These deficits were not adequately captured by measures of foveal function, arguing for the importance of independently assessing peripheral visual function. PMID:22836766

Peripheral vision of youths with low vision: motion perception, crowding, and visual search.

PubMed

Tadin, Duje; Nyquist, Jeffrey B; Lusk, Kelly E; Corn, Anne L; Lappin, Joseph S

2012-08-24

Effects of low vision on peripheral visual function are poorly understood, especially in children whose visual skills are still developing. The aim of this study was to measure both central and peripheral visual functions in youths with typical and low vision. Of specific interest was the extent to which measures of foveal function predict performance of peripheral tasks. We assessed central and peripheral visual functions in youths with typical vision (n = 7, ages 10-17) and low vision (n = 24, ages 9-18). Experimental measures used both static and moving stimuli and included visual crowding, visual search, motion acuity, motion direction discrimination, and multitarget motion comparison. In most tasks, visual function was impaired in youths with low vision. Substantial differences, however, were found both between participant groups and, importantly, across different tasks within participant groups. Foveal visual acuity was a modest predictor of peripheral form vision and motion sensitivity in either the central or peripheral field. Despite exhibiting normal motion discriminations in fovea, motion sensitivity of youths with low vision deteriorated in the periphery. This contrasted with typically sighted participants, who showed improved motion sensitivity with increasing eccentricity. Visual search was greatly impaired in youths with low vision. Our results reveal a complex pattern of visual deficits in peripheral vision and indicate a significant role of attentional mechanisms in observed impairments. These deficits were not adequately captured by measures of foveal function, arguing for the importance of independently assessing peripheral visual function.

Benchmarking neuromorphic vision: lessons learnt from computer vision

PubMed Central

Tan, Cheston; Lallee, Stephane; Orchard, Garrick

2015-01-01

Neuromorphic Vision sensors have improved greatly since the first silicon retina was presented almost three decades ago. They have recently matured to the point where they are commercially available and can be operated by laymen. However, despite improved availability of sensors, there remains a lack of good datasets, while algorithms for processing spike-based visual data are still in their infancy. On the other hand, frame-based computer vision algorithms are far more mature, thanks in part to widely accepted datasets which allow direct comparison between algorithms and encourage competition. We are presented with a unique opportunity to shape the development of Neuromorphic Vision benchmarks and challenges by leveraging what has been learnt from the use of datasets in frame-based computer vision. Taking advantage of this opportunity, in this paper we review the role that benchmarks and challenges have played in the advancement of frame-based computer vision, and suggest guidelines for the creation of Neuromorphic Vision benchmarks and challenges. We also discuss the unique challenges faced when benchmarking Neuromorphic Vision algorithms, particularly when attempting to provide direct comparison with frame-based computer vision. PMID:26528120

Pilot vision considerations : the effect of age on binocular fusion time.

DOT National Transportation Integrated Search

1966-10-01

The study provides data regarding the relationship between vision performance and age of the individual. It has direct application to pilot visual tasks with respect to instrument panel displays, and to controller visual tasks in association with rad...

Vision sensing techniques in aeronautics and astronautics

NASA Technical Reports Server (NTRS)

Hall, E. L.

1988-01-01

The close relationship between sensing and other tasks in orbital space, and the integral role of vision sensing in practical aerospace applications, are illustrated. Typical space mission-vision tasks encompass the docking of space vehicles, the detection of unexpected objects, the diagnosis of spacecraft damage, and the inspection of critical spacecraft components. Attention is presently given to image functions, the 'windowing' of a view, the number of cameras required for inspection tasks, the choice of incoherent or coherent (laser) illumination, three-dimensional-to-two-dimensional model-matching, edge- and region-segmentation techniques, and motion analysis for tracking.

Neural correlates of virtual route recognition in congenital blindness.

PubMed

Kupers, Ron; Chebat, Daniel R; Madsen, Kristoffer H; Paulson, Olaf B; Ptito, Maurice

2010-07-13

Despite the importance of vision for spatial navigation, blind subjects retain the ability to represent spatial information and to move independently in space to localize and reach targets. However, the neural correlates of navigation in subjects lacking vision remain elusive. We therefore used functional MRI (fMRI) to explore the cortical network underlying successful navigation in blind subjects. We first trained congenitally blind and blindfolded sighted control subjects to perform a virtual navigation task with the tongue display unit (TDU), a tactile-to-vision sensory substitution device that translates a visual image into electrotactile stimulation applied to the tongue. After training, participants repeated the navigation task during fMRI. Although both groups successfully learned to use the TDU in the virtual navigation task, the brain activation patterns showed substantial differences. Blind but not blindfolded sighted control subjects activated the parahippocampus and visual cortex during navigation, areas that are recruited during topographical learning and spatial representation in sighted subjects. When the navigation task was performed under full vision in a second group of sighted participants, the activation pattern strongly resembled the one obtained in the blind when using the TDU. This suggests that in the absence of vision, cross-modal plasticity permits the recruitment of the same cortical network used for spatial navigation tasks in sighted subjects.

Effectiveness of Assistive Technologies for Low Vision Rehabilitation: A Systematic Review

ERIC Educational Resources Information Center

Jutai, Jeffrey W.; Strong, J. Graham; Russell-Minda, Elizabeth

2009-01-01

"Low vision" describes any condition of diminished vision that is uncorrectable by standard eyeglasses, contact lenses, medication, or surgery that disrupts a person's ability to perform common age-appropriate visual tasks. Examples of assistive technologies for vision rehabilitation include handheld magnifiers; electronic vision-enhancement…

Correction of Visual Perception Based on Neuro-Fuzzy Learning for the Humanoid Robot TEO.

PubMed

Hernandez-Vicen, Juan; Martinez, Santiago; Garcia-Haro, Juan Miguel; Balaguer, Carlos

2018-03-25

New applications related to robotic manipulation or transportation tasks, with or without physical grasping, are continuously being developed. To perform these activities, the robot takes advantage of different kinds of perceptions. One of the key perceptions in robotics is vision. However, some problems related to image processing makes the application of visual information within robot control algorithms difficult. Camera-based systems have inherent errors that affect the quality and reliability of the information obtained. The need of correcting image distortion slows down image parameter computing, which decreases performance of control algorithms. In this paper, a new approach to correcting several sources of visual distortions on images in only one computing step is proposed. The goal of this system/algorithm is the computation of the tilt angle of an object transported by a robot, minimizing image inherent errors and increasing computing speed. After capturing the image, the computer system extracts the angle using a Fuzzy filter that corrects at the same time all possible distortions, obtaining the real angle in only one processing step. This filter has been developed by the means of Neuro-Fuzzy learning techniques, using datasets with information obtained from real experiments. In this way, the computing time has been decreased and the performance of the application has been improved. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator) from the University Carlos III of Madrid.

Correction of Visual Perception Based on Neuro-Fuzzy Learning for the Humanoid Robot TEO

PubMed Central

2018-01-01

New applications related to robotic manipulation or transportation tasks, with or without physical grasping, are continuously being developed. To perform these activities, the robot takes advantage of different kinds of perceptions. One of the key perceptions in robotics is vision. However, some problems related to image processing makes the application of visual information within robot control algorithms difficult. Camera-based systems have inherent errors that affect the quality and reliability of the information obtained. The need of correcting image distortion slows down image parameter computing, which decreases performance of control algorithms. In this paper, a new approach to correcting several sources of visual distortions on images in only one computing step is proposed. The goal of this system/algorithm is the computation of the tilt angle of an object transported by a robot, minimizing image inherent errors and increasing computing speed. After capturing the image, the computer system extracts the angle using a Fuzzy filter that corrects at the same time all possible distortions, obtaining the real angle in only one processing step. This filter has been developed by the means of Neuro-Fuzzy learning techniques, using datasets with information obtained from real experiments. In this way, the computing time has been decreased and the performance of the application has been improved. The resulting algorithm has been tried out experimentally in robot transportation tasks in the humanoid robot TEO (Task Environment Operator) from the University Carlos III of Madrid. PMID:29587392

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.

FLORA™: Phase I development of a functional vision assessment for prosthetic vision users.

PubMed

Geruschat, Duane R; Flax, Marshall; Tanna, Nilima; Bianchi, Michelle; Fisher, Andy; Goldschmidt, Mira; Fisher, Lynne; Dagnelie, Gislin; Deremeik, Jim; Smith, Audrey; Anaflous, Fatima; Dorn, Jessy

2015-07-01

Research groups and funding agencies need a functional assessment suitable for an ultra-low vision population to evaluate the impact of new vision-restoration treatments. The purpose of this study was to develop a pilot assessment to capture the functional visual ability and well-being of subjects whose vision has been partially restored with the Argus II Retinal Prosthesis System. The Functional Low-Vision Observer Rated Assessment (FLORA) pilot assessment involved a self-report section, a list of functional visual tasks for observation of performance and a case narrative summary. Results were analysed to determine whether the interview questions and functional visual tasks were appropriate for this ultra-low vision population and whether the ratings suffered from floor or ceiling effects. Thirty subjects with severe to profound retinitis pigmentosa (bare light perception or worse in both eyes) were enrolled in a clinical trial and implanted with the Argus II System. From this population, 26 subjects were assessed with the FLORA. Seven different evaluators administered the assessment. All 14 interview questions were asked. All 35 tasks for functional vision were selected for evaluation at least once, with an average of 20 subjects being evaluated for each test item. All four rating options—impossible (33 per cent), difficult (23 per cent), moderate (24 per cent) and easy (19 per cent)—were used by the evaluators. Evaluators also judged the amount of vision they observed the subjects using to complete the various tasks, with 'vision only' occurring 75 per cent on average with the System ON, and 29 per cent with the System OFF. The first version of the FLORA was found to contain useful elements for evaluation and to avoid floor and ceiling effects. The next phase of development will be to refine the assessment and to establish reliability and validity to increase its value as an assessment tool for functional vision and well-being. © 2015 The Authors. Clinical and Experimental Optometry © 2015 Optometry Australia.

Development of a battery of functional tests for low vision.

PubMed

Dougherty, Bradley E; Martin, Scott R; Kelly, Corey B; Jones, Lisa A; Raasch, Thomas W; Bullimore, Mark A

2009-08-01

We describe the development and evaluation of a battery of tests of functional visual performance of everyday tasks intended to be suitable for assessment of low vision patients. The functional test battery comprises-Reading rate: reading aloud 20 unrelated words for each of four print sizes (8, 4, 2, & 1 M); Telephone book: finding a name and reading the telephone number; Medicine bottle label: reading the name and dosing; Utility bill: reading the due date and amount due; Cooking instructions: reading cooking time on a food package; Coin sorting: making a specified amount from coins placed on a table; Playing card recognition: identifying denomination and suit; and Face recognition: identifying expressions of printed, life-size faces at 1 and 3 m. All tests were timed except face and playing card recognition. Fourteen normally sighted and 24 low vision subjects were assessed with the functional test battery. Visual acuity, contrast sensitivity, and quality of life (National Eye Institute Visual Function Questionnaire 25 [NEI-VFQ 25]) were measured and the functional tests repeated. Subsequently, 23 low vision patients participated in a pilot randomized clinical trial with half receiving low vision rehabilitation and half a delayed intervention. The functional tests were administered at enrollment and 3 months later. Normally sighted subjects could perform all tasks but the proportion of trials performed correctly by the low vision subjects ranged from 35% for face recognition at 3 m, to 95% for the playing card identification. On average, low vision subjects performed three times slower than the normally sighted subjects. Timed tasks with a visual search component showed poorer repeatability. In the pilot clinical trial, low vision rehabilitation produced the greatest improvement for the medicine bottle and cooking instruction tasks. Performance of patients on these functional tests has been assessed. Some appear responsive to low vision rehabilitation.

Computer vision enhances mobile eye-tracking to expose expert cognition in natural-scene visual-search tasks

NASA Astrophysics Data System (ADS)

Keane, Tommy P.; Cahill, Nathan D.; Tarduno, John A.; Jacobs, Robert A.; Pelz, Jeff B.

2014-02-01

Mobile eye-tracking provides the fairly unique opportunity to record and elucidate cognition in action. In our research, we are searching for patterns in, and distinctions between, the visual-search performance of experts and novices in the geo-sciences. Traveling to regions resultant from various geological processes as part of an introductory field studies course in geology, we record the prima facie gaze patterns of experts and novices when they are asked to determine the modes of geological activity that have formed the scene-view presented to them. Recording eye video and scene video in natural settings generates complex imagery that requires advanced applications of computer vision research to generate registrations and mappings between the views of separate observers. By developing such mappings, we could then place many observers into a single mathematical space where we can spatio-temporally analyze inter- and intra-subject fixations, saccades, and head motions. While working towards perfecting these mappings, we developed an updated experiment setup that allowed us to statistically analyze intra-subject eye-movement events without the need for a common domain. Through such analyses we are finding statistical differences between novices and experts in these visual-search tasks. In the course of this research we have developed a unified, open-source, software framework for processing, visualization, and interaction of mobile eye-tracking and high-resolution panoramic imagery.

Vision technology/algorithms for space robotics applications

NASA Technical Reports Server (NTRS)

Krishen, Kumar; Defigueiredo, Rui J. P.

1987-01-01

The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed.

The impact on midlevel vision of statistically optimal divisive normalization in V1.

PubMed

Coen-Cagli, Ruben; Schwartz, Odelia

2013-07-15

The first two areas of the primate visual cortex (V1, V2) provide a paradigmatic example of hierarchical computation in the brain. However, neither the functional properties of V2 nor the interactions between the two areas are well understood. One key aspect is that the statistics of the inputs received by V2 depend on the nonlinear response properties of V1. Here, we focused on divisive normalization, a canonical nonlinear computation that is observed in many neural areas and modalities. We simulated V1 responses with (and without) different forms of surround normalization derived from statistical models of natural scenes, including canonical normalization and a statistically optimal extension that accounted for image nonhomogeneities. The statistics of the V1 population responses differed markedly across models. We then addressed how V2 receptive fields pool the responses of V1 model units with different tuning. We assumed this is achieved by learning without supervision a linear representation that removes correlations, which could be accomplished with principal component analysis. This approach revealed V2-like feature selectivity when we used the optimal normalization and, to a lesser extent, the canonical one but not in the absence of both. We compared the resulting two-stage models on two perceptual tasks; while models encompassing V1 surround normalization performed better at object recognition, only statistically optimal normalization provided systematic advantages in a task more closely matched to midlevel vision, namely figure/ground judgment. Our results suggest that experiments probing midlevel areas might benefit from using stimuli designed to engage the computations that characterize V1 optimality.

Toward open set recognition.

PubMed

Scheirer, Walter J; de Rezende Rocha, Anderson; Sapkota, Archana; Boult, Terrance E

2013-07-01

To date, almost all experimental evaluations of machine learning-based recognition algorithms in computer vision have taken the form of "closed set" recognition, whereby all testing classes are known at training time. A more realistic scenario for vision applications is "open set" recognition, where incomplete knowledge of the world is present at training time, and unknown classes can be submitted to an algorithm during testing. This paper explores the nature of open set recognition and formalizes its definition as a constrained minimization problem. The open set recognition problem is not well addressed by existing algorithms because it requires strong generalization. As a step toward a solution, we introduce a novel "1-vs-set machine," which sculpts a decision space from the marginal distances of a 1-class or binary SVM with a linear kernel. This methodology applies to several different applications in computer vision where open set recognition is a challenging problem, including object recognition and face verification. We consider both in this work, with large scale cross-dataset experiments performed over the Caltech 256 and ImageNet sets, as well as face matching experiments performed over the Labeled Faces in the Wild set. The experiments highlight the effectiveness of machines adapted for open set evaluation compared to existing 1-class and binary SVMs for the same tasks.

Pre-operative segmentation of neck CT datasets for the planning of neck dissections

NASA Astrophysics Data System (ADS)

Cordes, Jeanette; Dornheim, Jana; Preim, Bernhard; Hertel, Ilka; Strauss, Gero

2006-03-01

For the pre-operative segmentation of CT neck datasets, we developed the software assistant NeckVision. The relevant anatomical structures for neck dissection planning can be segmented and the resulting patient-specific 3D-models are visualized afterwards in another software system for intervention planning. As a first step, we examined the appropriateness of elementary segmentation techniques based on gray values and contour information to extract the structures in the neck region from CT data. Region growing, interactive watershed transformation and live-wire are employed for segmentation of different target structures. It is also examined, which of the segmentation tasks can be automated. Based on this analysis, the software assistant NeckVision was developed to optimally support the workflow of image analysis for clinicians. The usability of NeckVision was tested within a first evaluation with four otorhinolaryngologists from the university hospital of Leipzig, four computer scientists from the university of Magdeburg and two laymen in both fields.

The Incremental Multiresolution Matrix Factorization Algorithm

PubMed Central

Ithapu, Vamsi K.; Kondor, Risi; Johnson, Sterling C.; Singh, Vikas

2017-01-01

Multiresolution analysis and matrix factorization are foundational tools in computer vision. In this work, we study the interface between these two distinct topics and obtain techniques to uncover hierarchical block structure in symmetric matrices – an important aspect in the success of many vision problems. Our new algorithm, the incremental multiresolution matrix factorization, uncovers such structure one feature at a time, and hence scales well to large matrices. We describe how this multiscale analysis goes much farther than what a direct “global” factorization of the data can identify. We evaluate the efficacy of the resulting factorizations for relative leveraging within regression tasks using medical imaging data. We also use the factorization on representations learned by popular deep networks, providing evidence of their ability to infer semantic relationships even when they are not explicitly trained to do so. We show that this algorithm can be used as an exploratory tool to improve the network architecture, and within numerous other settings in vision. PMID:29416293

(Computer) Vision without Sight

PubMed Central

Manduchi, Roberto; Coughlan, James

2012-01-01

Computer vision holds great promise for helping persons with blindness or visual impairments (VI) to interpret and explore the visual world. To this end, it is worthwhile to assess the situation critically by understanding the actual needs of the VI population and which of these needs might be addressed by computer vision. This article reviews the types of assistive technology application areas that have already been developed for VI, and the possible roles that computer vision can play in facilitating these applications. We discuss how appropriate user interfaces are designed to translate the output of computer vision algorithms into information that the user can quickly and safely act upon, and how system-level characteristics affect the overall usability of an assistive technology. Finally, we conclude by highlighting a few novel and intriguing areas of application of computer vision to assistive technology. PMID:22815563

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation.

PubMed

Carlson, Jordan A; Liu, Bo; Sallis, James F; Kerr, Jacqueline; Hipp, J Aaron; Staggs, Vincent S; Papa, Amy; Dean, Kelsey; Vasconcelos, Nuno M

2017-12-01

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82-0.98). Total MET-minutes were slightly underestimated by 9.3-17.1% and the ICCs were good (0.68-0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings.

Automated Ecological Assessment of Physical Activity: Advancing Direct Observation

PubMed Central

Carlson, Jordan A.; Liu, Bo; Sallis, James F.; Kerr, Jacqueline; Papa, Amy; Dean, Kelsey; Vasconcelos, Nuno M.

2017-01-01

Technological advances provide opportunities for automating direct observations of physical activity, which allow for continuous monitoring and feedback. This pilot study evaluated the initial validity of computer vision algorithms for ecological assessment of physical activity. The sample comprised 6630 seconds per camera (three cameras in total) of video capturing up to nine participants engaged in sitting, standing, walking, and jogging in an open outdoor space while wearing accelerometers. Computer vision algorithms were developed to assess the number and proportion of people in sedentary, light, moderate, and vigorous activity, and group-based metabolic equivalents of tasks (MET)-minutes. Means and standard deviations (SD) of bias/difference values, and intraclass correlation coefficients (ICC) assessed the criterion validity compared to accelerometry separately for each camera. The number and proportion of participants sedentary and in moderate-to-vigorous physical activity (MVPA) had small biases (within 20% of the criterion mean) and the ICCs were excellent (0.82–0.98). Total MET-minutes were slightly underestimated by 9.3–17.1% and the ICCs were good (0.68–0.79). The standard deviations of the bias estimates were moderate-to-large relative to the means. The computer vision algorithms appeared to have acceptable sample-level validity (i.e., across a sample of time intervals) and are promising for automated ecological assessment of activity in open outdoor settings, but further development and testing is needed before such tools can be used in a diverse range of settings. PMID:29194358

Reservoir Maintenance and Development Task Report for the DOE Geothermal Technologies Office GeoVision Study.

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

Lowry, Thomas Stephen; Finger, John T.; Carrigan, Charles R.

This report documents the key findings from the Reservoir Maintenance and Development (RM&D) Task of the U.S. Department of Energy's (DOE), Geothermal Technologies Office (GTO) Geothermal Vision Study (GeoVision Study). The GeoVision Study had the objective of conducting analyses of future geothermal growth based on sets of current and future geothermal technology developments. The RM&D Task is one of seven tasks within the GeoVision Study with the others being, Exploration and Confirmation, Potential to Penetration, Institutional Market Barriers, Environmental and Social Impacts, Thermal Applications, and Hybrid Systems. The full set of findings and the details of the GeoVision Study canmore » be found in the final GeoVision Study report on the DOE-GTO website. As applied here, RM&D refers to the activities associated with developing, exploiting, and maintaining a known geothermal resource. It assumes that the site has already been vetted and that the resource has been evaluated to be of sufficient quality to move towards full-scale development. It also assumes that the resource is to be developed for power generation, as opposed to low-temperature or direct use applications. This document presents the key factors influencing RM&D from both a technological and operational standpoint and provides a baseline of its current state. It also looks forward to describe areas of research and development that must be pursued if the development geothermal energy is to reach its full potential.« less

Pattern recognition for passive polarimetric data using nonparametric classifiers

NASA Astrophysics Data System (ADS)

Thilak, Vimal; Saini, Jatinder; Voelz, David G.; Creusere, Charles D.

2005-08-01

Passive polarization based imaging is a useful tool in computer vision and pattern recognition. A passive polarization imaging system forms a polarimetric image from the reflection of ambient light that contains useful information for computer vision tasks such as object detection (classification) and recognition. Applications of polarization based pattern recognition include material classification and automatic shape recognition. In this paper, we present two target detection algorithms for images captured by a passive polarimetric imaging system. The proposed detection algorithms are based on Bayesian decision theory. In these approaches, an object can belong to one of any given number classes and classification involves making decisions that minimize the average probability of making incorrect decisions. This minimum is achieved by assigning an object to the class that maximizes the a posteriori probability. Computing a posteriori probabilities requires estimates of class conditional probability density functions (likelihoods) and prior probabilities. A Probabilistic neural network (PNN), which is a nonparametric method that can compute Bayes optimal boundaries, and a -nearest neighbor (KNN) classifier, is used for density estimation and classification. The proposed algorithms are applied to polarimetric image data gathered in the laboratory with a liquid crystal-based system. The experimental results validate the effectiveness of the above algorithms for target detection from polarimetric data.

Interactive Tools for Measuring Visual Scanning Performance and Reaction Time.

PubMed

Brooks, Johnell; Seeanner, Julia; Hennessy, Sarah; Manganelli, Joseph; Crisler, Matthew; Rosopa, Patrick; Jenkins, Casey; Anderson, Michael; Drouin, Nathalie; Belle, Leah; Truesdail, Constance; Tanner, Stephanie

Occupational therapists are constantly searching for engaging, high-technology interactive tasks that provide immediate feedback to evaluate and train clients with visual scanning deficits. This study examined the relationship between two tools: the VISION COACH™ interactive light board and the Functional Object Detection © (FOD) Advanced driving simulator scenario. Fifty-four healthy drivers, ages 21-66 yr, were divided into three age groups. Participants performed braking response and visual target (E) detection tasks of the FOD Advanced driving scenario, followed by two sets of three trials using the VISION COACH Full Field 60 task. Results showed no significant effect of age on FOD Advanced performance but a significant effect of age on VISION COACH performance. Correlations showed that participants' performance on both braking and E detection tasks were significantly positively correlated with performance on the VISION COACH (.37 < r < .40, p < .01). These tools provide new options for therapists. Copyright © 2017 by the American Occupational Therapy Association, Inc.

Optoelectronic instrumentation enhancement using data mining feedback for a 3D measurement system

NASA Astrophysics Data System (ADS)

Flores-Fuentes, Wendy; Sergiyenko, Oleg; Gonzalez-Navarro, Félix F.; Rivas-López, Moisés; Hernandez-Balbuena, Daniel; Rodríguez-Quiñonez, Julio C.; Tyrsa, Vera; Lindner, Lars

2016-12-01

3D measurement by a cyber-physical system based on optoelectronic scanning instrumentation has been enhanced by outliers and regression data mining feedback. The prototype has applications in (1) industrial manufacturing systems that include: robotic machinery, embedded vision, and motion control, (2) health care systems for measurement scanning, and (3) infrastructure by providing structural health monitoring. This paper presents new research performed in data processing of a 3D measurement vision sensing database. Outliers from multivariate data have been detected and removal to improve artificial intelligence regression algorithm results. Physical measurement error regression data has been used for 3D measurements error correction. Concluding, that the joint of physical phenomena, measurement and computation is an effectiveness action for feedback loops in the control of industrial, medical and civil tasks.

Man-machine interactive imaging and data processing using high-speed digital mass storage

NASA Technical Reports Server (NTRS)

Alsberg, H.; Nathan, R.

1975-01-01

The role of vision in teleoperation has been recognized as an important element in the man-machine control loop. In most applications of remote manipulation, direct vision cannot be used. To overcome this handicap, the human operator's control capabilities are augmented by a television system. This medium provides a practical and useful link between workspace and the control station from which the operator perform his tasks. Human performance deteriorates when the images are degraded as a result of instrumental and transmission limitations. Image enhancement is used to bring out selected qualities in a picture to increase the perception of the observer. A general purpose digital computer, an extensive special purpose software system is used to perform an almost unlimited repertoire of processing operations.

Vision requirements for Space Station applications

NASA Technical Reports Server (NTRS)

Crouse, K. R.

1985-01-01

Problems which will be encountered by computer vision systems in Space Station operations are discussed, along with solutions be examined at Johnson Space Station. Lighting cannot be controlled in space, nor can the random presence of reflective surfaces. Task-oriented capabilities are to include docking to moving objects, identification of unexpected objects during autonomous flights to different orbits, and diagnoses of damage and repair requirements for autonomous Space Station inspection robots. The approaches being examined to provide these and other capabilities are television IR sensors, advanced pattern recognition programs feeding on data from laser probes, laser radar for robot eyesight and arrays of SMART sensors for automated location and tracking of target objects. Attention is also being given to liquid crystal light valves for optical processing of images for comparisons with on-board electronic libraries of images.

Modelling and representation issues in automated feature extraction from aerial and satellite images

NASA Astrophysics Data System (ADS)

Sowmya, Arcot; Trinder, John

New digital systems for the processing of photogrammetric and remote sensing images have led to new approaches to information extraction for mapping and Geographic Information System (GIS) applications, with the expectation that data can become more readily available at a lower cost and with greater currency. Demands for mapping and GIS data are increasing as well for environmental assessment and monitoring. Hence, researchers from the fields of photogrammetry and remote sensing, as well as computer vision and artificial intelligence, are bringing together their particular skills for automating these tasks of information extraction. The paper will review some of the approaches used in knowledge representation and modelling for machine vision, and give examples of their applications in research for image understanding of aerial and satellite imagery.

Gamut relativity: a new computational approach to brightness and lightness perception.

PubMed

Vladusich, Tony

2013-01-09

This article deconstructs the conventional theory that "brightness" and "lightness" constitute perceptual dimensions corresponding to the physical dimensions of luminance and reflectance, and builds in its place the theory that brightness and lightness correspond to computationally defined "modes," rather than dimensions, of perception. According to the theory, called gamut relativity, "blackness" and "whiteness" constitute the perceptual dimensions (forming a two-dimensional "blackness-whiteness" space) underlying achromatic color perception (black, white, and gray shades). These perceptual dimensions are postulated to be related to the neural activity levels in the ON and OFF channels of vision. The theory unifies and generalizes a number of extant concepts in the brightness and lightness literature, such as simultaneous contrast, anchoring, and scission, and quantitatively simulates several challenging perceptual phenomena, including the staircase Gelb effect and the effects of task instructions on achromatic color-matching behavior, all with a single free parameter. The theory also provides a new conception of achromatic color constancy in terms of the relative distances between points in blackness-whiteness space. The theory suggests a host of striking conclusions, the most important of which is that the perceptual dimensions of vision should be generically specified according to the computational properties of the brain, rather than in terms of "reified" physical dimensions. This new approach replaces the computational goal of estimating absolute physical quantities ("inverse optics") with the goal of computing object properties relatively.

ROBOSIGHT: Robotic Vision System For Inspection And Manipulation

NASA Astrophysics Data System (ADS)

Trivedi, Mohan M.; Chen, ChuXin; Marapane, Suresh

1989-02-01

Vision is an important sensory modality that can be used for deriving information critical to the proper, efficient, flexible, and safe operation of an intelligent robot. Vision systems are uti-lized for developing higher level interpretation of the nature of a robotic workspace using images acquired by cameras mounted on a robot. Such information can be useful for tasks such as object recognition, object location, object inspection, obstacle avoidance and navigation. In this paper we describe efforts directed towards developing a vision system useful for performing various robotic inspection and manipulation tasks. The system utilizes gray scale images and can be viewed as a model-based system. It includes general purpose image analysis modules as well as special purpose, task dependent object status recognition modules. Experiments are described to verify the robust performance of the integrated system using a robotic testbed.

How dolphins see the world: a comparison with chimpanzees and humans.

PubMed

Tomonaga, Masaki; Uwano, Yuka; Saito, Toyoshi

2014-01-16

Bottlenose dolphins use auditory (or echoic) information to recognise their environments, and many studies have described their echolocation perception abilities. However, relatively few systematic studies have examined their visual perception. We tested dolphins on a visual-matching task using two-dimensional geometric forms including various features. Based on error patterns, we used multidimensional scaling to analyse perceptual similarities among stimuli. In addition to dolphins, we conducted comparable tests with terrestrial species: chimpanzees were tested on a computer-controlled matching task and humans were tested on a rating task. The overall perceptual similarities among stimuli in dolphins were similar to those in the two species of primates. These results clearly indicate that the visual world is perceived similarly by the three species of mammals, even though each has adapted to a different environment and has differing degrees of dependence on vision.

Research and applications: Artificial intelligence

NASA Technical Reports Server (NTRS)

Raphael, B.; Duda, R. O.; Fikes, R. E.; Hart, P. E.; Nilsson, N. J.; Thorndyke, P. W.; Wilber, B. M.

1971-01-01

Research in the field of artificial intelligence is discussed. The focus of recent work has been the design, implementation, and integration of a completely new system for the control of a robot that plans, learns, and carries out tasks autonomously in a real laboratory environment. The computer implementation of low-level and intermediate-level actions; routines for automated vision; and the planning, generalization, and execution mechanisms are reported. A scenario that demonstrates the approximate capabilities of the current version of the entire robot system is presented.

Analysis of Brown camera distortion model

NASA Astrophysics Data System (ADS)

Nowakowski, Artur; Skarbek, Władysław

2013-10-01

Contemporary image acquisition devices introduce optical distortion into image. It results in pixel displacement and therefore needs to be compensated for many computer vision applications. The distortion is usually modeled by the Brown distortion model, which parameters can be included in camera calibration task. In this paper we describe original model, its dependencies and analyze orthogonality with regard to radius for its decentering distortion component. We also report experiments with camera calibration algorithm included in OpenCV library, especially a stability of distortion parameters estimation is evaluated.

Expert Systems for the Scheduling of Image Processing Tasks on a Parallel Processing System

DTIC Science & Technology

1986-12-01

existed for over twenty years. Credit for designing and implementing the first computer vision system is usually given to L. G . Roberts [Robe65]. With...hardware differences between systems. 44 LIST OF REFERENCES [Adam82] G . B. Adams III and H. J. Siegel, "The Extra Stage Cube: a Fault-Tolerant...Academic Press, 1985 [Robe65] L. G . Roberts, "Machine Perception of Three-Dimensional Solids," in Optical and Electro-Optical Information Processing, ed. J

High accuracy position method based on computer vision and error analysis

NASA Astrophysics Data System (ADS)

Chen, Shihao; Shi, Zhongke

2003-09-01

The study of high accuracy position system is becoming the hotspot in the field of autocontrol. And positioning is one of the most researched tasks in vision system. So we decide to solve the object locating by using the image processing method. This paper describes a new method of high accuracy positioning method through vision system. In the proposed method, an edge-detection filter is designed for a certain running condition. Here, the filter contains two mainly parts: one is image-processing module, this module is to implement edge detection, it contains of multi-level threshold self-adapting segmentation, edge-detection and edge filter; the other one is object-locating module, it is to point out the location of each object in high accurate, and it is made up of medium-filtering and curve-fitting. This paper gives some analysis error for the method to prove the feasibility of vision in position detecting. Finally, to verify the availability of the method, an example of positioning worktable, which is using the proposed method, is given at the end of the paper. Results show that the method can accurately detect the position of measured object and identify object attitude.

Evaluation of functional color vision requirements and current color vision screening tests for air traffic control specialists.

DOT National Transportation Integrated Search

1990-08-01

An experiment was conducted to evaluate the relation of type and degree of color vision deficiency and aeromedical color vision screening test scores to performance of color-dependent tasks of Air Traffic Control Specialists. The subjects included 37...

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'.

Object tracking with stereo vision

NASA Technical Reports Server (NTRS)

Huber, Eric

1994-01-01

A real-time active stereo vision system incorporating gaze control and task directed vision is described. Emphasis is placed on object tracking and object size and shape determination. Techniques include motion-centroid tracking, depth tracking, and contour tracking.

[Comparison study between biological vision and computer vision].

PubMed

Liu, W; Yuan, X G; Yang, C X; Liu, Z Q; Wang, R

2001-08-01

The development and bearing of biology vision in structure and mechanism were discussed, especially on the aspects including anatomical structure of biological vision, tentative classification of reception field, parallel processing of visual information, feedback and conformity effect of visual cortical, and so on. The new advance in the field was introduced through the study of the morphology of biological vision. Besides, comparison between biological vision and computer vision was made, and their similarities and differences were pointed out.

Towards an assistive peripheral visual prosthesis for long-term treatment of retinitis pigmentosa: evaluating mobility performance in immersive simulations

NASA Astrophysics Data System (ADS)

Zapf, Marc Patrick H.; Boon, Mei-Ying; Matteucci, Paul B.; Lovell, Nigel H.; Suaning, Gregg J.

2015-06-01

Objective. The prospective efficacy of a future peripheral retinal prosthesis complementing residual vision to raise mobility performance in non-end stage retinitis pigmentosa (RP) was evaluated using simulated prosthetic vision (SPV). Approach. Normally sighted volunteers were fitted with a wide-angle head-mounted display and carried out mobility tasks in photorealistic virtual pedestrian scenarios. Circumvention of low-lying obstacles, path following, and navigating around static and moving pedestrians were performed either with central simulated residual vision of 10° alone or enhanced by assistive SPV in the lower and lateral peripheral visual field (VF). Three layouts of assistive vision corresponding to hypothetical electrode array layouts were compared, emphasizing higher visual acuity, a wider visual angle, or eccentricity-dependent acuity across an intermediate angle. Movement speed, task time, distance walked and collisions with the environment were analysed as performance measures. Main results. Circumvention of low-lying obstacles was improved with all tested configurations of assistive SPV. Higher-acuity assistive vision allowed for greatest improvement in walking speeds—14% above that of plain residual vision, while only wide-angle and eccentricity-dependent vision significantly reduced the number of collisions—both by 21%. Navigating around pedestrians, there were significant reductions in collisions with static pedestrians by 33% and task time by 7.7% with the higher-acuity layout. Following a path, higher-acuity assistive vision increased walking speed by 9%, and decreased collisions with stationary cars by 18%. Significance. The ability of assistive peripheral prosthetic vision to improve mobility performance in persons with constricted VFs has been demonstrated. In a prospective peripheral visual prosthesis, electrode array designs need to be carefully tailored to the scope of tasks in which a device aims to assist. We posit that maximum benefit might come from application alongside existing visual aids, to further raise life quality of persons living through the prolonged early stages of RP.

Integration of local motion is normal in amblyopia

NASA Astrophysics Data System (ADS)

Hess, Robert F.; Mansouri, Behzad; Dakin, Steven C.; Allen, Harriet A.

2006-05-01

We investigate the global integration of local motion direction signals in amblyopia, in a task where performance is equated between normal and amblyopic eyes at the single element level. We use an equivalent noise model to derive the parameters of internal noise and number of samples, both of which we show are normal in amblyopia for this task. This result is in apparent conflict with a previous study in amblyopes showing that global motion processing is defective in global coherence tasks [Vision Res. 43, 729 (2003)]. A similar discrepancy between the normalcy of signal integration [Vision Res. 44, 2955 (2004)] and anomalous global coherence form processing has also been reported [Vision Res. 45, 449 (2005)]. We suggest that these discrepancies for form and motion processing in amblyopia point to a selective problem in separating signal from noise in the typical global coherence task.

A semi-automatic annotation tool for cooking video

NASA Astrophysics Data System (ADS)

Bianco, Simone; Ciocca, Gianluigi; Napoletano, Paolo; Schettini, Raimondo; Margherita, Roberto; Marini, Gianluca; Gianforme, Giorgio; Pantaleo, Giuseppe

2013-03-01

In order to create a cooking assistant application to guide the users in the preparation of the dishes relevant to their profile diets and food preferences, it is necessary to accurately annotate the video recipes, identifying and tracking the foods of the cook. These videos present particular annotation challenges such as frequent occlusions, food appearance changes, etc. Manually annotate the videos is a time-consuming, tedious and error-prone task. Fully automatic tools that integrate computer vision algorithms to extract and identify the elements of interest are not error free, and false positive and false negative detections need to be corrected in a post-processing stage. We present an interactive, semi-automatic tool for the annotation of cooking videos that integrates computer vision techniques under the supervision of the user. The annotation accuracy is increased with respect to completely automatic tools and the human effort is reduced with respect to completely manual ones. The performance and usability of the proposed tool are evaluated on the basis of the time and effort required to annotate the same video sequences.

Analysis of coherent dynamical processes through computer vision

NASA Astrophysics Data System (ADS)

Hack, M. J. Philipp

2016-11-01

Visualizations of turbulent boundary layers show an abundance of characteristic arc-shaped structures whose apparent similarity suggests a common origin in a coherent dynamical process. While the structures have been likened to the hairpin vortices observed in the late stages of transitional flow, a consistent description of the underlying mechanism has remained elusive. Detailed studies are complicated by the chaotic nature of turbulence which modulates each manifestation of the process and which renders the isolation of individual structures a challenging task. The present study applies methods from the field of computer vision to capture the time evolution of turbulent flow features and explore the associated physical mechanisms. The algorithm uses morphological operations to condense the structure of the turbulent flow field into a graph described by nodes and links. The low-dimensional geometric information is stored in a database and allows the identification and analysis of equivalent dynamical processes across multiple scales. The framework is not limited to turbulent boundary layers and can also be applied to different types of flows as well as problems from other fields of science.

Proteus: a reconfigurable computational network for computer vision

NASA Astrophysics Data System (ADS)

Haralick, Robert M.; Somani, Arun K.; Wittenbrink, Craig M.; Johnson, Robert; Cooper, Kenneth; Shapiro, Linda G.; Phillips, Ihsin T.; Hwang, Jenq N.; Cheung, William; Yao, Yung H.; Chen, Chung-Ho; Yang, Larry; Daugherty, Brian; Lorbeski, Bob; Loving, Kent; Miller, Tom; Parkins, Larye; Soos, Steven L.

1992-04-01

The Proteus architecture is a highly parallel MIMD, multiple instruction, multiple-data machine, optimized for large granularity tasks such as machine vision and image processing The system can achieve 20 Giga-flops (80 Giga-flops peak). It accepts data via multiple serial links at a rate of up to 640 megabytes/second. The system employs a hierarchical reconfigurable interconnection network with the highest level being a circuit switched Enhanced Hypercube serial interconnection network for internal data transfers. The system is designed to use 256 to 1,024 RISC processors. The processors use one megabyte external Read/Write Allocating Caches for reduced multiprocessor contention. The system detects, locates, and replaces faulty subsystems using redundant hardware to facilitate fault tolerance. The parallelism is directly controllable through an advanced software system for partitioning, scheduling, and development. System software includes a translator for the INSIGHT language, a parallel debugger, low and high level simulators, and a message passing system for all control needs. Image processing application software includes a variety of point operators neighborhood, operators, convolution, and the mathematical morphology operations of binary and gray scale dilation, erosion, opening, and closing.

The Ilac-Project Supporting Ancient Coin Classification by Means of Image Analysis

NASA Astrophysics Data System (ADS)

Kavelar, A.; Zambanini, S.; Kampel, M.; Vondrovec, K.; Siegl, K.

2013-07-01

This paper presents the ILAC project, which aims at the development of an automated image-based classification system for ancient Roman Republican coins. The benefits of such a system are manifold: operating at the suture between computer vision and numismatics, ILAC can reduce the day-to-day workload of numismatists by assisting them in classification tasks and providing a preselection of suitable coin classes. This is especially helpful for large coin hoard findings comprising several thousands of coins. Furthermore, this system could be implemented in an online platform for hobby numismatists, allowing them to access background information about their coin collection by simply uploading a photo of obverse and reverse for the coin of interest. ILAC explores different computer vision techniques and their combinations for the use of image-based coin recognition. Some of these methods, such as image matching, use the entire coin image in the classification process, while symbol or legend recognition exploit certain characteristics of the coin imagery. An overview of the methods explored so far and the respective experiments is given as well as an outlook on the next steps of the project.

Measuring vigilance decrement using computer vision assisted eye tracking in dynamic naturalistic environments.

PubMed

Bodala, Indu P; Abbasi, Nida I; Yu Sun; Bezerianos, Anastasios; Al-Nashash, Hasan; Thakor, Nitish V

2017-07-01

Eye tracking offers a practical solution for monitoring cognitive performance in real world tasks. However, eye tracking in dynamic environments is difficult due to high spatial and temporal variation of stimuli, needing further and thorough investigation. In this paper, we study the possibility of developing a novel computer vision assisted eye tracking analysis by using fixations. Eye movement data is obtained from a long duration naturalistic driving experiment. Source invariant feature transform (SIFT) algorithm was implemented using VLFeat toolbox to identify multiple areas of interest (AOIs). A new measure called `fixation score' was defined to understand the dynamics of fixation position between the target AOI and the non target AOIs. Fixation score is maximum when the subjects focus on the target AOI and diminishes when they gaze at the non-target AOIs. Statistically significant negative correlation was found between fixation score and reaction time data (r =-0.2253 and p<;0.05). This implies that with vigilance decrement, the fixation score decreases due to visual attention shifting away from the target objects resulting in an increase in the reaction time.

Optical Characterization of Wide Field-of-View Night Vision Devices

DTIC Science & Technology

1999-01-01

This paper has been cleared by ASC 99-2354 Optical Characterization of Wide Field-Of-View Night Vision Devices Peter L. Marasco and H. Lee Task Air...the SAFE SocietyÕs 36th Annual Symposium. Task, H.L., Hartman, R., Marasco , P.L., Zobel, A, (1993) Methods for measuring characteristics of night

Piaget's Water-Level Task: The Impact of Vision on Performance

ERIC Educational Resources Information Center

Papadopoulos, Konstantinos; Koustriava, Eleni

2011-01-01

In the present study, the aim was to examine the differences in performance between children and adolescents with visual impairment and sighted peers in the water-level task. Twenty-eight individuals with visual impairments, 14 individuals with blindness and 14 individuals with low vision, and 28 sighted individuals participated in the present…

Cognitive programs: software for attention's executive

PubMed Central

Tsotsos, John K.; Kruijne, Wouter

2014-01-01

What are the computational tasks that an executive controller for visual attention must solve? This question is posed in the context of the Selective Tuning model of attention. The range of required computations go beyond top-down bias signals or region-of-interest determinations, and must deal with overt and covert fixations, process timing and synchronization, information routing, memory, matching control to task, spatial localization, priming, and coordination of bottom-up with top-down information. During task execution, results must be monitored to ensure the expected results. This description includes the kinds of elements that are common in the control of any kind of complex machine or system. We seek a mechanistic integration of the above, in other words, algorithms that accomplish control. Such algorithms operate on representations, transforming a representation of one kind into another, which then forms the input to yet another algorithm. Cognitive Programs (CPs) are hypothesized to capture exactly such representational transformations via stepwise sequences of operations. CPs, an updated and modernized offspring of Ullman's Visual Routines, impose an algorithmic structure to the set of attentional functions and play a role in the overall shaping of attentional modulation of the visual system so that it provides its best performance. This requires that we consider the visual system as a dynamic, yet general-purpose processor tuned to the task and input of the moment. This differs dramatically from the almost universal cognitive and computational views, which regard vision as a passively observing module to which simple questions about percepts can be posed, regardless of task. Differing from Visual Routines, CPs explicitly involve the critical elements of Visual Task Executive (vTE), Visual Attention Executive (vAE), and Visual Working Memory (vWM). Cognitive Programs provide the software that directs the actions of the Selective Tuning model of visual attention. PMID:25505430

Stereo Vision Inside Tire

DTIC Science & Technology

2015-08-21

using the Open Computer Vision ( OpenCV ) libraries [6] for computer vision and the Qt library [7] for the user interface. The software has the...depth. The software application calibrates the cameras using the plane based calibration model from the OpenCV calib3D module and allows the...6] OpenCV . 2015. OpenCV Open Source Computer Vision. [Online]. Available at: opencv.org [Accessed]: 09/01/2015. [7] Qt. 2015. Qt Project home

Parallel Architectures and Parallel Algorithms for Integrated Vision Systems. Ph.D. Thesis

NASA Technical Reports Server (NTRS)

Choudhary, Alok Nidhi

1989-01-01

Computer vision is regarded as one of the most complex and computationally intensive problems. An integrated vision system (IVS) is a system that uses vision algorithms from all levels of processing to perform for a high level application (e.g., object recognition). An IVS normally involves algorithms from low level, intermediate level, and high level vision. Designing parallel architectures for vision systems is of tremendous interest to researchers. Several issues are addressed in parallel architectures and parallel algorithms for integrated vision systems.

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

PubMed Central

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

2014-01-01

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

The impact on midlevel vision of statistically optimal divisive normalization in V1

PubMed Central

Coen-Cagli, Ruben; Schwartz, Odelia

2013-01-01

The first two areas of the primate visual cortex (V1, V2) provide a paradigmatic example of hierarchical computation in the brain. However, neither the functional properties of V2 nor the interactions between the two areas are well understood. One key aspect is that the statistics of the inputs received by V2 depend on the nonlinear response properties of V1. Here, we focused on divisive normalization, a canonical nonlinear computation that is observed in many neural areas and modalities. We simulated V1 responses with (and without) different forms of surround normalization derived from statistical models of natural scenes, including canonical normalization and a statistically optimal extension that accounted for image nonhomogeneities. The statistics of the V1 population responses differed markedly across models. We then addressed how V2 receptive fields pool the responses of V1 model units with different tuning. We assumed this is achieved by learning without supervision a linear representation that removes correlations, which could be accomplished with principal component analysis. This approach revealed V2-like feature selectivity when we used the optimal normalization and, to a lesser extent, the canonical one but not in the absence of both. We compared the resulting two-stage models on two perceptual tasks; while models encompassing V1 surround normalization performed better at object recognition, only statistically optimal normalization provided systematic advantages in a task more closely matched to midlevel vision, namely figure/ground judgment. Our results suggest that experiments probing midlevel areas might benefit from using stimuli designed to engage the computations that characterize V1 optimality. PMID:23857950

Five-year safety and performance results from the Argus II Retinal Prosthesis System clinical trial

PubMed Central

da Cruz, Lyndon; Dorn, Jessy D.; Humayun, Mark S.; Dagnelie, Gislin; Handa, James; Barale, Pierre-Olivier; Sahel, José-Alain; Stanga, Paulo E.; Hafezi, Farhad; Safran, Avinoam B.; Salzmann, Joel; Santos, Arturo; Birch, David; Spencer, Rand; Cideciyan, Artur V.; de Juan, Eugene; Duncan, Jacque L.; Eliott, Dean; Fawzi, Amani; Olmos de Koo, Lisa C.; Ho, Allen C.; Brown, Gary; Haller, Julia; Regillo, Carl; Del Priore, Lucian V.; Arditi, Aries; Greenberg, Robert J.

2016-01-01

Purpose The Argus® II Retinal Prosthesis System (Second Sight Medical Products, Inc., Sylmar, CA) was developed to restore some vision to patients blind from retinitis pigmentosa (RP) or outer retinal degeneration. A clinical trial was initiated in 2006 to study the long-term safety and efficacy of the Argus II System in patients with bare or no light perception due to end-stage RP. Design The study is a prospective, multicenter, single-arm, clinical trial. Within-patient controls included the non-implanted fellow eye and patients' native residual vision compared to their vision when using the System. Subjects There were 30 subjects in 10 centers in the U.S. and Europe. Methods The worse-seeing eye of blind patients was implanted with the Argus II System. Patients wore glasses mounted with a small camera and a video processor that converted images into stimulation patterns sent to the electrode array on the retina. Main Outcome Measures The primary outcome measures were safety (the number, seriousness, and relatedness of adverse events) and visual function, as measured by three computer-based, objective tests. Secondary measures included functional vision performance on objectively-scored real-world tasks. Results Twenty-four out of 30 patients remained implanted with functioning Argus II Systems at 5 years post-implant. Only one additional serious adverse event was experienced since the 3-year time point. Patients performed significantly better with the System ON than OFF on all visual function tests and functional vision tasks. Conclusions The five-year results of the Argus II trial support the long-term safety profile and benefit of the Argus II System for patients blind from RP. The Argus II is the first and only retinal implant to have market approval in the European Economic Area, the United States, and Canada. PMID:27453256

Five-Year Safety and Performance Results from the Argus II Retinal Prosthesis System Clinical Trial.

PubMed

da Cruz, Lyndon; Dorn, Jessy D; Humayun, Mark S; Dagnelie, Gislin; Handa, James; Barale, Pierre-Olivier; Sahel, José-Alain; Stanga, Paulo E; Hafezi, Farhad; Safran, Avinoam B; Salzmann, Joel; Santos, Arturo; Birch, David; Spencer, Rand; Cideciyan, Artur V; de Juan, Eugene; Duncan, Jacque L; Eliott, Dean; Fawzi, Amani; Olmos de Koo, Lisa C; Ho, Allen C; Brown, Gary; Haller, Julia; Regillo, Carl; Del Priore, Lucian V; Arditi, Aries; Greenberg, Robert J

2016-10-01

The Argus II Retinal Prosthesis System (Second Sight Medical Products, Inc, Sylmar, CA) was developed to restore some vision to patients blind as a result of retinitis pigmentosa (RP) or outer retinal degeneration. A clinical trial was initiated in 2006 to study the long-term safety and efficacy of the Argus II System in patients with bare or no light perception resulting from end-stage RP. Prospective, multicenter, single-arm clinical trial. Within-patient controls included the nonimplanted fellow eye and patients' native residual vision compared with their vision with the Argus II. Thirty participants in 10 centers in the United States and Europe. The worse-seeing eye of blind patients was implanted with the Argus II. Patients wore glasses mounted with a small camera and a video processor that converted images into stimulation patterns sent to the electrode array on the retina. The primary outcome measures were safety (the number, seriousness, and relatedness of adverse events) and visual function, as measured by 3 computer-based, objective tests. Secondary measures included functional vision performance on objectively scored real-world tasks. Twenty-four of 30 patients remained implanted with functioning Argus II Systems at 5 years after implantation. Only 1 additional serious adverse event was experienced after the 3-year time point. Patients performed significantly better with the Argus II on than off on all visual function tests and functional vision tasks. The 5-year results of the Argus II trial support the long-term safety profile and benefit of the Argus II System for patients blind as a result of RP. The Argus II is the first and only retinal implant to have market approval in the European Economic Area, the United States, and Canada. Copyright © 2016 American Academy of Ophthalmology. Published by Elsevier Inc. All rights reserved.

Variational optical flow estimation for images with spectral and photometric sensor diversity

NASA Astrophysics Data System (ADS)

Bengtsson, Tomas; McKelvey, Tomas; Lindström, Konstantin

2015-03-01

Motion estimation of objects in image sequences is an essential computer vision task. To this end, optical flow methods compute pixel-level motion, with the purpose of providing low-level input to higher-level algorithms and applications. Robust flow estimation is crucial for the success of applications, which in turn depends on the quality of the captured image data. This work explores the use of sensor diversity in the image data within a framework for variational optical flow. In particular, a custom image sensor setup intended for vehicle applications is tested. Experimental results demonstrate the improved flow estimation performance when IR sensitivity or flash illumination is added to the system.

Building brains for bodies

NASA Technical Reports Server (NTRS)

Brooks, Rodney Allen; Stein, Lynn Andrea

1994-01-01

We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.

A Comparative Study : Microprogrammed Vs Risc Architectures For Symbolic Processing

NASA Astrophysics Data System (ADS)

Heudin, J. C.; Metivier, C.; Demigny, D.; Maurin, T.; Zavidovique, B.; Devos, F.

1987-05-01

It is oftenclaimed that conventional computers are not well suited for human-like tasks : Vision (Image Processing), Intelligence (Symbolic Processing) ... In the particular case of Artificial Intelligence, dynamic type-checking is one example of basic task that must be improved. The solution implemented in most Lisp work-stations consists in a microprogrammed architecture with a tagged memory. Another way to gain efficiency is to design a well suited instruction set for symbolic processing, which reduces the semantic gap between the high level language and the machine code. In this framework, the RISC concept provides a convenient approach to study new architectures for symbolic processing. This paper compares both approaches and describes our projectof designing a compact symbolic processor for Artificial Intelligence applications.

Saliency detection by conditional generative adversarial network

NASA Astrophysics Data System (ADS)

Cai, Xiaoxu; Yu, Hui

2018-04-01

Detecting salient objects in images has been a fundamental problem in computer vision. In recent years, deep learning has shown its impressive performance in dealing with many kinds of vision tasks. In this paper, we propose a new method to detect salient objects by using Conditional Generative Adversarial Network (GAN). This type of network not only learns the mapping from RGB images to salient regions, but also learns a loss function for training the mapping. To the best of our knowledge, this is the first time that Conditional GAN has been used in salient object detection. We evaluate our saliency detection method on 2 large publicly available datasets with pixel accurate annotations. The experimental results have shown the significant and consistent improvements over the state-of-the-art method on a challenging dataset, and the testing speed is much faster.

Accommodation and convergence during sustained computer work.

PubMed

Collier, Juanita D; Rosenfield, Mark

2011-07-01

With computer usage becoming almost universal in contemporary society, the reported prevalence of computer vision syndrome (CVS) is extremely high. However, the precise physiological mechanisms underlying CVS remain unclear. Although abnormal accommodation and vergence responses have been cited as being responsible for the symptoms produced, there is little objective evidence to support this claim. Accordingly, this study measured both of these oculomotor parameters during a sustained period of computer use. Subjects (N = 20) were required to read text aloud from a laptop computer at a viewing distance of 50 cm for a sustained 30-minute period through their habitual refractive correction. At 2-minute intervals, the accommodative response (AR) to the computer screen was measured objectively using a Grand Seiko WAM 5500 optometer (Grand Seiko, Hiroshima, Japan). Additionally, the vergence response was assessed by measuring the associated phoria (AP), i.e., prism to eliminate fixation disparity, using a customized fixation disparity target that appeared on the computer screen. Subjects were asked to rate the degree of difficulty of the reading task on a scale from 1 to 10. Mean accommodation and AP values during the task were 1.07 diopters and 0.74∆ base-in (BI), respectively. The mean discomfort score was 4.9. No significant changes in accommodation or vergence were observed during the course of the 30-minute test period. There was no significant difference in the AR as a function of subjective difficulty. However, the mean AP for the subjects who reported the least and greatest discomfort during the task was 1.55∆ BI and 0, respectively (P = 0.02). CVS, after 30 minutes was worse in subjects exhibiting zero fixation disparity when compared with those subjects having a BI AP but does not appear to be related to differences in accommodation. A slightly reduced vergence response increases subject comfort during the task. Copyright © 2011 American Optometric Association. Published by Elsevier Inc. All rights reserved.

A method for medulloblastoma tumor differentiation based on convolutional neural networks and transfer learning

NASA Astrophysics Data System (ADS)

Cruz-Roa, Angel; Arévalo, John; Judkins, Alexander; Madabhushi, Anant; González, Fabio

2015-12-01

Convolutional neural networks (CNN) have been very successful at addressing different computer vision tasks thanks to their ability to learn image representations directly from large amounts of labeled data. Features learned from a dataset can be used to represent images from a different dataset via an approach called transfer learning. In this paper we apply transfer learning to the challenging task of medulloblastoma tumor differentiation. We compare two different CNN models which were previously trained in two different domains (natural and histopathology images). The first CNN is a state-of-the-art approach in computer vision, a large and deep CNN with 16-layers, Visual Geometry Group (VGG) CNN. The second (IBCa-CNN) is a 2-layer CNN trained for invasive breast cancer tumor classification. Both CNNs are used as visual feature extractors of histopathology image regions of anaplastic and non-anaplastic medulloblastoma tumor from digitized whole-slide images. The features from the two models are used, separately, to train a softmax classifier to discriminate between anaplastic and non-anaplastic medulloblastoma image regions. Experimental results show that the transfer learning approach produce competitive results in comparison with the state of the art approaches for IBCa detection. Results also show that features extracted from the IBCa-CNN have better performance in comparison with features extracted from the VGG-CNN. The former obtains 89.8% while the latter obtains 76.6% in terms of average accuracy.

Application of Multi-task Sparse Lasso Feature Extraction and Support Vector Machine Regression in the Stellar Atmospheric Parameterization

NASA Astrophysics Data System (ADS)

Gao, Wei; Li, Xiang-ru

2017-07-01

The multi-task learning takes the multiple tasks together to make analysis and calculation, so as to dig out the correlations among them, and therefore to improve the accuracy of the analyzed results. This kind of methods have been widely applied to the machine learning, pattern recognition, computer vision, and other related fields. This paper investigates the application of multi-task learning in estimating the stellar atmospheric parameters, including the surface temperature (Teff), surface gravitational acceleration (lg g), and chemical abundance ([Fe/H]). Firstly, the spectral features of the three stellar atmospheric parameters are extracted by using the multi-task sparse group Lasso algorithm, then the support vector machine is used to estimate the atmospheric physical parameters. The proposed scheme is evaluated on both the Sloan stellar spectra and the theoretical spectra computed from the Kurucz's New Opacity Distribution Function (NEWODF) model. The mean absolute errors (MAEs) on the Sloan spectra are: 0.0064 for lg (Teff /K), 0.1622 for lg (g/(cm · s-2)), and 0.1221 dex for [Fe/H]; the MAEs on the synthetic spectra are 0.0006 for lg (Teff /K), 0.0098 for lg (g/(cm · s-2)), and 0.0082 dex for [Fe/H]. Experimental results show that the proposed scheme has a rather high accuracy for the estimation of stellar atmospheric parameters.

Computer vision for foreign body detection and removal in the food industry

USDA-ARS?s Scientific Manuscript database

Computer vision inspection systems are often used for quality control, product grading, defect detection and other product evaluation issues. This chapter focuses on the use of computer vision inspection systems that detect foreign bodies and remove them from the product stream. Specifically, we wi...

Chapter 11. Quality evaluation of apple by computer vision

USDA-ARS?s Scientific Manuscript database

Apple is one of the most consumed fruits in the world, and there is a critical need for enhanced computer vision technology for quality assessment of apples. This chapter gives a comprehensive review on recent advances in various computer vision techniques for detecting surface and internal defects ...

Online Graph Completion: Multivariate Signal Recovery in Computer Vision.

PubMed

Kim, Won Hwa; Jalal, Mona; Hwang, Seongjae; Johnson, Sterling C; Singh, Vikas

2017-07-01

The adoption of "human-in-the-loop" paradigms in computer vision and machine learning is leading to various applications where the actual data acquisition (e.g., human supervision) and the underlying inference algorithms are closely interwined. While classical work in active learning provides effective solutions when the learning module involves classification and regression tasks, many practical issues such as partially observed measurements, financial constraints and even additional distributional or structural aspects of the data typically fall outside the scope of this treatment. For instance, with sequential acquisition of partial measurements of data that manifest as a matrix (or tensor), novel strategies for completion (or collaborative filtering) of the remaining entries have only been studied recently. Motivated by vision problems where we seek to annotate a large dataset of images via a crowdsourced platform or alternatively, complement results from a state-of-the-art object detector using human feedback, we study the "completion" problem defined on graphs, where requests for additional measurements must be made sequentially. We design the optimization model in the Fourier domain of the graph describing how ideas based on adaptive submodularity provide algorithms that work well in practice. On a large set of images collected from Imgur, we see promising results on images that are otherwise difficult to categorize. We also show applications to an experimental design problem in neuroimaging.

Development of an Age Band on the ManuVis for 3-Year-Old Children with Visual Impairments.

PubMed

Reimer, A M; Barsingerhorn, A D; Overvelde, A; Nijhuis-Van der Sanden, M W G; Boonstra, F N; Cox, R F A

2017-08-01

To compare fine motor performance of 3-year-old children with visual impairment with peers having normal vision, to provide reference scores for 3-year-old children with visual impairment on the ManuVis, and to assess inter-rater reliability. 26 children with visual impairment (mean age: 3 years 7 months (SD 3 months); 17 boys) and 28 children with normal vision (mean age: 3 years 7 months (SD 4 months); 14 boys) participated in the study. The ManuVis age band for 3-year-old children comprised two one-handed tasks, two two-handed tasks, and a pre-writing task. Children with visual impairment needed more time on all tasks (p < .01) and performed the pre-writing task less accurately than children with normal vision (p < .001). Children aged 42-47 months performed significantly faster on two tasks and had better total scores than children aged 36-41 months (p < .05). Inter-rater reliability was excellent (Intra-class Correlation Coefficient = 0.96-0.99). The ManuVis age band for 3-year-old children is appropriate to assess fine motor skills, and is sensitive to differences between children with visual impairment and normal vision and between half-year age groups. Reference scores are provided for 3-year-old children with visual impairment to identify delayed fine motor development.

Visual recognition and inference using dynamic overcomplete sparse learning.

PubMed

Murray, Joseph F; Kreutz-Delgado, Kenneth

2007-09-01

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

78 FR 63302 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

.... Ferris Mr. Ferris, 70, has had complete loss of vision in his right eye since 1991. The visual acuity in... sufficient vision to perform his driving tasks to operate a commercial vehicle.'' Mr. Ferris reported that he...

How dolphins see the world: A comparison with chimpanzees and humans

PubMed Central

Tomonaga, Masaki; Uwano, Yuka; Saito, Toyoshi

2014-01-01

Bottlenose dolphins use auditory (or echoic) information to recognise their environments, and many studies have described their echolocation perception abilities. However, relatively few systematic studies have examined their visual perception. We tested dolphins on a visual-matching task using two-dimensional geometric forms including various features. Based on error patterns, we used multidimensional scaling to analyse perceptual similarities among stimuli. In addition to dolphins, we conducted comparable tests with terrestrial species: chimpanzees were tested on a computer-controlled matching task and humans were tested on a rating task. The overall perceptual similarities among stimuli in dolphins were similar to those in the two species of primates. These results clearly indicate that the visual world is perceived similarly by the three species of mammals, even though each has adapted to a different environment and has differing degrees of dependence on vision. PMID:24435017

Static and dynamic postural control in low-vision and normal-vision adults.

PubMed

Tomomitsu, Mônica S V; Alonso, Angelica Castilho; Morimoto, Eurica; Bobbio, Tatiana G; Greve, Julia M D

2013-04-01

This study aimed to evaluate the influence of reduced visual information on postural control by comparing low-vision and normal-vision adults in static and dynamic conditions. Twenty-five low-vision subjects and twenty-five normal sighted adults were evaluated for static and dynamic balance using four protocols: 1) the Modified Clinical Test of Sensory Interaction on Balance on firm and foam surfaces with eyes opened and closed; 2) Unilateral Stance with eyes opened and closed; 3) Tandem Walk; and 4) Step Up/Over. The results showed that the low-vision group presented greater body sway compared with the normal vision during balance on a foam surface (p≤0.001), the Unilateral Stance test for both limbs (p≤0.001), and the Tandem Walk test. The low-vision group showed greater step width (p≤0.001) and slower gait speed (p≤0.004). In the Step Up/Over task, low-vision participants were more cautious in stepping up (right p≤0.005 and left p≤0.009) and in executing the movement (p≤0.001). These findings suggest that visual feedback is crucial for determining balance, especially for dynamic tasks and on foam surfaces. Low-vision individuals had worse postural stability than normal-vision adults in terms of dynamic tests and balance on foam surfaces.

Training improves reading speed in peripheral vision: is it due to attention?

PubMed

Lee, Hye-Won; Kwon, Miyoung; Legge, Gordon E; Gefroh, Joshua J

2010-06-01

Previous research has shown that perceptual training in peripheral vision, using a letter-recognition task, increases reading speed and letter recognition (S. T. L. Chung, G. E. Legge, & S. H. Cheung, 2004). We tested the hypothesis that enhanced deployment of spatial attention to peripheral vision explains this training effect. Subjects were pre- and post-tested with 3 tasks at 10° above and below fixation-RSVP reading speed, trigram letter recognition (used to construct visual-span profiles), and deployment of spatial attention (measured as the benefit of a pre-cue for target position in a lexical-decision task). Groups of five normally sighted young adults received 4 days of trigram letter-recognition training in upper or lower visual fields, or central vision. A control group received no training. Our measure of deployment of spatial attention revealed visual-field anisotropies; better deployment of attention in the lower field than the upper, and in the lower-right quadrant compared with the other three quadrants. All subject groups exhibited slight improvement in deployment of spatial attention to peripheral vision in the post-test, but this improvement was not correlated with training-related increases in reading speed and the size of visual-span profiles. Our results indicate that improved deployment of spatial attention to peripheral vision does not account for improved reading speed and letter recognition in peripheral vision.

Using an Augmented Reality Device as a Distance-based Vision Aid-Promise and Limitations.

PubMed

Kinateder, Max; Gualtieri, Justin; Dunn, Matt J; Jarosz, Wojciech; Yang, Xing-Dong; Cooper, Emily A

2018-06-06

For people with limited vision, wearable displays hold the potential to digitally enhance visual function. As these display technologies advance, it is important to understand their promise and limitations as vision aids. The aim of this study was to test the potential of a consumer augmented reality (AR) device for improving the functional vision of people with near-complete vision loss. An AR application that translates spatial information into high-contrast visual patterns was developed. Two experiments assessed the efficacy of the application to improve vision: an exploratory study with four visually impaired participants and a main controlled study with participants with simulated vision loss (n = 48). In both studies, performance was tested on a range of visual tasks (identifying the location, pose and gesture of a person, identifying objects, and moving around in an unfamiliar space). Participants' accuracy and confidence were compared on these tasks with and without augmented vision, as well as their subjective responses about ease of mobility. In the main study, the AR application was associated with substantially improved accuracy and confidence in object recognition (all P < .001) and to a lesser degree in gesture recognition (P < .05). There was no significant change in performance on identifying body poses or in subjective assessments of mobility, as compared with a control group. Consumer AR devices may soon be able to support applications that improve the functional vision of users for some tasks. In our study, both artificially impaired participants and participants with near-complete vision loss performed tasks that they could not do without the AR system. Current limitations in system performance and form factor, as well as the risk of overconfidence, will need to be overcome.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

Functional Outcomes of the Low Vision Depression Prevention Trial in Age-Related Macular Degeneration.

PubMed

Deemer, Ashley D; Massof, Robert W; Rovner, Barry W; Casten, Robin J; Piersol, Catherine V

2017-03-01

To compare the efficacy of behavioral activation (BA) plus low vision rehabilitation with an occupational therapist (OT-LVR) with supportive therapy (ST) on visual function in patients with age-related macular degeneration (AMD). Single-masked, attention-controlled, randomized clinical trial with AMD patients with subsyndromal depressive symptoms (n = 188). All subjects had two outpatient low vision rehabilitation optometry visits, then were randomized to in-home BA + OT-LVR or ST. Behavioral activation is a structured behavioral treatment aiming to increase adaptive behaviors and achieve valued goals. Supportive therapy is a nondirective, psychological treatment that provides emotional support and controls for attention. Functional vision was assessed with the activity inventory (AI) in which participants rate the difficulty level of goals and corresponding tasks. Participants were assessed at baseline and 4 months. Improvements in functional vision measures were seen in both the BA + OT-LVR and ST groups at the goal level (d = 0.71; d = 0.56 respectively). At the task level, BA + OT-LVR patients showed more improvement in reading, inside-the-home tasks and outside-the-home tasks, when compared to ST patients. The greatest effects were seen in the BA + OT-LVR group in subjects with a visual acuity ≥20/70 (d = 0.360 reading; d = 0.500 inside the home; d = 0.468 outside the home). Based on the trends of the AI data, we suggest that BA + OT-LVR services, provided by an OT in the patient's home following conventional low vision optometry services, are more effective than conventional optometric low vision services alone for those with mild visual impairment. (ClinicalTrials.gov number, NCT00769015.).

The effects of absence of stereopsis on performance of a simulated surgical task in two-dimensional and three-dimensional viewing conditions

PubMed Central

Bloch, Edward; Uddin, Nabil; Gannon, Laura; Rantell, Khadija; Jain, Saurabh

2015-01-01

Background Stereopsis is believed to be advantageous for surgical tasks that require precise hand-eye coordination. We investigated the effects of short-term and long-term absence of stereopsis on motor task performance in three-dimensional (3D) and two-dimensional (2D) viewing conditions. Methods 30 participants with normal stereopsis and 15 participants with absent stereopsis performed a simulated surgical task both in free space under direct vision (3D) and via a monitor (2D), with both eyes open and one eye covered in each condition. Results The stereo-normal group scored higher, on average, than the stereo-absent group with both eyes open under direct vision (p<0.001). Both groups performed comparably in monocular and binocular monitor viewing conditions (p=0.579). Conclusions High-grade stereopsis confers an advantage when performing a fine motor task under direct vision. However, stereopsis does not appear advantageous to task performance under 2D viewing conditions, such as in video-assisted surgery. PMID:25185439

Machine vision for various manipulation tasks

NASA Astrophysics Data System (ADS)

Domae, Yukiyasu

2017-03-01

Bin-picking, re-grasping, pick-and-place, kitting, etc. There are many manipulation tasks in the fields of automation of factory, warehouse and so on. The main problem of the automation is that the target objects (items/parts) have various shapes, weights and surface materials. In my talk, I will show latest machine vision systems and algorithms against the problem.

Computer vision-based sorting of Atlantic salmon (Salmo salar) fillets according to their color level.

PubMed

Misimi, E; Mathiassen, J R; Erikson, U

2007-01-01

Computer vision method was used to evaluate the color of Atlantic salmon (Salmo salar) fillets. Computer vision-based sorting of fillets according to their color was studied on 2 separate groups of salmon fillets. The images of fillets were captured using a digital camera of high resolution. Images of salmon fillets were then segmented in the regions of interest and analyzed in red, green, and blue (RGB) and CIE Lightness, redness, and yellowness (Lab) color spaces, and classified according to the Roche color card industrial standard. Comparisons of fillet color between visual evaluations were made by a panel of human inspectors, according to the Roche SalmoFan lineal standard, and the color scores generated from computer vision algorithm showed that there were no significant differences between the methods. Overall, computer vision can be used as a powerful tool to sort fillets by color in a fast and nondestructive manner. The low cost of implementing computer vision solutions creates the potential to replace manual labor in fish processing plants with automation.

Reduced vision selectively impairs spatial updating in fall-prone older adults.

PubMed

Barrett, Maeve M; Doheny, Emer P; Setti, Annalisa; Maguinness, Corrina; Foran, Timothy G; Kenny, Rose Anne; Newell, Fiona N

2013-01-01

The current study examined the role of vision in spatial updating and its potential contribution to an increased risk of falls in older adults. Spatial updating was assessed using a path integration task in fall-prone and healthy older adults. Specifically, participants conducted a triangle completion task in which they were guided along two sides of a triangular route and were then required to return, unguided, to the starting point. During the task, participants could either clearly view their surroundings (full vision) or visuo-spatial information was reduced by means of translucent goggles (reduced vision). Path integration performance was measured by calculating the distance and angular deviation from the participant's return point relative to the starting point. Gait parameters for the unguided walk were also recorded. We found equivalent performance across groups on all measures in the full vision condition. In contrast, in the reduced vision condition, where participants had to rely on interoceptive cues to spatially update their position, fall-prone older adults made significantly larger distance errors relative to healthy older adults. However, there were no other performance differences between fall-prone and healthy older adults. These findings suggest that fall-prone older adults, compared to healthy older adults, have greater difficulty in reweighting other sensory cues for spatial updating when visual information is unreliable.

Real-time depth processing for embedded platforms

NASA Astrophysics Data System (ADS)

Rahnama, Oscar; Makarov, Aleksej; Torr, Philip

2017-05-01

Obtaining depth information of a scene is an important requirement in many computer-vision and robotics applications. For embedded platforms, passive stereo systems have many advantages over their active counterparts (i.e. LiDAR, Infrared). They are power efficient, cheap, robust to lighting conditions and inherently synchronized to the RGB images of the scene. However, stereo depth estimation is a computationally expensive task that operates over large amounts of data. For embedded applications which are often constrained by power consumption, obtaining accurate results in real-time is a challenge. We demonstrate a computationally and memory efficient implementation of a stereo block-matching algorithm in FPGA. The computational core achieves a throughput of 577 fps at standard VGA resolution whilst consuming less than 3 Watts of power. The data is processed using an in-stream approach that minimizes memory-access bottlenecks and best matches the raster scan readout of modern digital image sensors.

Functional considerations in evaluation and treatment of the client with low vision.

PubMed

Lampert, J; Lapolice, D J

1995-10-01

In evaluating and treating clients who have low vision, the occupational therapist must consider factors in addition to typical measures of the client's visual acuity, field loss, and oculomotor control. It is important to consider the functional implications of the client's ocular pathology, including illumination needs, contrast sensitivity, sensitivity to glare, and need for magnification as well as environmental factors such as the amount of pattern in a visual task, the amount of lighting and contrast available, and the conditions under which the task is performed. These factors are all relevant to occupational therapy low vision rehabilitation because each may influence the way in which a client uses his or her residual vision and achieves successful adaptation. This article provides an overview of these factors and presents a suggested protocol for evaluation of the client with low vision.

Do dichromats see colours in this way? Assessing simulation tools without colorimetric measurements.

PubMed

Lillo Jover, Julio A; Álvaro Llorente, Leticia; Moreira Villegas, Humberto; Melnikova, Anna

2016-11-01

Simulcheck evaluates Colour Simulation Tools (CSTs, they transform colours to mimic those seen by colour vision deficients). Two CSTs (Variantor and Coblis) were used to know if the standard Simulcheck version (direct measurement based, DMB) can be substituted by another (RGB values based) not requiring sophisticated measurement instruments. Ten normal trichromats performed the two psychophysical tasks included in the Simulcheck method. The Pseudoachromatic Stimuli Identification task provided the h uv (hue angle) values of the pseudoachromatic stimuli: colours seen as red or green by normal trichromats but as grey by colour deficient people. The Minimum Achromatic Contrast task was used to compute the L R (relative luminance) values of the pseudoachromatic stimuli. Simulcheck DMB version showed that Variantor was accurate to simulate protanopia but neither Variantor nor Coblis were accurate to simulate deuteranopia. Simulcheck RGB version provided accurate h uv values, so this variable can be adequately estimated when lacking a colorimeter —an expensive and unusual apparatus—. Contrary, the inaccuracy of the L R estimations provided by Simulcheck RGB version makes it advisable to compute this variable from the measurements performed with a photometer, a cheap and easy to find apparatus.

The Need for a Uniform Method of Recording and Reporting Functional Vision Assessments

ERIC Educational Resources Information Center

Shaw, Rona; Russotti, Joanne; Strauss-Schwartz, Judy; Vail, Helen; Kahn, Ronda

2009-01-01

The use of functional vision by school-age students who have visual impairments, including those with additional disabilities, is typically reported by teachers of students with visual impairments. Functional vision assessments determine how well a student uses his or her vision to perform tasks throughout the school day. The information that is…

Machine Learning, deep learning and optimization in computer vision

NASA Astrophysics Data System (ADS)

Canu, Stéphane

2017-03-01

As quoted in the Large Scale Computer Vision Systems NIPS workshop, computer vision is a mature field with a long tradition of research, but recent advances in machine learning, deep learning, representation learning and optimization have provided models with new capabilities to better understand visual content. The presentation will go through these new developments in machine learning covering basic motivations, ideas, models and optimization in deep learning for computer vision, identifying challenges and opportunities. It will focus on issues related with large scale learning that is: high dimensional features, large variety of visual classes, and large number of examples.

Low Vision Aids in Glaucoma

PubMed Central

Khanna, Anjani

2012-01-01

A large number of glaucoma patients suffer from vision impairments that qualify as low vision. Additional difficulties associated with low vision include problems with glare, lighting, and contrast, which can make daily activities extremely challenging. This article elaborates on how low vision aids can help with various tasks that visually impaired glaucoma patients need to do each day, to take care of themselves and to lead an independent life. PMID:27990068

Impairing the useful field of view in natural scenes: Tunnel vision versus general interference.

PubMed

Ringer, Ryan V; Throneburg, Zachary; Johnson, Aaron P; Kramer, Arthur F; Loschky, Lester C

2016-01-01

A fundamental issue in visual attention is the relationship between the useful field of view (UFOV), the region of visual space where information is encoded within a single fixation, and eccentricity. A common assumption is that impairing attentional resources reduces the size of the UFOV (i.e., tunnel vision). However, most research has not accounted for eccentricity-dependent changes in spatial resolution, potentially conflating fixed visual properties with flexible changes in visual attention. Williams (1988, 1989) argued that foveal loads are necessary to reduce the size of the UFOV, producing tunnel vision. Without a foveal load, it is argued that the attentional decrement is constant across the visual field (i.e., general interference). However, other research asserts that auditory working memory (WM) loads produce tunnel vision. To date, foveal versus auditory WM loads have not been compared to determine if they differentially change the size of the UFOV. In two experiments, we tested the effects of a foveal (rotated L vs. T discrimination) task and an auditory WM (N-back) task on an extrafoveal (Gabor) discrimination task. Gabor patches were scaled for size and processing time to produce equal performance across the visual field under single-task conditions, thus removing the confound of eccentricity-dependent differences in visual sensitivity. The results showed that although both foveal and auditory loads reduced Gabor orientation sensitivity, only the foveal load interacted with retinal eccentricity to produce tunnel vision, clearly demonstrating task-specific changes to the form of the UFOV. This has theoretical implications for understanding the UFOV.

Effectiveness of portable electronic and optical magnifiers for near vision activities in low vision: a randomised crossover trial.

PubMed

Taylor, John J; Bambrick, Rachel; Brand, Andrew; Bray, Nathan; Dutton, Michelle; Harper, Robert A; Hoare, Zoe; Ryan, Barbara; Edwards, Rhiannon T; Waterman, Heather; Dickinson, Christine

2017-07-01

To compare the performance of near vision activities using additional portable electronic vision enhancement systems (p-EVES), to using optical magnifiers alone, by individuals with visual impairment. A total of 100 experienced optical aid users were recruited from low vision clinics at Manchester Royal Eye Hospital, Manchester, UK, to a prospective two-arm cross-over randomised controlled trial. Reading, performance of near vision activities, and device usage were evaluated at baseline; and at the end of each study arm (Intervention A: existing optical aids plus p-EVES; Intervention B: optical aids only) which was after 2 and 4 months. A total of 82 participants completed the study. Overall, maximum reading speed for high contrast sentences was not statistically significantly different for optical aids and p-EVES, although the critical print size and threshold print size which could be accessed with p-EVES were statistically significantly smaller (p < 0.001 in both cases). The optical aids were used for a larger number of tasks (p < 0.001), and used more frequently (p < 0.001). However p-EVES were preferred for leisure reading by 70% of participants, and allowed longer duration of reading (p < 0.001). During the study arm when they had a p-EVES device, participants were able to carry out more tasks independently (p < 0.001), and reported less difficulty with a range of near vision activities (p < 0.001). The study provides evidence that p-EVES devices can play a useful role in supplementing the range of low vision aids used to reduce activity limitation for near vision tasks. © 2017 The Authors Ophthalmic & Physiological Optics © 2017 The College of Optometrists.

3-D Signal Processing in a Computer Vision System

Treesearch

Dongping Zhu; Richard W. Conners; Philip A. Araman

1991-01-01

This paper discusses the problem of 3-dimensional image filtering in a computer vision system that would locate and identify internal structural failure. In particular, a 2-dimensional adaptive filter proposed by Unser has been extended to 3-dimension. In conjunction with segmentation and labeling, the new filter has been used in the computer vision system to...

An overview of computer vision

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1982-01-01

An overview of computer vision is provided. Image understanding and scene analysis are emphasized, and pertinent aspects of pattern recognition are treated. The basic approach to computer vision systems, the techniques utilized, applications, the current existing systems and state-of-the-art issues and research requirements, who is doing it and who is funding it, and future trends and expectations are reviewed.

Experiences Using an Open Source Software Library to Teach Computer Vision Subjects

ERIC Educational Resources Information Center

Cazorla, Miguel; Viejo, Diego

2015-01-01

Machine vision is an important subject in computer science and engineering degrees. For laboratory experimentation, it is desirable to have a complete and easy-to-use tool. In this work we present a Java library, oriented to teaching computer vision. We have designed and built the library from the scratch with emphasis on readability and…

Detecting Motion from a Moving Platform; Phase 3: Unification of Control and Sensing for More Advanced Situational Awareness

DTIC Science & Technology

2011-11-01

RX-TY-TR-2011-0096-01) develops a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica...01 summarizes the development of a novel computer vision sensor based upon the biological vision system of the common housefly , Musca domestica

Road following for blindBike: an assistive bike navigation system for low vision persons

NASA Astrophysics Data System (ADS)

Grewe, Lynne; Overell, William

2017-05-01

Road Following is a critical component of blindBike, our assistive biking application for the visually impaired. This paper talks about the overall blindBike system and goals prominently featuring Road Following, which is the task of directing the user to follow the right side of the road. This work unlike what is commonly found for self-driving cars does not depend on lane line markings. 2D computer vision techniques are explored to solve the problem of Road Following. Statistical techniques including the use of Gaussian Mixture Models are employed. blindBike is developed as an Android Application and is running on a smartphone device. Other sensors including Gyroscope and GPS are utilized. Both Urban and suburban scenarios are tested and results are given. The success and challenges faced by blindBike's Road Following module are presented along with future avenues of work.

Vision-Based Real-Time Traversable Region Detection for Mobile Robot in the Outdoors.

PubMed

Deng, Fucheng; Zhu, Xiaorui; He, Chao

2017-09-13

Environment perception is essential for autonomous mobile robots in human-robot coexisting outdoor environments. One of the important tasks for such intelligent robots is to autonomously detect the traversable region in an unstructured 3D real world. The main drawback of most existing methods is that of high computational complexity. Hence, this paper proposes a binocular vision-based, real-time solution for detecting traversable region in the outdoors. In the proposed method, an appearance model based on multivariate Gaussian is quickly constructed from a sample region in the left image adaptively determined by the vanishing point and dominant borders. Then, a fast, self-supervised segmentation scheme is proposed to classify the traversable and non-traversable regions. The proposed method is evaluated on public datasets as well as a real mobile robot. Implementation on the mobile robot has shown its ability in the real-time navigation applications.

Episodic Reasoning for Vision-Based Human Action Recognition

PubMed Central

Martinez-del-Rincon, Jesus

2014-01-01

Smart Spaces, Ambient Intelligence, and Ambient Assisted Living are environmental paradigms that strongly depend on their capability to recognize human actions. While most solutions rest on sensor value interpretations and video analysis applications, few have realized the importance of incorporating common-sense capabilities to support the recognition process. Unfortunately, human action recognition cannot be successfully accomplished by only analyzing body postures. On the contrary, this task should be supported by profound knowledge of human agency nature and its tight connection to the reasons and motivations that explain it. The combination of this knowledge and the knowledge about how the world works is essential for recognizing and understanding human actions without committing common-senseless mistakes. This work demonstrates the impact that episodic reasoning has in improving the accuracy of a computer vision system for human action recognition. This work also presents formalization, implementation, and evaluation details of the knowledge model that supports the episodic reasoning. PMID:24959602

Image annotation based on positive-negative instances learning

NASA Astrophysics Data System (ADS)

Zhang, Kai; Hu, Jiwei; Liu, Quan; Lou, Ping

2017-07-01

Automatic image annotation is now a tough task in computer vision, the main sense of this tech is to deal with managing the massive image on the Internet and assisting intelligent retrieval. This paper designs a new image annotation model based on visual bag of words, using the low level features like color and texture information as well as mid-level feature as SIFT, and mixture the pic2pic, label2pic and label2label correlation to measure the correlation degree of labels and images. We aim to prune the specific features for each single label and formalize the annotation task as a learning process base on Positive-Negative Instances Learning. Experiments are performed using the Corel5K Dataset, and provide a quite promising result when comparing with other existing methods.

LLSURE: local linear SURE-based edge-preserving image filtering.

PubMed

Qiu, Tianshuang; Wang, Aiqi; Yu, Nannan; Song, Aimin

2013-01-01

In this paper, we propose a novel approach for performing high-quality edge-preserving image filtering. Based on a local linear model and using the principle of Stein's unbiased risk estimate as an estimator for the mean squared error from the noisy image only, we derive a simple explicit image filter which can filter out noise while preserving edges and fine-scale details. Moreover, this filter has a fast and exact linear-time algorithm whose computational complexity is independent of the filtering kernel size; thus, it can be applied to real time image processing tasks. The experimental results demonstrate the effectiveness of the new filter for various computer vision applications, including noise reduction, detail smoothing and enhancement, high dynamic range compression, and flash/no-flash denoising.

Relevance feedback-based building recognition

NASA Astrophysics Data System (ADS)

Li, Jing; Allinson, Nigel M.

2010-07-01

Building recognition is a nontrivial task in computer vision research which can be utilized in robot localization, mobile navigation, etc. However, existing building recognition systems usually encounter the following two problems: 1) extracted low level features cannot reveal the true semantic concepts; and 2) they usually involve high dimensional data which require heavy computational costs and memory. Relevance feedback (RF), widely applied in multimedia information retrieval, is able to bridge the gap between the low level visual features and high level concepts; while dimensionality reduction methods can mitigate the high-dimensional problem. In this paper, we propose a building recognition scheme which integrates the RF and subspace learning algorithms. Experimental results undertaken on our own building database show that the newly proposed scheme appreciably enhances the recognition accuracy.

Heterogeneous compute in computer vision: OpenCL in OpenCV

NASA Astrophysics Data System (ADS)

Gasparakis, Harris

2014-02-01

We explore the relevance of Heterogeneous System Architecture (HSA) in Computer Vision, both as a long term vision, and as a near term emerging reality via the recently ratified OpenCL 2.0 Khronos standard. After a brief review of OpenCL 1.2 and 2.0, including HSA features such as Shared Virtual Memory (SVM) and platform atomics, we identify what genres of Computer Vision workloads stand to benefit by leveraging those features, and we suggest a new mental framework that replaces GPU compute with hybrid HSA APU compute. As a case in point, we discuss, in some detail, popular object recognition algorithms (part-based models), emphasizing the interplay and concurrent collaboration between the GPU and CPU. We conclude by describing how OpenCL has been incorporated in OpenCV, a popular open source computer vision library, emphasizing recent work on the Transparent API, to appear in OpenCV 3.0, which unifies the native CPU and OpenCL execution paths under a single API, allowing the same code to execute either on CPU or on a OpenCL enabled device, without even recompiling.

Characterization of the Structure and Function of the Normal Human Fovea Using Adaptive Optics Scanning Laser Ophthalmoscopy

NASA Astrophysics Data System (ADS)

Putnam, Nicole Marie

In order to study the limits of spatial vision in normal human subjects, it is important to look at and near the fovea. The fovea is the specialized part of the retina, the light-sensitive multi-layered neural tissue that lines the inner surface of the human eye, where the cone photoreceptors are smallest (approximately 2.5 microns or 0.5 arcmin) and cone density reaches a peak. In addition, there is a 1:1 mapping from the photoreceptors to the brain in this central region of the retina. As a result, the best spatial sampling is achieved in the fovea and it is the retinal location used for acuity and spatial vision tasks. However, vision is typically limited by the blur induced by the normal optics of the eye and clinical tests of foveal vision and foveal imaging are both limited due to the blur. As a result, it is unclear what the perceptual benefit of extremely high cone density is. Cutting-edge imaging technology, specifically Adaptive Optics Scanning Laser Ophthalmoscopy (AOSLO), can be utilized to remove this blur, zoom in, and as a result visualize individual cone photoreceptors throughout the central fovea. This imaging combined with simultaneous image stabilization and targeted stimulus delivery expands our understanding of both the anatomical structure of the fovea on a microscopic scale and the placement of stimuli within this retinal area during visual tasks. The final step is to investigate the role of temporal variables in spatial vision tasks since the eye is in constant motion even during steady fixation. In order to learn more about the fovea, it becomes important to study the effect of this motion on spatial vision tasks. This dissertation steps through many of these considerations, starting with a model of the foveal cone mosaic imaged with AOSLO. We then use this high resolution imaging to compare anatomical and functional markers of the center of the normal human fovea. Finally, we investigate the role of natural and manipulated fixational eye movements in foveal vision, specifically looking at a motion detection task, contrast sensitivity, and image fading.

Task relevance induces momentary changes in the functional visual field during reading.

PubMed

Kaakinen, Johanna K; Hyönä, Jukka

2014-02-01

In the research reported here, we examined whether task demands can induce momentary tunnel vision during reading. More specifically, we examined whether the size of the functional visual field depends on task relevance. Forty participants read an expository text with a specific task in mind while their eye movements were recorded. A display-change paradigm with random-letter strings as preview masks was used to study the size of the functional visual field within sentences that contained task-relevant and task-irrelevant information. The results showed that orthographic parafoveal-on-foveal effects and preview benefits were observed for words within task-irrelevant but not task-relevant sentences. The results indicate that the size of the functional visual field is flexible and depends on the momentary processing demands of a reading task. The higher cognitive processing requirements experienced when reading task-relevant text rather than task-irrelevant text induce momentary tunnel vision, which narrows the functional visual field.

A high-throughput screening approach to discovering good forms of biologically inspired visual representation.

PubMed

Pinto, Nicolas; Doukhan, David; DiCarlo, James J; Cox, David D

2009-11-01

While many models of biological object recognition share a common set of "broad-stroke" properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model--e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct "parts" have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision.

A High-Throughput Screening Approach to Discovering Good Forms of Biologically Inspired Visual Representation

PubMed Central

Pinto, Nicolas; Doukhan, David; DiCarlo, James J.; Cox, David D.

2009-01-01

While many models of biological object recognition share a common set of “broad-stroke” properties, the performance of any one model depends strongly on the choice of parameters in a particular instantiation of that model—e.g., the number of units per layer, the size of pooling kernels, exponents in normalization operations, etc. Since the number of such parameters (explicit or implicit) is typically large and the computational cost of evaluating one particular parameter set is high, the space of possible model instantiations goes largely unexplored. Thus, when a model fails to approach the abilities of biological visual systems, we are left uncertain whether this failure is because we are missing a fundamental idea or because the correct “parts” have not been tuned correctly, assembled at sufficient scale, or provided with enough training. Here, we present a high-throughput approach to the exploration of such parameter sets, leveraging recent advances in stream processing hardware (high-end NVIDIA graphic cards and the PlayStation 3's IBM Cell Processor). In analogy to high-throughput screening approaches in molecular biology and genetics, we explored thousands of potential network architectures and parameter instantiations, screening those that show promising object recognition performance for further analysis. We show that this approach can yield significant, reproducible gains in performance across an array of basic object recognition tasks, consistently outperforming a variety of state-of-the-art purpose-built vision systems from the literature. As the scale of available computational power continues to expand, we argue that this approach has the potential to greatly accelerate progress in both artificial vision and our understanding of the computational underpinning of biological vision. PMID:19956750

Demystifying Multitask Deep Neural Networks for Quantitative Structure-Activity Relationships.

PubMed

Xu, Yuting; Ma, Junshui; Liaw, Andy; Sheridan, Robert P; Svetnik, Vladimir

2017-10-23

Deep neural networks (DNNs) are complex computational models that have found great success in many artificial intelligence applications, such as computer vision1,2 and natural language processing.3,4 In the past four years, DNNs have also generated promising results for quantitative structure-activity relationship (QSAR) tasks.5,6 Previous work showed that DNNs can routinely make better predictions than traditional methods, such as random forests, on a diverse collection of QSAR data sets. It was also found that multitask DNN models-those trained on and predicting multiple QSAR properties simultaneously-outperform DNNs trained separately on the individual data sets in many, but not all, tasks. To date there has been no satisfactory explanation of why the QSAR of one task embedded in a multitask DNN can borrow information from other unrelated QSAR tasks. Thus, using multitask DNNs in a way that consistently provides a predictive advantage becomes a challenge. In this work, we explored why multitask DNNs make a difference in predictive performance. Our results show that during prediction a multitask DNN does borrow "signal" from molecules with similar structures in the training sets of the other tasks. However, whether this borrowing leads to better or worse predictive performance depends on whether the activities are correlated. On the basis of this, we have developed a strategy to use multitask DNNs that incorporate prior domain knowledge to select training sets with correlated activities, and we demonstrate its effectiveness on several examples.

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform

PubMed Central

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B.

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks. PMID:26909015

Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform.

PubMed

Giulioni, Massimiliano; Lagorce, Xavier; Galluppi, Francesco; Benosman, Ryad B

2016-01-01

Estimating the speed and direction of moving objects is a crucial component of agents behaving in a dynamic world. Biological organisms perform this task by means of the neural connections originating from their retinal ganglion cells. In artificial systems the optic flow is usually extracted by comparing activity of two or more frames captured with a vision sensor. Designing artificial motion flow detectors which are as fast, robust, and efficient as the ones found in biological systems is however a challenging task. Inspired by the architecture proposed by Barlow and Levick in 1965 to explain the spiking activity of the direction-selective ganglion cells in the rabbit's retina, we introduce an architecture for robust optical flow extraction with an analog neuromorphic multi-chip system. The task is performed by a feed-forward network of analog integrate-and-fire neurons whose inputs are provided by contrast-sensitive photoreceptors. Computation is supported by the precise time of spike emission, and the extraction of the optical flow is based on time lag in the activation of nearby retinal neurons. Mimicking ganglion cells our neuromorphic detectors encode the amplitude and the direction of the apparent visual motion in their output spiking pattern. Hereby we describe the architectural aspects, discuss its latency, scalability, and robustness properties and demonstrate that a network of mismatched delicate analog elements can reliably extract the optical flow from a simple visual scene. This work shows how precise time of spike emission used as a computational basis, biological inspiration, and neuromorphic systems can be used together for solving specific tasks.

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.

Constructional ability in two- versus three-dimensions: relationship to spatial vision and locus of cerebrovascular lesion.

PubMed

Capruso, Daniel X; Hamsher, Kerry deS

2011-06-01

Clinical evaluation and research on constructional ability have come to rely almost exclusively on two-dimensional tasks such as graphomotor copying or mosaic Block Design (BD). A return to the inclusion of a third dimension in constructional tests may increase the spatial demands of the task, and improve understanding of the relationship between visual perception and constructional ability in patients with cerebral disease. Subjects were patients (n=43) with focal or multifocal cerebrovascular lesions as determined by CT or MRI. Tests of temporal orientation, verbal intelligence, language, object vision and spatial vision were used to determine which factors were predictive of performance on two-dimensional BD and Three-Dimensional Block Construction (3-DBC) tasks. Stepwise linear regression indicated that spatial vision predicted BD performance, and was even more strongly predictive of 3-DBC. Other cognitive domains did not account for significant additional variance in performance of either BD or 3-DBC. Bilateral cerebral lesions produced more severe deficits on BD than did unilateral cerebral lesions. The presence of a posterior cerebral lesion was the significant factor in producing deficits in 3-DBC. The spatial aspect of a constructional task is enhanced when the patient is required to assemble an object in all three dimensions of space. In the typical patient with cerebrovascular disease, constructional deficits typically occur in the context of a wider syndrome of deficits in spatial vision. Copyright © 2010 Elsevier Srl. All rights reserved.

GeoVision Exploration Task Force Report

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

Doughty, Christine; Dobson, Patrick F.; Wall, Anna

The GeoVision study effort included ground-breaking, detailed research on current and future market conditions and geothermal technologies in order to forecast and quantify the electric and non-electric deployment potentials under a range of scenarios, in addition to their impacts on the Nation’s jobs, economy and environment. Coordinated by the U.S. Department of Energy’s (DOE’s) Geothermal Technologies Office (GTO), the GeoVision study development relied on the collection, modeling, and analysis of robust datasets through seven national laboratory partners, which were organized into eight technical Task Force groups. The purpose of this report is to provide a central repository for the researchmore » conducted by the Exploration Task Force. The Exploration Task Force consists of four individuals representing three national laboratories: Patrick Dobson (task lead) and Christine Doughty of Lawrence Berkeley National Laboratory, Anna Wall of National Renewable Energy Laboratory, Travis McLing of Idaho National Laboratory, and Chester Weiss of Sandia National Laboratories. As part of the GeoVision analysis, our team conducted extensive scientific and financial analyses on a number of topics related to current and future geothermal exploration methods. The GeoVision Exploration Task Force complements the drilling and resource technology investigations conducted as part of the Reservoir Maintenance and Development Task Force. The Exploration Task Force however has focused primarily on early stage R&D technologies in exploration and confirmation drilling, along with an evaluation of geothermal financing challenges and assumptions, and innovative “blue-sky” technologies. This research was used to develop geothermal resource supply curves (through the use of GETEM) for use in the ReEDS capacity expansion modeling that determines geothermal technology deployment potential. It also catalogues and explores the large array of early-stage R&D technologies with the potential to dramatically reduce exploration and geothermal development costs, forming the basis of the GeoVision Technology Improvement (TI) scenario. These modeling topics are covered in detail in Potential to Penetration task force report. Most of the research contained herein has been published in peer-reviewed papers or conference proceedings and are cited and referenced accordingly. The sections that follow provide a central repository for all of the research findings of the Exploration and Confirmation Task Force. In summary, it provides a comprehensive discussion of Engineered Geothermal Systems (EGS) and associated technology challenges, the risks and costs of conducting geothermal exploration, a review of existing government efforts to date in advancing early-stage R&D in both exploration and EGS technologies, as well as a discussion of promising and innovative technologies and implementation of blue-sky concepts that could significantly reduce costs, lower risks, and shorten the time needed to explore and develop geothermal resources of all types.« less

Using parallel evolutionary development for a biologically-inspired computer vision system for mobile robots.

PubMed

Wright, Cameron H G; Barrett, Steven F; Pack, Daniel J

2005-01-01

We describe a new approach to attacking the problem of robust computer vision for mobile robots. The overall strategy is to mimic the biological evolution of animal vision systems. Our basic imaging sensor is based upon the eye of the common house fly, Musca domestica. The computational algorithms are a mix of traditional image processing, subspace techniques, and multilayer neural networks.

Progress in computer vision.

NASA Astrophysics Data System (ADS)

Jain, A. K.; Dorai, C.

Computer vision has emerged as a challenging and important area of research, both as an engineering and a scientific discipline. The growing importance of computer vision is evident from the fact that it was identified as one of the "Grand Challenges" and also from its prominent role in the National Information Infrastructure. While the design of a general-purpose vision system continues to be elusive machine vision systems are being used successfully in specific application elusive, machine vision systems are being used successfully in specific application domains. Building a practical vision system requires a careful selection of appropriate sensors, extraction and integration of information from available cues in the sensed data, and evaluation of system robustness and performance. The authors discuss and demonstrate advantages of (1) multi-sensor fusion, (2) combination of features and classifiers, (3) integration of visual modules, and (IV) admissibility and goal-directed evaluation of vision algorithms. The requirements of several prominent real world applications such as biometry, document image analysis, image and video database retrieval, and automatic object model construction offer exciting problems and new opportunities to design and evaluate vision algorithms.

Can Humans Fly Action Understanding with Multiple Classes of Actors

DTIC Science & Technology

2015-06-08

recognition using structure from motion point clouds. In European Conference on Computer Vision, 2008. [5] R. Caruana. Multitask learning. Machine Learning...tonomous driving ? the kitti vision benchmark suite. In IEEE Conference on Computer Vision and Pattern Recognition, 2012. [12] L. Gorelick, M. Blank

Visual-conformal display format for helicopter guidance

NASA Astrophysics Data System (ADS)

Doehler, H.-U.; Schmerwitz, Sven; Lueken, Thomas

2014-06-01

Helicopter guidance in situations where natural vision is reduced is still a challenging task. Beside new available sensors, which are able to "see" through darkness, fog and dust, display technology remains one of the key issues of pilot assistance systems. As long as we have pilots within aircraft cockpits, we have to keep them informed about the outside situation. "Situational awareness" of humans is mainly powered by their visual channel. Therefore, display systems which are able to cross-fade seamless from natural vision to artificial computer vision and vice versa, are of greatest interest within this context. Helmet-mounted displays (HMD) have this property when they apply a head-tracker for measuring the pilot's head orientation relative to the aircraft reference frame. Together with the aircraft's position and orientation relative to the world's reference frame, the on-board graphics computer can generate images which are perfectly aligned with the outside world. We call image elements which match the outside world, "visual-conformal". Published display formats for helicopter guidance in degraded visual environment apply mostly 2D-symbologies which stay far behind from what is possible. We propose a perspective 3D-symbology for a head-tracked HMD which shows as much as possible visual-conformal elements. We implemented and tested our proposal within our fixed based cockpit simulator as well as in our flying helicopter simulator (FHS). Recently conducted simulation trials with experienced helicopter pilots give some first evaluation results of our proposal.

Volumetric segmentation of range images for printed circuit board inspection

NASA Astrophysics Data System (ADS)

Van Dop, Erik R.; Regtien, Paul P. L.

1996-10-01

Conventional computer vision approaches towards object recognition and pose estimation employ 2D grey-value or color imaging. As a consequence these images contain information about projections of a 3D scene only. The subsequent image processing will then be difficult, because the object coordinates are represented with just image coordinates. Only complicated low-level vision modules like depth from stereo or depth from shading can recover some of the surface geometry of the scene. Recent advances in fast range imaging have however paved the way towards 3D computer vision, since range data of the scene can now be obtained with sufficient accuracy and speed for object recognition and pose estimation purposes. This article proposes the coded-light range-imaging method together with superquadric segmentation to approach this task. Superquadric segments are volumetric primitives that describe global object properties with 5 parameters, which provide the main features for object recognition. Besides, the principle axes of a superquadric segment determine the phase of an object in the scene. The volumetric segmentation of a range image can be used to detect missing, false or badly placed components on assembled printed circuit boards. Furthermore, this approach will be useful to recognize and extract valuable or toxic electronic components on printed circuit boards scrap that currently burden the environment during electronic waste processing. Results on synthetic range images with errors constructed according to a verified noise model illustrate the capabilities of this approach.

Bio-inspired vision based robot control using featureless estimations of time-to-contact.

PubMed

Zhang, Haijie; Zhao, Jianguo

2017-01-31

Marvelous vision based dynamic behaviors of insects and birds such as perching, landing, and obstacle avoidance have inspired scientists to propose the idea of time-to-contact, which is defined as the time for a moving observer to contact an object or surface if the current velocity is maintained. Since with only a vision sensor, time-to-contact can be directly estimated from consecutive images, it is widely used for a variety of robots to fulfill various tasks such as obstacle avoidance, docking, chasing, perching and landing. However, most of existing methods to estimate the time-to-contact need to extract and track features during the control process, which is time-consuming and cannot be applied to robots with limited computation power. In this paper, we adopt a featureless estimation method, extend this method to more general settings with angular velocities, and improve the estimation results using Kalman filtering. Further, we design an error based controller with gain scheduling strategy to control the motion of mobile robots. Experiments for both estimation and control are conducted using a customized mobile robot platform with low-cost embedded systems. Onboard experimental results demonstrate the effectiveness of the proposed approach, with the robot being controlled to successfully dock in front of a vertical wall. The estimation and control methods presented in this paper can be applied to computation-constrained miniature robots for agile locomotion such as landing, docking, or navigation.

Robot acting on moving bodies (RAMBO): Preliminary results

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madju; Harwood, David

1989-01-01

A robot system called RAMBO is being developed. It is equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a moving object. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations nearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enchancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows the use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using parametric cubic splines between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

Operator vision aids for space teleoperation assembly and servicing

NASA Technical Reports Server (NTRS)

Brooks, Thurston L.; Ince, Ilhan; Lee, Greg

1992-01-01

This paper investigates concepts for visual operator aids required for effective telerobotic control. Operator visual aids, as defined here, mean any operational enhancement that improves man-machine control through the visual system. These concepts were derived as part of a study of vision issues for space teleoperation. Extensive literature on teleoperation, robotics, and human factors was surveyed to definitively specify appropriate requirements. This paper presents these visual aids in three general categories of camera/lighting functions, display enhancements, and operator cues. In the area of camera/lighting functions concepts are discussed for: (1) automatic end effector or task tracking; (2) novel camera designs; (3) computer-generated virtual camera views; (4) computer assisted camera/lighting placement; and (5) voice control. In the technology area of display aids, concepts are presented for: (1) zone displays, such as imminent collision or indexing limits; (2) predictive displays for temporal and spatial location; (3) stimulus-response reconciliation displays; (4) graphical display of depth cues such as 2-D symbolic depth, virtual views, and perspective depth; and (5) view enhancements through image processing and symbolic representations. Finally, operator visual cues (e.g., targets) that help identify size, distance, shape, orientation and location are discussed.

Remote hardware-reconfigurable robotic camera

NASA Astrophysics Data System (ADS)

Arias-Estrada, Miguel; Torres-Huitzil, Cesar; Maya-Rueda, Selene E.

2001-10-01

In this work, a camera with integrated image processing capabilities is discussed. The camera is based on an imager coupled to an FPGA device (Field Programmable Gate Array) which contains an architecture for real-time computer vision low-level processing. The architecture can be reprogrammed remotely for application specific purposes. The system is intended for rapid modification and adaptation for inspection and recognition applications, with the flexibility of hardware and software reprogrammability. FPGA reconfiguration allows the same ease of upgrade in hardware as a software upgrade process. The camera is composed of a digital imager coupled to an FPGA device, two memory banks, and a microcontroller. The microcontroller is used for communication tasks and FPGA programming. The system implements a software architecture to handle multiple FPGA architectures in the device, and the possibility to download a software/hardware object from the host computer into its internal context memory. System advantages are: small size, low power consumption, and a library of hardware/software functionalities that can be exchanged during run time. The system has been validated with an edge detection and a motion processing architecture, which will be presented in the paper. Applications targeted are in robotics, mobile robotics, and vision based quality control.

Fast Markerless Tracking for Augmented Reality in Planar Environment

NASA Astrophysics Data System (ADS)

Basori, Ahmad Hoirul; Afif, Fadhil Noer; Almazyad, Abdulaziz S.; AbuJabal, Hamza Ali S.; Rehman, Amjad; Alkawaz, Mohammed Hazim

2015-12-01

Markerless tracking for augmented reality should not only be accurate but also fast enough to provide a seamless synchronization between real and virtual beings. Current reported methods showed that a vision-based tracking is accurate but requires high computational power. This paper proposes a real-time hybrid-based method for tracking unknown environments in markerless augmented reality. The proposed method provides collaboration of vision-based approach with accelerometers and gyroscopes sensors as camera pose predictor. To align the augmentation relative to camera motion, the tracking method is done by substituting feature-based camera estimation with combination of inertial sensors with complementary filter to provide more dynamic response. The proposed method managed to track unknown environment with faster processing time compared to available feature-based approaches. Moreover, the proposed method can sustain its estimation in a situation where feature-based tracking loses its track. The collaboration of sensor tracking managed to perform the task for about 22.97 FPS, up to five times faster than feature-based tracking method used as comparison. Therefore, the proposed method can be used to track unknown environments without depending on amount of features on scene, while requiring lower computational cost.

Computer vision in cell biology.

PubMed

Danuser, Gaudenz

2011-11-23

Computer vision refers to the theory and implementation of artificial systems that extract information from images to understand their content. Although computers are widely used by cell biologists for visualization and measurement, interpretation of image content, i.e., the selection of events worth observing and the definition of what they mean in terms of cellular mechanisms, is mostly left to human intuition. This Essay attempts to outline roles computer vision may play and should play in image-based studies of cellular life. Copyright © 2011 Elsevier Inc. All rights reserved.

Measuring saliency in images: which experimental parameters for the assessment of image quality?

NASA Astrophysics Data System (ADS)

Fredembach, Clement; Woolfe, Geoff; Wang, Jue

2012-01-01

Predicting which areas of an image are perceptually salient or attended to has become an essential pre-requisite of many computer vision applications. Because observers are notoriously unreliable in remembering where they look a posteriori, and because asking where they look while observing the image necessarily in uences the results, ground truth about saliency and visual attention has to be obtained by gaze tracking methods. From the early work of Buswell and Yarbus to the most recent forays in computer vision there has been, perhaps unfortunately, little agreement on standardisation of eye tracking protocols for measuring visual attention. As the number of parameters involved in experimental methodology can be large, their individual in uence on the nal results is not well understood. Consequently, the performance of saliency algorithms, when assessed by correlation techniques, varies greatly across the literature. In this paper, we concern ourselves with the problem of image quality. Specically: where people look when judging images. We show that in this case, the performance gap between existing saliency prediction algorithms and experimental results is signicantly larger than otherwise reported. To understand this discrepancy, we rst devise an experimental protocol that is adapted to the task of measuring image quality. In a second step, we compare our experimental parameters with the ones of existing methods and show that a lot of the variability can directly be ascribed to these dierences in experimental methodology and choice of variables. In particular, the choice of a task, e.g., judging image quality vs. free viewing, has a great impact on measured saliency maps, suggesting that even for a mildly cognitive task, ground truth obtained by free viewing does not adapt well. Careful analysis of the prior art also reveals that systematic bias can occur depending on instrumental calibration and the choice of test images. We conclude this work by proposing a set of parameters, tasks and images that can be used to compare the various saliency prediction methods in a manner that is meaningful for image quality assessment.

Computer Vision Syndrome.

PubMed

Randolph, Susan A

2017-07-01

With the increased use of electronic devices with visual displays, computer vision syndrome is becoming a major public health issue. Improving the visual status of workers using computers results in greater productivity in the workplace and improved visual comfort.

SKread predicts handwriting performance in patients with low vision.

PubMed

Downes, Ken; Walker, Laura L; Fletcher, Donald C

2015-06-01

To assess whether performance on the Smith-Kettlewell Reading (SKread) test is a reliable predictor of handwriting performance in patients with low vision. Cross-sectional study. Sixty-six patients at their initial low-vision rehabilitation evaluation. The patients completed all components of a routine low-vision appointment including logMAR acuity, performed the SKread test, and performed a handwriting task. Patients were timed while performing each task and their accuracy was recorded. The handwriting task was performed by having patients write 5 5-letter words into sets of boxes where each letter is separated by a box. The boxes were 15 × 15 mm, and accuracy was scored with 50 points possible from 25 letters: 1 point for each letter within the confines of a box and 1 point if the letter was legible. Correlation analysis was then performed. Median age of participants was 84 (range 54-97) years. Fifty-seven patients (86%) had age-related macular degeneration or some other maculopathy, whereas 9 patients (14%) had visual impairment from media opacity or neurologic impairment. Median Early Treatment Diabetic Retinopathy Study acuity was 20/133 (range 20/22 to 20/1000), and median logMAR acuity was 0.82 (range 0.04-1.70). SKread errors per block correlated with logMAR acuity (r = 0.6), and SKread time per block correlated with logMAR acuity (r = 0.51). SKread errors per block correlated with handwriting task time/accuracy ratio (r = 0.61). SKread time per block correlated with handwriting task time/accuracy ratio (r = 0.7). LogMAR acuity score correlated with handwriting task time/accuracy ratio (r = 0.42). All p values were < 0.01. SKread scores predict handwriting performance in patients with low vision better than logMAR acuity. Copyright © 2015 Canadian Ophthalmological Society. Published by Elsevier Inc. All rights reserved.

Any way you look at it, successful obstacle negotiation needs visually guided on-line foot placement regulation during the approach phase.

PubMed

Patla, Aftab E; Greig, Michael

In the two experiments discussed in this paper we quantified obstacle avoidance performance characteristics carried out open loop (without vision) but with different initial visual sampling conditions and compared it to the full vision condition. The initial visual sampling conditions included: static vision (SV), vision during forward walking for three steps and stopping (FW), vision during forward walking for three steps and not stopping (FW-NS), and vision during backward walking for three steps and stopping (BW). In experiment 1, we compared performance during SV, FW and BW with full vision condition, while in the second experiment we compared performance during FW and FW-NS conditions. The questions we wanted to address are: Is ecologically valid dynamic visual sampling of the environment superior to static visual sampling for open loop obstacle avoidance task? What are the reasons for failure in performing open loop obstacle avoidance task? The results showed that irrespective of the initial visual sampling condition when open loop control is initiated from a standing posture, the success rate was only approximately 50%. The main reason for the high failure rates was not inappropriate limb elevation, but incorrect foot placement before the obstacle. The second experiment showed that it is not the nature of visual sampling per se that influences success rate, but the fact that the open loop obstacle avoidance task is initiated from a standing posture. The results of these two experiments clearly demonstrate the importance of on-line visual information for adaptive human locomotion.

Computer vision and soft computing for automatic skull-face overlay in craniofacial superimposition.

PubMed

Campomanes-Álvarez, B Rosario; Ibáñez, O; Navarro, F; Alemán, I; Botella, M; Damas, S; Cordón, O

2014-12-01

Craniofacial superimposition can provide evidence to support that some human skeletal remains belong or not to a missing person. It involves the process of overlaying a skull with a number of ante mortem images of an individual and the analysis of their morphological correspondence. Within the craniofacial superimposition process, the skull-face overlay stage just focuses on achieving the best possible overlay of the skull and a single ante mortem image of the suspect. Although craniofacial superimposition has been in use for over a century, skull-face overlay is still applied by means of a trial-and-error approach without an automatic method. Practitioners finish the process once they consider that a good enough overlay has been attained. Hence, skull-face overlay is a very challenging, subjective, error prone, and time consuming part of the whole process. Though the numerical assessment of the method quality has not been achieved yet, computer vision and soft computing arise as powerful tools to automate it, dramatically reducing the time taken by the expert and obtaining an unbiased overlay result. In this manuscript, we justify and analyze the use of these techniques to properly model the skull-face overlay problem. We also present the automatic technical procedure we have developed using these computational methods and show the four overlays obtained in two craniofacial superimposition cases. This automatic procedure can be thus considered as a tool to aid forensic anthropologists to develop the skull-face overlay, automating and avoiding subjectivity of the most tedious task within craniofacial superimposition. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Feasibility Study of a Vision-Based Landing System for Unmanned Fixed-Wing Aircraft

DTIC Science & Technology

2017-06-01

International Journal of Computer Science and Network Security 7 no. 3: 112–117. Accessed April 7, 2017. http://www.sciencedirect.com/science/ article /pii...the feasibility of applying computer vision techniques and visual feedback in the control loop for an autonomous system. This thesis examines the...integration into an autonomous aircraft control system. 14. SUBJECT TERMS autonomous systems, auto-land, computer vision, image processing

Surpassing Humans and Computers with JellyBean: Crowd-Vision-Hybrid Counting Algorithms.

PubMed

Sarma, Akash Das; Jain, Ayush; Nandi, Arnab; Parameswaran, Aditya; Widom, Jennifer

2015-11-01

Counting objects is a fundamental image processisng primitive, and has many scientific, health, surveillance, security, and military applications. Existing supervised computer vision techniques typically require large quantities of labeled training data, and even with that, fail to return accurate results in all but the most stylized settings. Using vanilla crowd-sourcing, on the other hand, can lead to significant errors, especially on images with many objects. In this paper, we present our JellyBean suite of algorithms, that combines the best of crowds and computer vision to count objects in images, and uses judicious decomposition of images to greatly improve accuracy at low cost. Our algorithms have several desirable properties: (i) they are theoretically optimal or near-optimal , in that they ask as few questions as possible to humans (under certain intuitively reasonable assumptions that we justify in our paper experimentally); (ii) they operate under stand-alone or hybrid modes, in that they can either work independent of computer vision algorithms, or work in concert with them, depending on whether the computer vision techniques are available or useful for the given setting; (iii) they perform very well in practice, returning accurate counts on images that no individual worker or computer vision algorithm can count correctly, while not incurring a high cost.

Biological Basis For Computer Vision: Some Perspectives

NASA Astrophysics Data System (ADS)

Gupta, Madan M.

1990-03-01

Using biology as a basis for the development of sensors, devices and computer vision systems is a challenge to systems and vision scientists. It is also a field of promising research for engineering applications. Biological sensory systems, such as vision, touch and hearing, sense different physical phenomena from our environment, yet they possess some common mathematical functions. These mathematical functions are cast into the neural layers which are distributed throughout our sensory regions, sensory information transmission channels and in the cortex, the centre of perception. In this paper, we are concerned with the study of the biological vision system and the emulation of some of its mathematical functions, both retinal and visual cortex, for the development of a robust computer vision system. This field of research is not only intriguing, but offers a great challenge to systems scientists in the development of functional algorithms. These functional algorithms can be generalized for further studies in such fields as signal processing, control systems and image processing. Our studies are heavily dependent on the the use of fuzzy - neural layers and generalized receptive fields. Building blocks of such neural layers and receptive fields may lead to the design of better sensors and better computer vision systems. It is hoped that these studies will lead to the development of better artificial vision systems with various applications to vision prosthesis for the blind, robotic vision, medical imaging, medical sensors, industrial automation, remote sensing, space stations and ocean exploration.

Eye movements during visual search in patients with glaucoma

PubMed Central

2012-01-01

Background Glaucoma has been shown to lead to disability in many daily tasks including visual search. This study aims to determine whether the saccadic eye movements of people with glaucoma differ from those of people with normal vision, and to investigate the association between eye movements and impaired visual search. Methods Forty patients (mean age: 67 [SD: 9] years) with a range of glaucomatous visual field (VF) defects in both eyes (mean best eye mean deviation [MD]: –5.9 (SD: 5.4) dB) and 40 age-related people with normal vision (mean age: 66 [SD: 10] years) were timed as they searched for a series of target objects in computer displayed photographs of real world scenes. Eye movements were simultaneously recorded using an eye tracker. Average number of saccades per second, average saccade amplitude and average search duration across trials were recorded. These response variables were compared with measurements of VF and contrast sensitivity. Results The average rate of saccades made by the patient group was significantly smaller than the number made by controls during the visual search task (P = 0.02; mean reduction of 5.6% (95% CI: 0.1 to 10.4%). There was no difference in average saccade amplitude between the patients and the controls (P = 0.09). Average number of saccades was weakly correlated with aspects of visual function, with patients with worse contrast sensitivity (PR logCS; Spearman’s rho: 0.42; P = 0.006) and more severe VF defects (best eye MD; Spearman’s rho: 0.34; P = 0.037) tending to make less eye movements during the task. Average detection time in the search task was associated with the average rate of saccades in the patient group (Spearman’s rho = −0.65; P < 0.001) but this was not apparent in the controls. Conclusions The average rate of saccades made during visual search by this group of patients was fewer than those made by people with normal vision of a similar average age. There was wide variability in saccade rate in the patients but there was an association between an increase in this measure and better performance in the search task. Assessment of eye movements in individuals with glaucoma might provide insight into the functional deficits of the disease. PMID:22937814

Dynamic Vision for Control

DTIC Science & Technology

2006-07-27

unlimited 13. SUPPLEMENTARY NOTES 14. ABSTRACT The goal of this project was to develop analytical and computational tools to make vision a Viable sensor for...vision.ucla. edu July 27, 2006 Abstract The goal of this project was to develop analytical and computational tools to make vision a viable sensor for the ... sensors . We have proposed the framework of stereoscopic segmentation where multiple images of the same obejcts were jointly processed to extract geometry

Using multiple sensors for printed circuit board insertion

NASA Technical Reports Server (NTRS)

Sood, Deepak; Repko, Michael C.; Kelley, Robert B.

1989-01-01

As more and more activities are performed in space, there will be a greater demand placed on the information handling capacity of people who are to direct and accomplish these tasks. A promising alternative to full-time human involvement is the use of semi-autonomous, intelligent robot systems. To automate tasks such as assembly, disassembly, repair and maintenance, the issues presented by environmental uncertainties need to be addressed. These uncertainties are introduced by variations in the computed position of the robot at different locations in its work envelope, variations in part positioning, and tolerances of part dimensions. As a result, the robot system may not be able to accomplish the desired task without the help of sensor feedback. Measurements on the environment allow real time corrections to be made to the process. A design and implementation of an intelligent robot system which inserts printed circuit boards into a card cage are presented. Intelligent behavior is accomplished by coupling the task execution sequence with information derived from three different sensors: an overhead three-dimensional vision system, a fingertip infrared sensor, and a six degree of freedom wrist-mounted force/torque sensor.

The feasibility of using UML to compare the impact of different brands of computer system on the clinical consultation.

PubMed

Kumarapeli, Pushpa; de Lusignan, Simon; Koczan, Phil; Jones, Beryl; Sheeler, Ian

2007-01-01

UK general practice is universally computerised, with computers used in the consulting room at the point of care. Practices use a range of different brands of computer system, which have developed organically to meet the needs of general practitioners and health service managers. Unified Modelling Language (UML) is a standard modelling and specification notation widely used in software engineering. To examine the feasibility of UML notation to compare the impact of different brands of general practice computer system on the clinical consultation. Multi-channel video recordings of simulated consultation sessions were recorded on three different clinical computer systems in common use (EMIS, iSOFT Synergy and IPS Vision). User action recorder software recorded time logs of keyboard and mouse use, and pattern recognition software captured non-verbal communication. The outputs of these were used to create UML class and sequence diagrams for each consultation. We compared 'definition of the presenting problem' and 'prescribing', as these tasks were present in all the consultations analysed. Class diagrams identified the entities involved in the clinical consultation. Sequence diagrams identified common elements of the consultation (such as prescribing) and enabled comparisons to be made between the different brands of computer system. The clinician and computer system interaction varied greatly between the different brands. UML sequence diagrams are useful in identifying common tasks in the clinical consultation, and for contrasting the impact of the different brands of computer system on the clinical consultation. Further research is needed to see if patterns demonstrated in this pilot study are consistently displayed.

Liderazgo visionario (Visionary Leadership). ERIC Digest.

ERIC Educational Resources Information Center

Lashway, Larry

"Vision" is one of the most frequently used buzzwords in the education literature of the 1990s. This digest in Spanish presents an overview of visionary leadership, which many education experts consider to be a make-or-break task for the school leader. It discusses various definitions of vision, the significance of vision for…

Visionary Leadership. ERIC Digest, Number 110.

ERIC Educational Resources Information Center

Lashway, Larry

"Vision" is one of the most frequently used buzzwords in the education literature of the 1990s. This digest presents an overview of visionary leadership, which many education experts consider to be a make-or-break task for the school leader. It discusses various definitions of vision, the significance of vision for organizations, the…

78 FR 34143 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-06

... moving violations in a CMV. Daniel G. Cohen Mr. Cohen, 62, has had a complete loss of vision in his left.... Following an examination in 2012, his ophthalmologist noted, ``In my medical opinion, Mr. Cohen passes all... vision to perform the driving tasks required to operate a commercial vehicle.'' Mr. Cohen reported that...

A digital retina-like low-level vision processor.

PubMed

Mertoguno, S; Bourbakis, N G

2003-01-01

This correspondence presents the basic design and the simulation of a low level multilayer vision processor that emulates to some degree the functional behavior of a human retina. This retina-like multilayer processor is the lower part of an autonomous self-organized vision system, called Kydon, that could be used on visually impaired people with a damaged visual cerebral cortex. The Kydon vision system, however, is not presented in this paper. The retina-like processor consists of four major layers, where each of them is an array processor based on hexagonal, autonomous processing elements that perform a certain set of low level vision tasks, such as smoothing and light adaptation, edge detection, segmentation, line recognition and region-graph generation. At each layer, the array processor is a 2D array of k/spl times/m hexagonal identical autonomous cells that simultaneously execute certain low level vision tasks. Thus, the hardware design and the simulation at the transistor level of the processing elements (PEs) of the retina-like processor and its simulated functionality with illustrative examples are provided in this paper.

Colour blindness in everyday life and car driving.

PubMed

Tagarelli, Antonio; Piro, Anna; Tagarelli, Giuseppe; Lantieri, Pasquale Bruno; Risso, Domenico; Olivieri, Rosario Luciano

2004-08-01

The aim of the present work was to ascertain, through the administration of a psychosocial questionnaire, the difficulties that subjects with defective colour vision experience in carrying out everyday tasks and work, including driving a car with a driver's licence held for no more than 3 years. Subjects with defective colour vision (n = 151) and subjects with normal vision (n = 302) completed a psychosocial questionnaire regarding the difficulties associated with congenital colour vision deficiency in daily life, work and driving a car. Subjects were diagnosed as colour-blind using the Ishihara test. Statistically significant differences between the two samples were found for daily life activities. Subjects with defective colour vision preferred daytime driving. At night, subjects with defective colour vision had difficulty identifying reflectors on the road and the rear signal lights of cars ahead of them. Colour-blind Calabrian subjects admitted to experiencing colour-related difficulties with a wide range of occupational tasks and leisure pursuits. In particular, colour-blind Calabrian subjects preferred daytime driving, and fewer drove regularly, compared to orthochromatics, who were indifferent to night or daytime driving.

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.

A wirelessly programmable actuation and sensing system for structural health monitoring

NASA Astrophysics Data System (ADS)

Long, James; Büyüköztürk, Oral

2016-04-01

Wireless sensor networks promise to deliver low cost, low power and massively distributed systems for structural health monitoring. A key component of these systems, particularly when sampling rates are high, is the capability to process data within the network. Although progress has been made towards this vision, it remains a difficult task to develop and program 'smart' wireless sensing applications. In this paper we present a system which allows data acquisition and computational tasks to be specified in Python, a high level programming language, and executed within the sensor network. Key features of this system include the ability to execute custom application code without firmware updates, to run multiple users' requests concurrently and to conserve power through adjustable sleep settings. Specific examples of sensor node tasks are given to demonstrate the features of this system in the context of structural health monitoring. The system comprises of individual firmware for nodes in the wireless sensor network, and a gateway server and web application through which users can remotely submit their requests.

V-Man Generation for 3-D Real Time Animation. Chapter 5

NASA Technical Reports Server (NTRS)

Nebel, Jean-Christophe; Sibiryakov, Alexander; Ju, Xiangyang

2007-01-01

The V-Man project has developed an intuitive authoring and intelligent system to create, animate, control and interact in real-time with a new generation of 3D virtual characters: The V-Men. It combines several innovative algorithms coming from Virtual Reality, Physical Simulation, Computer Vision, Robotics and Artificial Intelligence. Given a high-level task like "walk to that spot" or "get that object", a V-Man generates the complete animation required to accomplish the task. V-Men synthesise motion at runtime according to their environment, their task and their physical parameters, drawing upon its unique set of skills manufactured during the character creation. The key to the system is the automated creation of realistic V-Men, not requiring the expertise of an animator. It is based on real human data captured by 3D static and dynamic body scanners, which is then processed to generate firstly animatable body meshes, secondly 3D garments and finally skinned body meshes.

A top-down manner-based DCNN architecture for semantic image segmentation.

PubMed

Qiao, Kai; Chen, Jian; Wang, Linyuan; Zeng, Lei; Yan, Bin

2017-01-01

Given their powerful feature representation for recognition, deep convolutional neural networks (DCNNs) have been driving rapid advances in high-level computer vision tasks. However, their performance in semantic image segmentation is still not satisfactory. Based on the analysis of visual mechanism, we conclude that DCNNs in a bottom-up manner are not enough, because semantic image segmentation task requires not only recognition but also visual attention capability. In the study, superpixels containing visual attention information are introduced in a top-down manner, and an extensible architecture is proposed to improve the segmentation results of current DCNN-based methods. We employ the current state-of-the-art fully convolutional network (FCN) and FCN with conditional random field (DeepLab-CRF) as baselines to validate our architecture. Experimental results of the PASCAL VOC segmentation task qualitatively show that coarse edges and error segmentation results are well improved. We also quantitatively obtain about 2%-3% intersection over union (IOU) accuracy improvement on the PASCAL VOC 2011 and 2012 test sets.

Damage Detection and Verification System (DDVS) for In-Situ Health Monitoring

NASA Technical Reports Server (NTRS)

Williams, Martha K.; Lewis, Mark; Szafran, J.; Shelton, C.; Ludwig, L.; Gibson, T.; Lane, J.; Trautwein, T.

2015-01-01

Project presentation for Game Changing Program Smart Book Release. Detection and Verification System (DDVS) expands the Flat Surface Damage Detection System (FSDDS) sensory panels damage detection capabilities and includes an autonomous inspection capability utilizing cameras and dynamic computer vision algorithms to verify system health. Objectives of this formulation task are to establish the concept of operations, formulate the system requirements for a potential ISS flight experiment, and develop a preliminary design of an autonomous inspection capability system that will be demonstrated as a proof-of-concept ground based damage detection and inspection system.

Improving Cognitive Skills of the Industrial Robot

NASA Astrophysics Data System (ADS)

Bezák, Pavol

2015-08-01

At present, there are plenty of industrial robots that are programmed to do the same repetitive task all the time. Industrial robots doing such kind of job are not able to understand whether the action is correct, effective or good. Object detection, manipulation and grasping is challenging due to the hand and object modeling uncertainties, unknown contact type and object stiffness properties. In this paper, the proposal of an intelligent humanoid hand object detection and grasping model is presented assuming that the object properties are known. The control is simulated in the Matlab Simulink/ SimMechanics, Neural Network Toolbox and Computer Vision System Toolbox.

Neural network-based feature point descriptors for registration of optical and SAR images

NASA Astrophysics Data System (ADS)

Abulkhanov, Dmitry; Konovalenko, Ivan; Nikolaev, Dmitry; Savchik, Alexey; Shvets, Evgeny; Sidorchuk, Dmitry

2018-04-01

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method's effectiveness.

A moving observer in a three-dimensional world

PubMed Central

2016-01-01

For many tasks such as retrieving a previously viewed object, an observer must form a representation of the world at one location and use it at another. A world-based three-dimensional reconstruction of the scene built up from visual information would fulfil this requirement, something computer vision now achieves with great speed and accuracy. However, I argue that it is neither easy nor necessary for the brain to do this. I discuss biologically plausible alternatives, including the possibility of avoiding three-dimensional coordinate frames such as ego-centric and world-based representations. For example, the distance, slant and local shape of surfaces dictate the propensity of visual features to move in the image with respect to one another as the observer's perspective changes (through movement or binocular viewing). Such propensities can be stored without the need for three-dimensional reference frames. The problem of representing a stable scene in the face of continual head and eye movements is an appropriate starting place for understanding the goal of three-dimensional vision, more so, I argue, than the case of a static binocular observer. This article is part of the themed issue ‘Vision in our three-dimensional world’. PMID:27269608

Portable Common Execution Environment (PCEE) project review: Peer review

NASA Technical Reports Server (NTRS)

Locke, C. Douglass

1991-01-01

The purpose of the review was to conduct an independent, in-depth analysis of the PCEE project and to provide the results of said review. The review team was tasked with evaluating the potential contribution of the PCEE project to the improvement of the life cycle support of mission and safety critical (MASC) computing components for large, complex, non-stop, distributed systems similar to those planned for such NASA programs as the space station, lunar outpost, and manned missions to Mars. Some conclusions of the review team are as follow: The PCEE project was given high marks for its breath of vision on the overall problem with MASC software; Correlated with the sweeping vision, the Review Team is very skeptical that any research project can successfully attack such a broad range of problems; and several recommendations are made such as to identify the components of the broad solution envisioned, prioritizing them with respect to their impact and the likely ability of the PCEE or others to attack them successfully, and to rewrite its Concept Document differentiating the problem description, objectives, approach, and results so that the project vision becomes assessible to others.

Vision for perception and vision for action: normal and unusual development.

PubMed

Dilks, Daniel D; Hoffman, James E; Landau, Barbara

2008-07-01

Evidence suggests that visual processing is divided into the dorsal ('how') and ventral ('what') streams. We examined the normal development of these streams and their breakdown under neurological deficit by comparing performance of normally developing children and Williams syndrome individuals on two tasks: a visually guided action ('how') task, in which participants posted a card into an oriented slot, and a perception ('what') task, in which they matched a card to the slot's orientation. Results showed that all groups performed worse on the action task than the perception task, but the disparity was more pronounced in WS individuals and in normal 3-4-year-olds than in older children. These findings suggest that the 'how' system may be relatively slow to develop and more vulnerable to breakdown than the 'what' system.

Integrating Sensory/Actuation Systems in Agricultural Vehicles

PubMed Central

Emmi, Luis; Gonzalez-de-Soto, Mariano; Pajares, Gonzalo; Gonzalez-de-Santos, Pablo

2014-01-01

In recent years, there have been major advances in the development of new and more powerful perception systems for agriculture, such as computer-vision and global positioning systems. Due to these advances, the automation of agricultural tasks has received an important stimulus, especially in the area of selective weed control where high precision is essential for the proper use of resources and the implementation of more efficient treatments. Such autonomous agricultural systems incorporate and integrate perception systems for acquiring information from the environment, decision-making systems for interpreting and analyzing such information, and actuation systems that are responsible for performing the agricultural operations. These systems consist of different sensors, actuators, and computers that work synchronously in a specific architecture for the intended purpose. The main contribution of this paper is the selection, arrangement, integration, and synchronization of these systems to form a whole autonomous vehicle for agricultural applications. This type of vehicle has attracted growing interest, not only for researchers but also for manufacturers and farmers. The experimental results demonstrate the success and performance of the integrated system in guidance and weed control tasks in a maize field, indicating its utility and efficiency. The whole system is sufficiently flexible for use in other agricultural tasks with little effort and is another important contribution in the field of autonomous agricultural vehicles. PMID:24577525

Integrating sensory/actuation systems in agricultural vehicles.

PubMed

Emmi, Luis; Gonzalez-de-Soto, Mariano; Pajares, Gonzalo; Gonzalez-de-Santos, Pablo

2014-02-26

In recent years, there have been major advances in the development of new and more powerful perception systems for agriculture, such as computer-vision and global positioning systems. Due to these advances, the automation of agricultural tasks has received an important stimulus, especially in the area of selective weed control where high precision is essential for the proper use of resources and the implementation of more efficient treatments. Such autonomous agricultural systems incorporate and integrate perception systems for acquiring information from the environment, decision-making systems for interpreting and analyzing such information, and actuation systems that are responsible for performing the agricultural operations. These systems consist of different sensors, actuators, and computers that work synchronously in a specific architecture for the intended purpose. The main contribution of this paper is the selection, arrangement, integration, and synchronization of these systems to form a whole autonomous vehicle for agricultural applications. This type of vehicle has attracted growing interest, not only for researchers but also for manufacturers and farmers. The experimental results demonstrate the success and performance of the integrated system in guidance and weed control tasks in a maize field, indicating its utility and efficiency. The whole system is sufficiently flexible for use in other agricultural tasks with little effort and is another important contribution in the field of autonomous agricultural vehicles.

Grasping with the eyes of your hands: hapsis and vision modulate hand preference.

PubMed

Stone, Kayla D; Gonzalez, Claudia L R

2014-02-01

Right-hand preference has been demonstrated for visually guided reaching and grasping. Grasping, however, requires the integration of both visual and haptic cues. To what extent does vision influence hand preference for grasping? Is there a hand preference for haptically guided grasping? Two experiments were designed to address these questions. In Experiment 1, individuals were tested in a reaching-to-grasp task with vision (sighted condition) and with hapsis (blindfolded condition). Participants were asked to put together 3D models using building blocks scattered on a tabletop. The models were simple, composed of ten blocks of three different shapes. Starting condition (Vision-First or Hapsis-First) was counterbalanced among participants. Right-hand preference was greater in visually guided grasping but only in the Vision-First group. Participants who initially built the models while blindfolded (Hapsis-First group) used their right hand significantly less for the visually guided portion of the task. To investigate whether grasping using hapsis modifies subsequent hand preference, participants received an additional haptic experience in a follow-up experiment. While blindfolded, participants manipulated the blocks in a container for 5 min prior to the task. This additional experience did not affect right-hand use on visually guided grasping but had a robust effect on haptically guided grasping. Together, the results demonstrate first that hand preference for grasping is influenced by both vision and hapsis, and second, they highlight how flexible this preference could be when modulated by hapsis.

Sensor fusion IV: Control paradigms and data structures; Proceedings of the Meeting, Boston, MA, Nov. 12-15, 1991

NASA Technical Reports Server (NTRS)

Schenker, Paul S. (Editor)

1992-01-01

Various papers on control paradigms and data structures in sensor fusion are presented. The general topics addressed include: decision models and computational methods, sensor modeling and data representation, active sensing strategies, geometric planning and visualization, task-driven sensing, motion analysis, models motivated biology and psychology, decentralized detection and distributed decision, data fusion architectures, robust estimation of shapes and features, application and implementation. Some of the individual subjects considered are: the Firefly experiment on neural networks for distributed sensor data fusion, manifold traversing as a model for learning control of autonomous robots, choice of coordinate systems for multiple sensor fusion, continuous motion using task-directed stereo vision, interactive and cooperative sensing and control for advanced teleoperation, knowledge-based imaging for terrain analysis, physical and digital simulations for IVA robotics.

Visual and cognitive predictors of performance on brake reaction test: Salisbury eye evaluation driving study.

PubMed

Zhang, Lei; Baldwin, Kevin; Munoz, Beatriz; Munro, Cynthia; Turano, Kathleen; Hassan, Shirin; Lyketsos, Constantine; Bandeen-Roche, Karen; West, Sheila K

2007-01-01

Concern for driving safety has prompted research into understanding factors related to performance. Brake reaction speed (BRS), the speed with which persons react to a sudden change in driving conditions, is a measure of performance. Our aim is to determine the visual, cognitive, and physical factors predicting BRS in a population sample of 1425 older drivers. The Maryland Department of Motor Vehicles roster of persons aged 67-87 and residing in Salisbury, MD, was used for recruitment of the study population. Procedures included the following: habitual, binocular visual acuity using ETDRS charts, contrast sensitivity using a Pelli-Robson chart, visual fields assessed with a 81-point screening Humphrey field at a single intensity threshold, and a questionnaire to ascertain medical conditions. Cognitive status was assessed using a standard battery of tests for attention, memory, visuo-spatial, and scanning. BRS was assessed using a computer-driven device that measured separately the initial reaction speed (IRS) (from light change to red until removing foot from accelerator) and physical response speed (PRS) (removing foot from accelerator to full brake depression). Five trial times were averaged, and time was converted to speed. The median brake reaction time varied from 384 to 5688 milliseconds. Age, gender, and cognition predicted total BRS, a non-informative result as there are two distinct parts to the task. Once separated, decrease in IRS was associated with low scores on cognitive factors and missing points on the visual field. A decrease in PRS was associated with having three or more physical complaints related to legs and feet, and poorer vision search. Vision was not related to PRS. We have demonstrated the importance of segregating the speeds for the two tasks involved in brake reaction. Only the IRS depends on vision. Persons in good physical condition may perform poorly on brake reaction tests if their vision or cognition is compromised.

Impact of 2D and 3D vision on performance of novice subjects using da Vinci robotic system.

PubMed

Blavier, A; Gaudissart, Q; Cadière, G B; Nyssen, A S

2006-01-01

The aim of this study was to evaluate the impact of 3D and 2D vision on performance of novice subjects using da Vinci robotic system. 224 nurses without any surgical experience were divided into two groups and executed a motor task with the robotic system in 2D for one group and with the robotic system in 3D for the other group. Time to perform the task was recorded. Our data showed significant better time performance in 3D view (24.67 +/- 11.2) than in 2D view (40.26 +/- 17.49, P < 0.001). Our findings emphasized the advantage of 3D vision over 2D view in performing surgical task, encouraging the development of efficient and less expensive 3D systems in order to improve the accuracy of surgical gesture, the resident training and the operating time.

Research on three-dimensional reconstruction method based on binocular vision

NASA Astrophysics Data System (ADS)

Li, Jinlin; Wang, Zhihui; Wang, Minjun

2018-03-01

As the hot and difficult issue in computer vision, binocular stereo vision is an important form of computer vision,which has a broad application prospects in many computer vision fields,such as aerial mapping,vision navigation,motion analysis and industrial inspection etc.In this paper, a research is done into binocular stereo camera calibration, image feature extraction and stereo matching. In the binocular stereo camera calibration module, the internal parameters of a single camera are obtained by using the checkerboard lattice of zhang zhengyou the field of image feature extraction and stereo matching, adopted the SURF operator in the local feature operator and the SGBM algorithm in the global matching algorithm are used respectively, and the performance are compared. After completed the feature points matching, we can build the corresponding between matching points and the 3D object points using the camera parameters which are calibrated, which means the 3D information.

Machine learning and computer vision approaches for phenotypic profiling.

PubMed

Grys, Ben T; Lo, Dara S; Sahin, Nil; Kraus, Oren Z; Morris, Quaid; Boone, Charles; Andrews, Brenda J

2017-01-02

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. © 2017 Grys et al.

Machine learning and computer vision approaches for phenotypic profiling

PubMed Central

Morris, Quaid

2017-01-01

With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach. PMID:27940887

Possible Computer Vision Systems and Automated or Computer-Aided Edging and Trimming

Treesearch

Philip A. Araman

1990-01-01

This paper discusses research which is underway to help our industry reduce costs, increase product volume and value recovery, and market more accurately graded and described products. The research is part of a team effort to help the hardwood sawmill industry automate with computer vision systems, and computer-aided or computer controlled processing. This paper...

Discriminative Cooperative Networks for Detecting Phase Transitions

NASA Astrophysics Data System (ADS)

Liu, Ye-Hua; van Nieuwenburg, Evert P. L.

2018-04-01

The classification of states of matter and their corresponding phase transitions is a special kind of machine-learning task, where physical data allow for the analysis of new algorithms, which have not been considered in the general computer-science setting so far. Here we introduce an unsupervised machine-learning scheme for detecting phase transitions with a pair of discriminative cooperative networks (DCNs). In this scheme, a guesser network and a learner network cooperate to detect phase transitions from fully unlabeled data. The new scheme is efficient enough for dealing with phase diagrams in two-dimensional parameter spaces, where we can utilize an active contour model—the snake—from computer vision to host the two networks. The snake, with a DCN "brain," moves and learns actively in the parameter space, and locates phase boundaries automatically.

Are children with low vision adapted to the visual environment in classrooms of mainstream schools?

PubMed

Negiloni, Kalpa; Ramani, Krishna Kumar; Jeevitha, R; Kalva, Jayashree; Sudhir, Rachapalle Reddi

2018-02-01

The study aimed to evaluate the classroom environment of children with low vision and provide recommendations to reduce visual stress, with focus on mainstream schooling. The medical records of 110 children (5-17 years) seen in low vision clinic during 1 year period (2015) at a tertiary care center in south India were extracted. The visual function levels of children were compared to the details of their classroom environment. The study evaluated and recommended the chalkboard visual task size and viewing distance required for children with mild, moderate, and severe visual impairment (VI). The major causes of low vision based on the site of abnormality and etiology were retinal (80%) and hereditary (67%) conditions, respectively, in children with mild (n = 18), moderate (n = 72), and severe (n = 20) VI. Many of the children (72%) had difficulty in viewing chalkboard and common strategies used for better visibility included copying from friends (47%) and going closer to chalkboard (42%). To view the chalkboard with reduced visual stress, a child with mild VI can be seated at a maximum distance of 4.3 m from the chalkboard, with the minimum size of visual task (height of lowercase letter writing on chalkboard) recommended to be 3 cm. For 3/60-6/60 range, the maximum viewing distance with the visual task size of 4 cm is recommended to be 85 cm to 1.7 m. Simple modifications of the visual task size and seating arrangements can aid children with low vision with better visibility of chalkboard and reduced visual stress to manage in mainstream schools.

Factors influencing self-reported vision-related activity limitation in the visually impaired.

PubMed

Tabrett, Daryl R; Latham, Keziah

2011-07-15

The use of patient-reported outcome (PRO) measures to assess self-reported difficulty in visual activities is common in patients with impaired vision. This study determines the visual and psychosocial factors influencing patients' responses to self-report measures, to aid in understanding what is being measured. One hundred visually impaired participants completed the Activity Inventory (AI), which assesses self-reported, vision-related activity limitation (VRAL) in the task domains of reading, mobility, visual information, and visual motor tasks. Participants also completed clinical tests of visual function (distance visual acuity and near reading performance both with and without low vision aids [LVAs], contrast sensitivity, visual fields, and depth discrimination), and questionnaires assessing depressive symptoms, social support, adjustment to visual loss, and personality. Multiple regression analyses identified that an acuity measure (distance or near), and, to a lesser extent, near reading performance without LVAs, visual fields, and contrast sensitivity best explained self-reported VRAL (28%-50% variance explained). Significant psychosocial correlates were depression and adjustment, explaining an additional 6% to 19% unique variance. Dependent on task domain, the parameters assessed explained 59% to 71% of the variance in self-reported VRAL. Visual function, most notably acuity without LVAs, is the best predictor of self-reported VRAL assessed by the AI. Depression and adjustment to visual loss also significantly influence self-reported VRAL, largely independent of the severity of visual loss and most notably in the less vision-specific tasks. The results suggest that rehabilitation strategies addressing depression and adjustment could improve perceived visual disability.

Convolutional networks for fast, energy-efficient neuromorphic computing

PubMed Central

Esser, Steven K.; Merolla, Paul A.; Arthur, John V.; Cassidy, Andrew S.; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J.; McKinstry, Jeffrey L.; Melano, Timothy; Barch, Davis R.; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D.; Modha, Dharmendra S.

2016-01-01

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware’s underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer. PMID:27651489

Convolutional networks for fast, energy-efficient neuromorphic computing.

PubMed

Esser, Steven K; Merolla, Paul A; Arthur, John V; Cassidy, Andrew S; Appuswamy, Rathinakumar; Andreopoulos, Alexander; Berg, David J; McKinstry, Jeffrey L; Melano, Timothy; Barch, Davis R; di Nolfo, Carmelo; Datta, Pallab; Amir, Arnon; Taba, Brian; Flickner, Myron D; Modha, Dharmendra S

2016-10-11

Deep networks are now able to achieve human-level performance on a broad spectrum of recognition tasks. Independently, neuromorphic computing has now demonstrated unprecedented energy-efficiency through a new chip architecture based on spiking neurons, low precision synapses, and a scalable communication network. Here, we demonstrate that neuromorphic computing, despite its novel architectural primitives, can implement deep convolution networks that (i) approach state-of-the-art classification accuracy across eight standard datasets encompassing vision and speech, (ii) perform inference while preserving the hardware's underlying energy-efficiency and high throughput, running on the aforementioned datasets at between 1,200 and 2,600 frames/s and using between 25 and 275 mW (effectively >6,000 frames/s per Watt), and (iii) can be specified and trained using backpropagation with the same ease-of-use as contemporary deep learning. This approach allows the algorithmic power of deep learning to be merged with the efficiency of neuromorphic processors, bringing the promise of embedded, intelligent, brain-inspired computing one step closer.

The Mind's Eye: Reading from "Scientific American."

ERIC Educational Resources Information Center

Scientific American, Inc., New York, NY.

Understanding vision is not a simple task. Nevertheless, a great deal is known about vision, more than about any of our other senses. The articles collected in this volume were chosen and organized with the intention of providing a survey of a number of different areas of vision research. Three major sections focus on the general categories of…

Suitability of School Textbooks for 5 to 7 Year Old Children with Colour Vision Deficiencies

ERIC Educational Resources Information Center

Torrents, Aurora; Bofill, Francesc; Cardona, Genis

2011-01-01

Purpose: The aim of the present study was to determine, through colorimetric analysis, whether school textbooks for children aged 5 to 7 years contained tasks requiring normal colour vision discrimination for their resolution. In addition, the performance of a group of observers with diverse colour vision deficiencies was evaluated while…

Reading by Children with Low Vision

ERIC Educational Resources Information Center

Gompel, Marjolein; van Bon, Wim H. J.; Schreuder, Robert

2004-01-01

This study of the reading of text found that despite their lower reading speed on a reading-comprehension task, the children with low vision comprehended texts at least as well as did the sighted children. Children with low vision need more time to read and comprehend a text, but they seem to use this time with enough efficiency to process the…

Smartphone, tablet computer and e-reader use by people with vision impairment.

PubMed

Crossland, Michael D; Silva, Rui S; Macedo, Antonio F

2014-09-01

Consumer electronic devices such as smartphones, tablet computers, and e-book readers have become far more widely used in recent years. Many of these devices contain accessibility features such as large print and speech. Anecdotal experience suggests people with vision impairment frequently make use of these systems. Here we survey people with self-identified vision impairment to determine their use of this equipment. An internet-based survey was advertised to people with vision impairment by word of mouth, social media, and online. Respondents were asked demographic information, what devices they owned, what they used these devices for, and what accessibility features they used. One hundred and thirty-two complete responses were received. Twenty-six percent of the sample reported that they had no vision and the remainder reported they had low vision. One hundred and seven people (81%) reported using a smartphone. Those with no vision were as likely to use a smartphone or tablet as those with low vision. Speech was found useful by 59% of smartphone users. Fifty-one percent of smartphone owners used the camera and screen as a magnifier. Forty-eight percent of the sample used a tablet computer, and 17% used an e-book reader. The most frequently cited reason for not using these devices included cost and lack of interest. Smartphones, tablet computers, and e-book readers can be used by people with vision impairment. Speech is used by people with low vision as well as those with no vision. Many of our (self-selected) group used their smartphone camera and screen as a magnifier, and others used the camera flash as a spotlight. © 2014 The Authors Ophthalmic & Physiological Optics © 2014 The College of Optometrists.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources.

PubMed

Liu, Yu-Ting; Pal, Nikhil R; Marathe, Amar R; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems.

Fuzzy Decision-Making Fuser (FDMF) for Integrating Human-Machine Autonomous (HMA) Systems with Adaptive Evidence Sources

PubMed Central

Liu, Yu-Ting; Pal, Nikhil R.; Marathe, Amar R.; Wang, Yu-Kai; Lin, Chin-Teng

2017-01-01

A brain-computer interface (BCI) creates a direct communication pathway between the human brain and an external device or system. In contrast to patient-oriented BCIs, which are intended to restore inoperative or malfunctioning aspects of the nervous system, a growing number of BCI studies focus on designing auxiliary systems that are intended for everyday use. The goal of building these BCIs is to provide capabilities that augment existing intact physical and mental capabilities. However, a key challenge to BCI research is human variability; factors such as fatigue, inattention, and stress vary both across different individuals and for the same individual over time. If these issues are addressed, autonomous systems may provide additional benefits that enhance system performance and prevent problems introduced by individual human variability. This study proposes a human-machine autonomous (HMA) system that simultaneously aggregates human and machine knowledge to recognize targets in a rapid serial visual presentation (RSVP) task. The HMA focuses on integrating an RSVP BCI with computer vision techniques in an image-labeling domain. A fuzzy decision-making fuser (FDMF) is then applied in the HMA system to provide a natural adaptive framework for evidence-based inference by incorporating an integrated summary of the available evidence (i.e., human and machine decisions) and associated uncertainty. Consequently, the HMA system dynamically aggregates decisions involving uncertainties from both human and autonomous agents. The collaborative decisions made by an HMA system can achieve and maintain superior performance more efficiently than either the human or autonomous agents can achieve independently. The experimental results shown in this study suggest that the proposed HMA system with the FDMF can effectively fuse decisions from human brain activities and the computer vision techniques to improve overall performance on the RSVP recognition task. This conclusion demonstrates the potential benefits of integrating autonomous systems with BCI systems. PMID:28676734

Clinical predictors of the optimal spectacle correction for comfort performing desktop tasks.

PubMed

Leffler, Christopher T; Davenport, Byrd; Rentz, Jodi; Miller, Amy; Benson, William

2008-11-01

The best strategy for spectacle correction of presbyopia for near tasks has not been determined. Thirty volunteers over the age of 40 years were tested for subjective accommodative amplitude, pupillary size, fusional vergence, interpupillary distance, arm length, preferred working distance, near and far visual acuity and preferred reading correction in the phoropter and trial frames. Subjects performed near tasks (reading, writing and counting change) using various spectacle correction strengths. Predictors of the correction maximising near task comfort were determined by multivariable linear regression. The mean age was 54.9 years (range 43 to 71) and 40 per cent had diabetes. Significant predictors of the most comfortable addition in univariate analyses were age (p<0.001), interpupillary distance (p=0.02), fusional vergence amplitude (p=0.02), distance visual acuity in the worse eye (p=0.01), vision at 40 cm in the worse eye with distance correction (p=0.01), duration of diabetes (p=0.01), and the preferred correction to read at 40 cm with the phoropter (p=0.002) or trial frames (p<0.001). Target distance selected wearing trial frames (in dioptres), arm length, and accommodative amplitude were not significant predictors (p>0.15). The preferred addition wearing trial frames holding a reading target at a distance selected by the patient was the only independent predictor. Excluding this variable, distance visual acuity was predictive independent of age or near vision wearing distance correction. The distance selected for task performance was predicted by vision wearing distance correction at near and at distance. Multivariable linear regression can be used to generate tables based on distance visual acuity and age or near vision wearing distance correction to determine tentative near spectacle addition. Final spectacle correction for desktop tasks can be estimated by subjective refraction with trial frames.

Development of a Wireless Computer Vision Instrument to Detect Biotic Stress in Wheat

PubMed Central

Casanova, Joaquin J.; O'Shaughnessy, Susan A.; Evett, Steven R.; Rush, Charles M.

2014-01-01

Knowledge of crop abiotic and biotic stress is important for optimal irrigation management. While spectral reflectance and infrared thermometry provide a means to quantify crop stress remotely, these measurements can be cumbersome. Computer vision offers an inexpensive way to remotely detect crop stress independent of vegetation cover. This paper presents a technique using computer vision to detect disease stress in wheat. Digital images of differentially stressed wheat were segmented into soil and vegetation pixels using expectation maximization (EM). In the first season, the algorithm to segment vegetation from soil and distinguish between healthy and stressed wheat was developed and tested using digital images taken in the field and later processed on a desktop computer. In the second season, a wireless camera with near real-time computer vision capabilities was tested in conjunction with the conventional camera and desktop computer. For wheat irrigated at different levels and inoculated with wheat streak mosaic virus (WSMV), vegetation hue determined by the EM algorithm showed significant effects from irrigation level and infection. Unstressed wheat had a higher hue (118.32) than stressed wheat (111.34). In the second season, the hue and cover measured by the wireless computer vision sensor showed significant effects from infection (p = 0.0014), as did the conventional camera (p < 0.0001). Vegetation hue obtained through a wireless computer vision system in this study is a viable option for determining biotic crop stress in irrigation scheduling. Such a low-cost system could be suitable for use in the field in automated irrigation scheduling applications. PMID:25251410

Effects of visual information regarding allocentric processing in haptic parallelity matching.

PubMed

Van Mier, Hanneke I

2013-10-01

Research has revealed that haptic perception of parallelity deviates from physical reality. Large and systematic deviations have been found in haptic parallelity matching most likely due to the influence of the hand-centered egocentric reference frame. Providing information that increases the influence of allocentric processing has been shown to improve performance on haptic matching. In this study allocentric processing was stimulated by providing informative vision in haptic matching tasks that were performed using hand- and arm-centered reference frames. Twenty blindfolded participants (ten men, ten women) explored the orientation of a reference bar with the non-dominant hand and subsequently matched (task HP) or mirrored (task HM) its orientation on a test bar with the dominant hand. Visual information was provided by means of informative vision with participants having full view of the test bar, while the reference bar was blocked from their view (task VHP). To decrease the egocentric bias of the hands, participants also performed a visual haptic parallelity drawing task (task VHPD) using an arm-centered reference frame, by drawing the orientation of the reference bar. In all tasks, the distance between and orientation of the bars were manipulated. A significant effect of task was found; performance improved from task HP, to VHP to VHPD, and HM. Significant effects of distance were found in the first three tasks, whereas orientation and gender effects were only significant in tasks HP and VHP. The results showed that stimulating allocentric processing by means of informative vision and reducing the egocentric bias by using an arm-centered reference frame led to most accurate performance on parallelity matching. © 2013 Elsevier B.V. All rights reserved.

Relationship between binocular vision, visual acuity, and fine motor skills.

PubMed

O'Connor, Anna R; Birch, Eileen E; Anderson, Susan; Draper, Hayley

2010-12-01

The aims of this study were to analyze the relationship between the performance on fine motor skills tasks and peripheral and bifoveal sensory fusion, phasic and tonic motor fusion, the level of visual acuity (VA) in the poorer seeing eye, and the interocular VA difference. Subjects aged 12 to 28 years with a range of levels of binocular vision and VA performed three tasks: Purdue pegboard (number of pegs placed in 30 s), bead threading task (with two sizes of bead to increase the difficulty, time taken to thread a fixed number of beads), and a water pouring task (accuracy and time to pour a fixed quantity into five glass cylinders). Ophthalmic measures included peripheral (Worth 4 dot) and bifoveal (4 prism diopter) sensory fusion, phasic (prism bar) and tonic (Risley rotary prism) motor fusion ranges, and monocular VA. One hundred twenty-one subjects with a mean age of 18.8 years were tested; 18.2% had a manifest strabismus. Performance on fine motor skills tasks was significantly better in subjects with sensory and motor fusion compared with those without for most tasks, with significant differences between those with and without all measures of fusion on the pegboard and bead task. Both the acuity in the poorer seeing eye (highest r value of all motor tasks = 0.43) and the interocular acuity difference were statistically significantly related to performance on the motor skill tasks. Both sensory and motor fusion and good VA in both eyes are of benefit in the performance of fine motor skills tasks, with the presence of some binocular vision being beneficial compared with no fusion on certain sensorimotor tasks. This evidence supports the need to maximize fusion and VA outcomes.

Computer vision challenges and technologies for agile manufacturing

NASA Astrophysics Data System (ADS)

Molley, Perry A.

1996-02-01

Sandia National Laboratories, a Department of Energy laboratory, is responsible for maintaining the safety, security, reliability, and availability of the nuclear weapons stockpile for the United States. Because of the changing national and global political climates and inevitable budget cuts, Sandia is changing the methods and processes it has traditionally used in the product realization cycle for weapon components. Because of the increasing age of the nuclear stockpile, it is certain that the reliability of these weapons will degrade with time unless eventual action is taken to repair, requalify, or renew them. Furthermore, due to the downsizing of the DOE weapons production sites and loss of technical personnel, the new product realization process is being focused on developing and deploying advanced automation technologies in order to maintain the capability for producing new components. The goal of Sandia's technology development program is to create a product realization environment that is cost effective, has improved quality and reduced cycle time for small lot sizes. The new environment will rely less on the expertise of humans and more on intelligent systems and automation to perform the production processes. The systems will be robust in order to provide maximum flexibility and responsiveness for rapidly changing component or product mixes. An integrated enterprise will allow ready access to and use of information for effective and efficient product and process design. Concurrent engineering methods will allow a speedup of the product realization cycle, reduce costs, and dramatically lessen the dependency on creating and testing physical prototypes. Virtual manufacturing will allow production processes to be designed, integrated, and programed off-line before a piece of hardware ever moves. The overriding goal is to be able to build a large variety of new weapons parts on short notice. Many of these technologies that are being developed are also applicable to commercial production processes and applications. Computer vision will play a critical role in the new agile production environment for automation of processes such as inspection, assembly, welding, material dispensing and other process control tasks. Although there are many academic and commercial solutions that have been developed, none have had widespread adoption considering the huge potential number of applications that could benefit from this technology. The reason for this slow adoption is that the advantages of computer vision for automation can be a double-edged sword. The benefits can be lost if the vision system requires an inordinate amount of time for reprogramming by a skilled operator to account for different parts, changes in lighting conditions, background clutter, changes in optics, etc. Commercially available solutions typically require an operator to manually program the vision system with features used for the recognition. In a recent survey, we asked a number of commercial manufacturers and machine vision companies the question, 'What prevents machine vision systems from being more useful in factories?' The number one (and unanimous) response was that vision systems require too much skill to set up and program to be cost effective.

Computer vision-based analysis of foods: a non-destructive colour measurement tool to monitor quality and safety.

PubMed

Mogol, Burçe Ataç; Gökmen, Vural

2014-05-01

Computer vision-based image analysis has been widely used in food industry to monitor food quality. It allows low-cost and non-contact measurements of colour to be performed. In this paper, two computer vision-based image analysis approaches are discussed to extract mean colour or featured colour information from the digital images of foods. These types of information may be of particular importance as colour indicates certain chemical changes or physical properties in foods. As exemplified here, the mean CIE a* value or browning ratio determined by means of computer vision-based image analysis algorithms can be correlated with acrylamide content of potato chips or cookies. Or, porosity index as an important physical property of breadcrumb can be calculated easily. In this respect, computer vision-based image analysis provides a useful tool for automatic inspection of food products in a manufacturing line, and it can be actively involved in the decision-making process where rapid quality/safety evaluation is needed. © 2013 Society of Chemical Industry.

Multi-Stage System for Automatic Target Recognition

NASA Technical Reports Server (NTRS)

Chao, Tien-Hsin; Lu, Thomas T.; Ye, David; Edens, Weston; Johnson, Oliver

2010-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feedforward back-propagation neural network (NN) is then trained to classify each feature vector and to remove false positives. The system parameter optimizations process has been developed to adapt to various targets and datasets. The objective was to design an efficient computer vision system that can learn to detect multiple targets in large images with unknown backgrounds. Because the target size is small relative to the image size in this problem, there are many regions of the image that could potentially contain the target. A cursory analysis of every region can be computationally efficient, but may yield too many false positives. On the other hand, a detailed analysis of every region can yield better results, but may be computationally inefficient. The multi-stage ATR system was designed to achieve an optimal balance between accuracy and computational efficiency by incorporating both models. The detection stage first identifies potential ROIs where the target may be present by performing a fast Fourier domain OT-MACH filter-based correlation. Because threshold for this stage is chosen with the goal of detecting all true positives, a number of false positives are also detected as ROIs. The verification stage then transforms the regions of interest into feature space, and eliminates false positives using an artificial neural network classifier. The multi-stage system allows tuning the detection sensitivity and the identification specificity individually in each stage. It is easier to achieve optimized ATR operation based on its specific goal. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar and video image datasets.

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

PubMed

Kriegeskorte, Nikolaus

2015-11-24

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

Development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification

NASA Astrophysics Data System (ADS)

Astafiev, A.; Orlov, A.; Privezencev, D.

2018-01-01

The article is devoted to the development of technology and software for the construction of positioning and control systems in industrial plants based on aggregation to determine the current storage area using computer vision and radiofrequency identification. It describes the developed of the project of hardware for industrial products positioning system in the territory of a plant on the basis of radio-frequency grid. It describes the development of the project of hardware for industrial products positioning system in the plant on the basis of computer vision methods. It describes the development of the method of aggregation to determine the current storage area using computer vision and radiofrequency identification. Experimental studies in laboratory and production conditions have been conducted and described in the article.

Assessing the severity of color vision loss with implications for aviation and other occupational environments.

PubMed

Rodriguez-Carmona, Marisa; O'Neill-Biba, Matilda; Barbur, John L

2012-01-01

The Ishihara Test (IT) is arguably the most sensitive and commonly used color vision test within aviation and other occupational environments, but when no errors are allowed -20% of normal trichromats fail the test. The number of allowed errors varies in different occupations and sometimes within the same environment (such as aviation) in order to reflect the difficulties of the color-related tasks. The implicit assumption is that the plates can be ranked in order of difficulty. The principal aim of this study was to investigate whether appropriate "weights" can be attached to each IT plate to reflect the likelihood of producing a correct response. A second aim was to justify the use of color thresholds for quantifying the loss of red-green (RG) and yellow-blue (YB) chromatic sensitivity. We investigated 742 subjects (236 normals, 340 deutans, and 166 protans) using the first 25 plates of the 38-plate IT and measured RG chromatic sensitivity using the Color Assessment and Diagnosis (CAD) test. The IT error scores provided plate-specific "weights" which were used to calculate a Severity Index (SI) of color vision loss for each subject. Error scores, SI values, and CAD thresholds were measured and compared in each of the three subject groups. Color thresholds can provide a good measure of the severity of both RG and YB color vision loss. Neither the number of IT plates failed nor the SI value computed in this way can be used to determine reliably the severity of color vision loss.

The handicap of abnormal colour vision.

PubMed

Cole, Barry L

2004-07-01

All people with abnormal colour vision, except for a few mildly affected deuteranomals, report that they experience problems with colour in everyday life and at work. Contemporary society presents them with increasing problems because colour is now so widely used in printed materials and in computer displays. Equal opportunity law gives them protection against unfair discrimination in employment, so a decision to exclude a person from employment on the grounds of abnormal colour vision must now be well supported by good evidence and sound argument. This paper reviews the investigations that have contributed to understanding the nature and consequences of the problems they have. All those with abnormal colour vision are at a disadvantage with comparative colour tasks that involve precise matching of colours or discrimination of fine colour differences either because of their loss of colour discrimination or anomalous perception of metamers. The majority have problems when colour is used to code information, in man-made colour codes and in naturally occurring colour codes that signal ripeness of fruit, freshness of meat or illness. They can be denied the benefit of colour to mark out objects and organise complex visual displays. They may be unreliable when a colour name is used as an identifier. They are slower and less successful in search when colour is an attribute of the target object or is used to organise the visual display. Because those with the more severe forms of abnormal colour vision perceive a very limited gamut of colours, they are at a disadvantage in the pursuit and appreciation of those forms of art that use colour.

78 FR 24798 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2013-04-26

... exceeded the speed limit by 13 mph. Marcus R. Watkins Mr. Watkins, 50, has had a retinal detachment in his... vision to perform driving tasks required to operate a commercial vehicle.'' Mr. Watkins reported that he...

Latency in Visionic Systems: Test Methods and Requirements

NASA Technical Reports Server (NTRS)

Bailey, Randall E.; Arthur, J. J., III; Williams, Steven P.; Kramer, Lynda J.

2005-01-01

A visionics device creates a pictorial representation of the external scene for the pilot. The ultimate objective of these systems may be to electronically generate a form of Visual Meteorological Conditions (VMC) to eliminate weather or time-of-day as an operational constraint and provide enhancement over actual visual conditions where eye-limiting resolution may be a limiting factor. Empirical evidence has shown that the total system delays or latencies including the imaging sensors and display systems, can critically degrade their utility, usability, and acceptability. Definitions and measurement techniques are offered herein as common test and evaluation methods for latency testing in visionics device applications. Based upon available data, very different latency requirements are indicated based upon the piloting task, the role in which the visionics device is used in this task, and the characteristics of the visionics cockpit display device including its resolution, field-of-regard, and field-of-view. The least stringent latency requirements will involve Head-Up Display (HUD) applications, where the visionics imagery provides situational information as a supplement to symbology guidance and command information. Conversely, the visionics system latency requirement for a large field-of-view Head-Worn Display application, providing a Virtual-VMC capability from which the pilot will derive visual guidance, will be the most stringent, having a value as low as 20 msec.

Enhanced computer vision with Microsoft Kinect sensor: a review.

PubMed

Han, Jungong; Shao, Ling; Xu, Dong; Shotton, Jamie

2013-10-01

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.

Texture and art with deep neural networks.

PubMed

Gatys, Leon A; Ecker, Alexander S; Bethge, Matthias

2017-10-01

Although the study of biological vision and computer vision attempt to understand powerful visual information processing from different angles, they have a long history of informing each other. Recent advances in texture synthesis that were motivated by visual neuroscience have led to a substantial advance in image synthesis and manipulation in computer vision using convolutional neural networks (CNNs). Here, we review these recent advances and discuss how they can in turn inspire new research in visual perception and computational neuroscience. Copyright © 2017. Published by Elsevier Ltd.

Visual Search in the Real World: Color Vision Deficiency Affects Peripheral Guidance, but Leaves Foveal Verification Largely Unaffected.

PubMed

Kugler, Günter; 't Hart, Bernard M; Kohlbecher, Stefan; Bartl, Klaus; Schumann, Frank; Einhäuser, Wolfgang; Schneider, Erich

2015-01-01

People with color vision deficiencies report numerous limitations in daily life, restricting, for example, their access to some professions. However, they use basic color terms systematically and in a similar manner as people with normal color vision. We hypothesize that a possible explanation for this discrepancy between color perception and behavioral consequences might be found in the gaze behavior of people with color vision deficiency. A group of participants with color vision deficiencies and a control group performed several search tasks in a naturalistic setting on a lawn. All participants wore a mobile eye-tracking-driven camera with a high foveal image resolution (EyeSeeCam). Search performance as well as fixations of objects of different colors were examined. Search performance was similar in both groups in a color-unrelated search task as well as in a search for yellow targets. While searching for red targets, participants with color vision deficiencies exhibited a strongly degraded performance. This was closely matched by the number of fixations on red objects shown by the two groups. Importantly, once they fixated a target, participants with color vision deficiencies exhibited only few identification errors. In contrast to controls, participants with color vision deficiencies are not able to enhance their search for red targets on a (green) lawn by an efficient guiding mechanism. The data indicate that the impaired guiding is the main influence on search performance, while foveal identification (verification) is largely unaffected by the color vision deficiency.

A comparative study of deep learning models for medical image classification

NASA Astrophysics Data System (ADS)

Dutta, Suvajit; Manideep, B. C. S.; Rai, Shalva; Vijayarajan, V.

2017-11-01

Deep Learning(DL) techniques are conquering over the prevailing traditional approaches of neural network, when it comes to the huge amount of dataset, applications requiring complex functions demanding increase accuracy with lower time complexities. Neurosciences has already exploited DL techniques, thus portrayed itself as an inspirational source for researchers exploring the domain of Machine learning. DL enthusiasts cover the areas of vision, speech recognition, motion planning and NLP as well, moving back and forth among fields. This concerns with building models that can successfully solve variety of tasks requiring intelligence and distributed representation. The accessibility to faster CPUs, introduction of GPUs-performing complex vector and matrix computations, supported agile connectivity to network. Enhanced software infrastructures for distributed computing worked in strengthening the thought that made researchers suffice DL methodologies. The paper emphases on the following DL procedures to traditional approaches which are performed manually for classifying medical images. The medical images are used for the study Diabetic Retinopathy(DR) and computed tomography (CT) emphysema data. Both DR and CT data diagnosis is difficult task for normal image classification methods. The initial work was carried out with basic image processing along with K-means clustering for identification of image severity levels. After determining image severity levels ANN has been applied on the data to get the basic classification result, then it is compared with the result of DNNs (Deep Neural Networks), which performed efficiently because of its multiple hidden layer features basically which increases accuracy factors, but the problem of vanishing gradient in DNNs made to consider Convolution Neural Networks (CNNs) as well for better results. The CNNs are found to be providing better outcomes when compared to other learning models aimed at classification of images. CNNs are favoured as they provide better visual processing models successfully classifying the noisy data as well. The work centres on the detection on Diabetic Retinopathy-loss in vision and recognition of computed tomography (CT) emphysema data measuring the severity levels for both cases. The paper discovers how various Machine Learning algorithms can be implemented ensuing a supervised approach, so as to get accurate results with less complexity possible.

The role of vision, speed, and attention in overcoming directional biases during arm movements.

PubMed

Dounskaia, Natalia; Goble, Jacob A

2011-03-01

Previous research has revealed directional biases (preferences to select movements in specific directions) during horizontal arm movements with the use of a free-stroke drawing task. The biases were interpreted as a result of a tendency to generate motion at either the shoulder or elbow (leading joint) and move the other (subordinate) joint predominantly passively to avoid neural effort for control of interaction torque. Here, we examined influence of vision, movement speed, and attention on the directional biases. Participants performed the free-stroke drawing task, producing center-out strokes in randomly selected directions. Movements were performed with and without vision and at comfortable and fast pace. A secondary, cognitive task was used to distract attention. Preferred directions remained the same in all conditions. Bias strength mildly increased without vision, especially during fast movements. Striking increases in bias strength were caused by the secondary task, pointing to additional cognitive load associated with selection of movements in the non-preferred directions. Further analyses demonstrated that the tendency to minimize active interference with interaction torque at the subordinate joint matched directional biases in all conditions. This match supports the explanation of directional biases as a result of a tendency to minimize neural effort for interaction torque control. The cognitive load may enhance this tendency in two ways, directly, by reducing neural capacity for interaction torque control, and indirectly, by decreasing capacity of working memory that stores visited directions. The obtained results suggest strong directional biases during daily activities because natural arm movements usually subserve cognitive tasks.

Quality of life and near vision impairment due to functional presbyopia among rural Chinese adults.

PubMed

Lu, Qing; Congdon, Nathan; He, Xiangdong; Murthy, Gudlavalleti V S; Yang, Amy; He, Wei

2011-06-13

To evaluate the impact of near-vision impairment on visual functioning and quality of life in a rural adult population in Shenyang, northern China. A population-based, cross-sectional study was conducted among persons aged 40+ years, during which functional presbyopia (correctable presenting near vision < 20/50 [N8] at 40 cm) was assessed. Near-vision-related quality of life and spectacle usage questionnaires were administered by trained interviewers to determine the degree of self-rated difficulty with near tasks. A total of 1008 respondents (91.5% of 1102 eligible persons) were examined, and 776 (78%) of completed the questionnaires (mean age, 57.0 ± 10.2 years; 63.3% women). Near-vision spectacle wearers obtained their spectacles primarily from markets (74.5%) and optical shops (21.7%), and only 1.14% from eye clinics. Among 538 (69.3%) persons with functional presbyopia, self-rated overall (distance and near) vision was worse (P < 0.001) and difficulty with activities of daily living greater (P < 0.001) than among nonpresbyopes. Odds of reporting any difficulty with daily tasks remained higher (OR = 2.32; P < 0.001) for presbyopes after adjustment for age, sex, education and distance vision. Compared to persons without presbyopia, presbyopic persons were more likely to report diminished accomplishment due to vision (P = 0.01, adjusted for age, sex, education, and distance vision.) Difficulties with activities of daily living and resulting social impediments are common due to presbyopia in this setting. Most spectacle wearers with presbyopia in rural China obtain near correction from sources that do not provide comprehensive vision care.

Impact of computer use on children's vision.

PubMed

Kozeis, N

2009-10-01

Today, millions of children use computers on a daily basis. Extensive viewing of the computer screen can lead to eye discomfort, fatigue, blurred vision and headaches, dry eyes and other symptoms of eyestrain. These symptoms may be caused by poor lighting, glare, an improper work station set-up, vision problems of which the person was not previously aware, or a combination of these factors. Children can experience many of the same symptoms related to computer use as adults. However, some unique aspects of how children use computers may make them more susceptible than adults to the development of these problems. In this study, the most common eye symptoms related to computer use in childhood, the possible causes and ways to avoid them are reviewed.

Vision Guided Intelligent Robot Design And Experiments

NASA Astrophysics Data System (ADS)

Slutzky, G. D.; Hall, E. L.

1988-02-01

The concept of an intelligent robot is an important topic combining sensors, manipulators, and artificial intelligence to design a useful machine. Vision systems, tactile sensors, proximity switches and other sensors provide the elements necessary for simple game playing as well as industrial applications. These sensors permit adaption to a changing environment. The AI techniques permit advanced forms of decision making, adaptive responses, and learning while the manipulator provides the ability to perform various tasks. Computer languages such as LISP and OPS5, have been utilized to achieve expert systems approaches in solving real world problems. The purpose of this paper is to describe several examples of visually guided intelligent robots including both stationary and mobile robots. Demonstrations will be presented of a system for constructing and solving a popular peg game, a robot lawn mower, and a box stacking robot. The experience gained from these and other systems provide insight into what may be realistically expected from the next generation of intelligent machines.

Neural Network Target Identification System for False Alarm Reduction

NASA Technical Reports Server (NTRS)

Ye, David; Edens, Weston; Lu, Thomas T.; Chao, Tien-Hsin

2009-01-01

A multi-stage automated target recognition (ATR) system has been designed to perform computer vision tasks with adequate proficiency in mimicking human vision. The system is able to detect, identify, and track targets of interest. Potential regions of interest (ROIs) are first identified by the detection stage using an Optimum Trade-off Maximum Average Correlation Height (OT-MACH) filter combined with a wavelet transform. False positives are then eliminated by the verification stage using feature extraction methods in conjunction with neural networks. Feature extraction transforms the ROIs using filtering and binning algorithms to create feature vectors. A feed forward back propagation neural network (NN) is then trained to classify each feature vector and remove false positives. This paper discusses the test of the system performance and parameter optimizations process which adapts the system to various targets and datasets. The test results show that the system was successful in substantially reducing the false positive rate when tested on a sonar image dataset.

The Application of Virtex-II Pro FPGA in High-Speed Image Processing Technology of Robot Vision Sensor

NASA Astrophysics Data System (ADS)

Ren, Y. J.; Zhu, J. G.; Yang, X. Y.; Ye, S. H.

2006-10-01

The Virtex-II Pro FPGA is applied to the vision sensor tracking system of IRB2400 robot. The hardware platform, which undertakes the task of improving SNR and compressing data, is constructed by using the high-speed image processing of FPGA. The lower level image-processing algorithm is realized by combining the FPGA frame and the embedded CPU. The velocity of image processing is accelerated due to the introduction of FPGA and CPU. The usage of the embedded CPU makes it easily to realize the logic design of interface. Some key techniques are presented in the text, such as read-write process, template matching, convolution, and some modules are simulated too. In the end, the compare among the modules using this design, using the PC computer and using the DSP, is carried out. Because the high-speed image processing system core is a chip of FPGA, the function of which can renew conveniently, therefore, to a degree, the measure system is intelligent.

Activity Recognition in Egocentric video using SVM, kNN and Combined SVMkNN Classifiers

NASA Astrophysics Data System (ADS)

Sanal Kumar, K. P.; Bhavani, R., Dr.

2017-08-01

Egocentric vision is a unique perspective in computer vision which is human centric. The recognition of egocentric actions is a challenging task which helps in assisting elderly people, disabled patients and so on. In this work, life logging activity videos are taken as input. There are 2 categories, first one is the top level and second one is second level. Here, the recognition is done using the features like Histogram of Oriented Gradients (HOG), Motion Boundary Histogram (MBH) and Trajectory. The features are fused together and it acts as a single feature. The extracted features are reduced using Principal Component Analysis (PCA). The features that are reduced are provided as input to the classifiers like Support Vector Machine (SVM), k nearest neighbor (kNN) and combined Support Vector Machine (SVM) and k Nearest Neighbor (kNN) (combined SVMkNN). These classifiers are evaluated and the combined SVMkNN provided better results than other classifiers in the literature.

Reducing the Time and Cost of Testing Engines

NASA Technical Reports Server (NTRS)

2004-01-01

Producing a new aircraft engine currently costs approximately $1 billion, with 3 years of development time for a commercial engine and 10 years for a military engine. The high development time and cost make it extremely difficult to transition advanced technologies for cleaner, quieter, and more efficient new engines. To reduce this time and cost, NASA created a vision for the future where designers would use high-fidelity computer simulations early in the design process in order to resolve critical design issues before building the expensive engine hardware. To accomplish this vision, NASA's Glenn Research Center initiated a collaborative effort with the aerospace industry and academia to develop its Numerical Propulsion System Simulation (NPSS), an advanced engineering environment for the analysis and design of aerospace propulsion systems and components. Partners estimate that using NPSS has the potential to dramatically reduce the time, effort, and expense necessary to design and test jet engines by generating sophisticated computer simulations of an aerospace object or system. These simulations will permit an engineer to test various design options without having to conduct costly and time-consuming real-life tests. By accelerating and streamlining the engine system design analysis and test phases, NPSS facilitates bringing the final product to market faster. NASA's NPSS Version (V)1.X effort was a task within the Agency s Computational Aerospace Sciences project of the High Performance Computing and Communication program, which had a mission to accelerate the availability of high-performance computing hardware and software to the U.S. aerospace community for its use in design processes. The technology brings value back to NASA by improving methods of analyzing and testing space transportation components.

Operational Assessment of Color Vision

DTIC Science & Technology

2016-06-20

evaluated in this study. 15. SUBJECT TERMS Color vision, aviation, cone contrast test, Colour Assessment & Diagnosis , color Dx, OBVA 16. SECURITY...symbologies are frequently used to aid or direct critical activities such as aircraft landing approaches or railroad right-of-way designations...computer-generated display systems have facilitated the development of computer-based, automated tests of color vision [14,15]. The United Kingdom’s

Neo-Symbiosis: The Next Stage in the Evolution of Human Information Interaction

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

Griffith, Douglas; Greitzer, Frank L.

We re-address the vision of human-computer symbiosis expressed by J. C. R. Licklider nearly a half-century ago, when he wrote: “The hope is that in not too many years, human brains and computing machines will be coupled together very tightly, and that the resulting partnership will think as no human brain has ever thought and process data in a way not approached by the information-handling machines we know today.” (Licklider, 1960). Unfortunately, little progress was made toward this vision over four decades following Licklider’s challenge, despite significant advancements in the fields of human factors and computer science. Licklider’s vision wasmore » largely forgotten. However, recent advances in information science and technology, psychology, and neuroscience have rekindled the potential of making the Licklider’s vision a reality. This paper provides a historical context for and updates the vision, and it argues that such a vision is needed as a unifying framework for advancing IS&T.« less

An analysis of observer-rated functional vision in patients implanted with the Argus II Retinal Prosthesis System at three years.

PubMed

Geruschat, Duane R; Richards, Thomas P; Arditi, Aries; da Cruz, Lyndon; Dagnelie, Gislin; Dorn, Jessy D; Duncan, Jacque L; Ho, Allen C; Olmos de Koo, Lisa C; Sahel, José-Alain; Stanga, Paulo E; Thumann, Gabriele; Wang, Vizhong; Greenberg, Robert J

2016-05-01

The purpose of this analysis was to compare observer-rated tasks in patients implanted with the Argus II Retinal Prosthesis System, when the device is ON versus OFF. The Functional Low-Vision Observer Rated Assessment (FLORA) instrument was administered to 26 blind patients implanted with the Argus II Retinal Prosthesis System at a mean follow-up of 36 months. FLORA is a multi-component instrument that consists in part of observer-rated assessment of 35 tasks completed with the device ON versus OFF. The ease with which a patient completes a task is scored using a four-point scale, ranging from easy (score of 1) to impossible (score of 4). The tasks are evaluated individually and organised into four discrete domains, including 'Visual orientation', 'Visual mobility', 'Daily life and 'Interaction with others'. Twenty-six patients completed each of the 35 tasks. Overall, 24 out of 35 tasks (69 per cent) were statistically significantly easier to achieve with the device ON versus OFF. In each of the four domains, patients' performances were significantly better (p < 0.05) with the device ON versus OFF, ranging from 19 to 38 per cent improvement. Patients with an Argus II Retinal Prosthesis implanted for 18 to 44 months (mean 36 months), demonstrated significantly improved completion of vision-related tasks with the device ON versus OFF. © 2016 The Authors Clinical and Experimental Optometry published by John Wiley & Sons Australia, Ltd on behalf of Optometry Australia.

Are children with low vision adapted to the visual environment in classrooms of mainstream schools?

PubMed Central

Negiloni, Kalpa; Ramani, Krishna Kumar; Jeevitha, R; Kalva, Jayashree; Sudhir, Rachapalle Reddi

2018-01-01

Purpose: The study aimed to evaluate the classroom environment of children with low vision and provide recommendations to reduce visual stress, with focus on mainstream schooling. Methods: The medical records of 110 children (5–17 years) seen in low vision clinic during 1 year period (2015) at a tertiary care center in south India were extracted. The visual function levels of children were compared to the details of their classroom environment. The study evaluated and recommended the chalkboard visual task size and viewing distance required for children with mild, moderate, and severe visual impairment (VI). Results: The major causes of low vision based on the site of abnormality and etiology were retinal (80%) and hereditary (67%) conditions, respectively, in children with mild (n = 18), moderate (n = 72), and severe (n = 20) VI. Many of the children (72%) had difficulty in viewing chalkboard and common strategies used for better visibility included copying from friends (47%) and going closer to chalkboard (42%). To view the chalkboard with reduced visual stress, a child with mild VI can be seated at a maximum distance of 4.3 m from the chalkboard, with the minimum size of visual task (height of lowercase letter writing on chalkboard) recommended to be 3 cm. For 3/60–6/60 range, the maximum viewing distance with the visual task size of 4 cm is recommended to be 85 cm to 1.7 m. Conclusion: Simple modifications of the visual task size and seating arrangements can aid children with low vision with better visibility of chalkboard and reduced visual stress to manage in mainstream schools. PMID:29380777

Operational Colour Vision in the Modern Aviation Environment (la Vision des couleurs dans l’environnement aeronautique operationnel d’ aujourd hui)

DTIC Science & Technology

2001-03-01

detection or use by special forces in air-sea rescue operations. It is not the case that colour vision is improved and the use of the devices should be...situation. The tests were developed by clinicians for detecting pathologies. Only rarely do they bear any close relation to the tasks actually...examination procedures will certainly emerge, helped by microcomputing, the use of databases and, why not, Internet? iii la Vision des couleurs dans

Application of Multi-task Lasso Regression in the Stellar Parametrization

NASA Astrophysics Data System (ADS)

Chang, L. N.; Zhang, P. A.

2015-01-01

The multi-task learning approaches have attracted the increasing attention in the fields of machine learning, computer vision, and artificial intelligence. By utilizing the correlations in tasks, learning multiple related tasks simultaneously is better than learning each task independently. An efficient multi-task Lasso (Least Absolute Shrinkage Selection and Operator) regression algorithm is proposed in this paper to estimate the physical parameters of stellar spectra. It not only makes different physical parameters share the common features, but also can effectively preserve their own peculiar features. Experiments were done based on the ELODIE data simulated with the stellar atmospheric simulation model, and on the SDSS data released by the American large survey Sloan. The precision of the model is better than those of the methods in the related literature, especially for the acceleration of gravity (lg g) and the chemical abundance ([Fe/H]). In the experiments, we changed the resolution of the spectrum, and applied the noises with different signal-to-noise ratio (SNR) to the spectrum, so as to illustrate the stability of the model. The results show that the model is influenced by both the resolution and the noise. But the influence of the noise is larger than that of the resolution. In general, the multi-task Lasso regression algorithm is easy to operate, has a strong stability, and also can improve the overall accuracy of the model.

Computer Vision Syndrome: Implications for the Occupational Health Nurse.

PubMed

Lurati, Ann Regina

2018-02-01

Computers and other digital devices are commonly used both in the workplace and during leisure time. Computer vision syndrome (CVS) is a new health-related condition that negatively affects workers. This article reviews the pathology of and interventions for CVS with implications for the occupational health nurse.

MRF energy minimization and beyond via dual decomposition.

PubMed

Komodakis, Nikos; Paragios, Nikos; Tziritas, Georgios

2011-03-01

This paper introduces a new rigorous theoretical framework to address discrete MRF-based optimization in computer vision. Such a framework exploits the powerful technique of Dual Decomposition. It is based on a projected subgradient scheme that attempts to solve an MRF optimization problem by first decomposing it into a set of appropriately chosen subproblems, and then combining their solutions in a principled way. In order to determine the limits of this method, we analyze the conditions that these subproblems have to satisfy and demonstrate the extreme generality and flexibility of such an approach. We thus show that by appropriately choosing what subproblems to use, one can design novel and very powerful MRF optimization algorithms. For instance, in this manner we are able to derive algorithms that: 1) generalize and extend state-of-the-art message-passing methods, 2) optimize very tight LP-relaxations to MRF optimization, and 3) take full advantage of the special structure that may exist in particular MRFs, allowing the use of efficient inference techniques such as, e.g., graph-cut-based methods. Theoretical analysis on the bounds related with the different algorithms derived from our framework and experimental results/comparisons using synthetic and real data for a variety of tasks in computer vision demonstrate the extreme potentials of our approach.

Autonomous Aerial Refueling Ground Test Demonstration—A Sensor-in-the-Loop, Non-Tracking Method

PubMed Central

Chen, Chao-I; Koseluk, Robert; Buchanan, Chase; Duerner, Andrew; Jeppesen, Brian; Laux, Hunter

2015-01-01

An essential capability for an unmanned aerial vehicle (UAV) to extend its airborne duration without increasing the size of the aircraft is called the autonomous aerial refueling (AAR). This paper proposes a sensor-in-the-loop, non-tracking method for probe-and-drogue style autonomous aerial refueling tasks by combining sensitivity adjustments of a 3D Flash LIDAR camera with computer vision based image-processing techniques. The method overcomes the inherit ambiguity issues when reconstructing 3D information from traditional 2D images by taking advantage of ready to use 3D point cloud data from the camera, followed by well-established computer vision techniques. These techniques include curve fitting algorithms and outlier removal with the random sample consensus (RANSAC) algorithm to reliably estimate the drogue center in 3D space, as well as to establish the relative position between the probe and the drogue. To demonstrate the feasibility of the proposed method on a real system, a ground navigation robot was designed and fabricated. Results presented in the paper show that using images acquired from a 3D Flash LIDAR camera as real time visual feedback, the ground robot is able to track a moving simulated drogue and continuously narrow the gap between the robot and the target autonomously. PMID:25970254

Integration of prior knowledge into dense image matching for video surveillance

NASA Astrophysics Data System (ADS)

Menze, M.; Heipke, C.

2014-08-01

Three-dimensional information from dense image matching is a valuable input for a broad range of vision applications. While reliable approaches exist for dedicated stereo setups they do not easily generalize to more challenging camera configurations. In the context of video surveillance the typically large spatial extent of the region of interest and repetitive structures in the scene render the application of dense image matching a challenging task. In this paper we present an approach that derives strong prior knowledge from a planar approximation of the scene. This information is integrated into a graph-cut based image matching framework that treats the assignment of optimal disparity values as a labelling task. Introducing the planar prior heavily reduces ambiguities together with the search space and increases computational efficiency. The results provide a proof of concept of the proposed approach. It allows the reconstruction of dense point clouds in more general surveillance camera setups with wider stereo baselines.

Learning Weight Uncertainty with Stochastic Gradient MCMC for Shape Classification

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

Li, Chunyuan; Stevens, Andrew J.; Chen, Changyou

2016-08-10

Learning the representation of shape cues in 2D & 3D objects for recognition is a fundamental task in computer vision. Deep neural networks (DNNs) have shown promising performance on this task. Due to the large variability of shapes, accurate recognition relies on good estimates of model uncertainty, ignored in traditional training of DNNs, typically learned via stochastic optimization. This paper leverages recent advances in stochastic gradient Markov Chain Monte Carlo (SG-MCMC) to learn weight uncertainty in DNNs. It yields principled Bayesian interpretations for the commonly used Dropout/DropConnect techniques and incorporates them into the SG-MCMC framework. Extensive experiments on 2D &more » 3D shape datasets and various DNN models demonstrate the superiority of the proposed approach over stochastic optimization. Our approach yields higher recognition accuracy when used in conjunction with Dropout and Batch-Normalization.« less

Image annotation by deep neural networks with attention shaping

NASA Astrophysics Data System (ADS)

Zheng, Kexin; Lv, Shaohe; Ma, Fang; Chen, Fei; Jin, Chi; Dou, Yong

2017-07-01

Image annotation is a task of assigning semantic labels to an image. Recently, deep neural networks with visual attention have been utilized successfully in many computer vision tasks. In this paper, we show that conventional attention mechanism is easily misled by the salient class, i.e., the attended region always contains part of the image area describing the content of salient class at different attention iterations. To this end, we propose a novel attention shaping mechanism, which aims to maximize the non-overlapping area between consecutive attention processes by taking into account the history of previous attention vectors. Several weighting polices are studied to utilize the history information in different manners. In two benchmark datasets, i.e., PASCAL VOC2012 and MIRFlickr-25k, the average precision is improved by up to 10% in comparison with the state-of-the-art annotation methods.

A multidisciplinary approach to solving computer related vision problems.

PubMed

Long, Jennifer; Helland, Magne

2012-09-01

This paper proposes a multidisciplinary approach to solving computer related vision issues by including optometry as a part of the problem-solving team. Computer workstation design is increasing in complexity. There are at least ten different professions who contribute to workstation design or who provide advice to improve worker comfort, safety and efficiency. Optometrists have a role identifying and solving computer-related vision issues and in prescribing appropriate optical devices. However, it is possible that advice given by optometrists to improve visual comfort may conflict with other requirements and demands within the workplace. A multidisciplinary approach has been advocated for solving computer related vision issues. There are opportunities for optometrists to collaborate with ergonomists, who coordinate information from physical, cognitive and organisational disciplines to enact holistic solutions to problems. This paper proposes a model of collaboration and examples of successful partnerships at a number of professional levels including individual relationships between optometrists and ergonomists when they have mutual clients/patients, in undergraduate and postgraduate education and in research. There is also scope for dialogue between optometry and ergonomics professional associations. A multidisciplinary approach offers the opportunity to solve vision related computer issues in a cohesive, rather than fragmented way. Further exploration is required to understand the barriers to these professional relationships. © 2012 The College of Optometrists.

3D vision upgrade kit for the TALON robot system

NASA Astrophysics Data System (ADS)

Bodenhamer, Andrew; Pettijohn, Bradley; Pezzaniti, J. Larry; Edmondson, Richard; Vaden, Justin; Hyatt, Brian; Morris, James; Chenault, David; Tchon, Joe; Barnidge, Tracy; Kaufman, Seth; Kingston, David; Newell, Scott

2010-02-01

In September 2009 the Fort Leonard Wood Field Element of the US Army Research Laboratory - Human Research and Engineering Directorate, in conjunction with Polaris Sensor Technologies and Concurrent Technologies Corporation, evaluated the objective performance benefits of Polaris' 3D vision upgrade kit for the TALON small unmanned ground vehicle (SUGV). This upgrade kit is a field-upgradable set of two stereo-cameras and a flat panel display, using only standard hardware, data and electrical connections existing on the TALON robot. Using both the 3D vision system and a standard 2D camera and display, ten active-duty Army Soldiers completed seven scenarios designed to be representative of missions performed by military SUGV operators. Mission time savings (6.5% to 32%) were found for six of the seven scenarios when using the 3D vision system. Operators were not only able to complete tasks quicker but, for six of seven scenarios, made fewer mistakes in their task execution. Subjective Soldier feedback was overwhelmingly in support of pursuing 3D vision systems, such as the one evaluated, for fielding to combat units.

Development of Collaborative Research Initiatives to Advance the Aerospace Sciences-via the Communications, Electronics, Information Systems Focus Group

NASA Technical Reports Server (NTRS)

Knasel, T. Michael

1996-01-01

The primary goal of the Adaptive Vision Laboratory Research project was to develop advanced computer vision systems for automatic target recognition. The approach used in this effort combined several machine learning paradigms including evolutionary learning algorithms, neural networks, and adaptive clustering techniques to develop the E-MOR.PH system. This system is capable of generating pattern recognition systems to solve a wide variety of complex recognition tasks. A series of simulation experiments were conducted using E-MORPH to solve problems in OCR, military target recognition, industrial inspection, and medical image analysis. The bulk of the funds provided through this grant were used to purchase computer hardware and software to support these computationally intensive simulations. The payoff from this effort is the reduced need for human involvement in the design and implementation of recognition systems. We have shown that the techniques used in E-MORPH are generic and readily transition to other problem domains. Specifically, E-MORPH is multi-phase evolutionary leaming system that evolves cooperative sets of features detectors and combines their response using an adaptive classifier to form a complete pattern recognition system. The system can operate on binary or grayscale images. In our most recent experiments, we used multi-resolution images that are formed by applying a Gabor wavelet transform to a set of grayscale input images. To begin the leaming process, candidate chips are extracted from the multi-resolution images to form a training set and a test set. A population of detector sets is randomly initialized to start the evolutionary process. Using a combination of evolutionary programming and genetic algorithms, the feature detectors are enhanced to solve a recognition problem. The design of E-MORPH and recognition results for a complex problem in medical image analysis are described at the end of this report. The specific task involves the identification of vertebrae in x-ray images of human spinal columns. This problem is extremely challenging because the individual vertebra exhibit variation in shape, scale, orientation, and contrast. E-MORPH generated several accurate recognition systems to solve this task. This dual use of this ATR technology clearly demonstrates the flexibility and power of our approach.

Aging and Vision

PubMed Central

Owsley, Cynthia

2010-01-01

Given the increasing size of the older adult population in many countries, there is a pressing need to identify the nature of aging-related vision impairments, their underlying mechanisms, and how they impact older adults’ performance of everyday visual tasks. The results of this research can then be used to develop and evaluate interventions to slow or reverse aging-related declines in vision, thereby improving quality of life. Here we summarize salient developments in research on aging and vision over the past 25 years, focusing on spatial contrast sensitivity, vision under low luminance, temporal sensitivity and motion perception, and visual processing speed. PMID:20974168

Validity of clinical color vision tests for air traffic control specialists.

DOT National Transportation Integrated Search

1992-10-01

An experiment on the relationship between aeromedical color vision screening test performance and performance on color-dependent tasks of Air Traffic Control Specialists was replicated to expand the data base supporting the job-related validity of th...

Development of a table tennis robot for ball interception using visual feedback

NASA Astrophysics Data System (ADS)

Parnichkun, Manukid; Thalagoda, Janitha A.

2016-07-01

This paper presents a concept of intercepting a moving table tennis ball using a robot. The robot has four degrees of freedom(DOF) which are simplified in such a way that The system is able to perform the task within the bounded limit. It employs computer vision to localize the ball. For ball identification, Colour Based Threshold Segmentation(CBTS) and Background Subtraction(BS) methodologies are used. Coordinate Transformation(CT) is employed to transform the data, which is taken based on camera coordinate frame to the general coordinate frame. The sensory system consisted of two HD Web Cameras. The computation time of image processing from web cameras is long .it is not possible to intercept table tennis ball using only image processing. Therefore the projectile motion model is employed to predict the final destination of the ball.

C4ISR Architecture Working Group (AWG), Architecture Framework Version 2.0.

DTIC Science & Technology

1997-12-18

Vision Name Name/identifier of document that contains doctrine, goals, or vision Type Doctrine, goals, or vision Description Text summary description...e.g., organization, directive, order) Description Text summary of tasking •Rules, Criteria, or Conventions Name Name/identifier of document that...contains rules, criteria, or conventions Type One of: rules, criteria, or conventions Description Text summary description of contents or

Color line-scan technology in industrial applications

NASA Astrophysics Data System (ADS)

Lemstrom, Guy F.

1995-10-01

Color machine vision opens new possibilities for industrial on-line quality control applications. With color machine vision it's possible to detect different colors and shades, make color separation, spectroscopic applications and at the same time do measurements in the same way as with gray scale technology. These can be geometrical measurements such as dimensions, shape, texture etc. By combining these technologies in a color line scan camera, it brings the machine vision to new dimensions of realizing new applications and new areas in the machine vision business. Quality and process control requirements in the industry get more demanding every day. Color machine vision can be the solution for many simple tasks that haven't been realized with gray scale technology. The lack of detecting or measuring colors has been one reason why machine vision has not been used in quality control as much as it could have been. Color machine vision has shown a growing enthusiasm in the industrial machine vision applications. Potential areas of the industry include food, wood, mining and minerals, printing, paper, glass, plastic, recycling etc. Tasks are from simple measuring to total process and quality control. The color machine vision is not only for measuring colors. It can also be for contrast enhancement, object detection, background removing, structure detection and measuring. Color or spectral separation can be used in many different ways for working out machine vision application than before. It's only a question of how to use the benefits of having two or more data per measured pixel, instead of having only one as in case with traditional gray scale technology. There are plenty of potential applications already today that can be realized with color vision and it's going to give more performance to many traditional gray scale applications in the near future. But the most important feature is that color machine vision offers a new way of working out applications, where machine vision hasn't been applied before.

Computer vision

NASA Technical Reports Server (NTRS)

Gennery, D.; Cunningham, R.; Saund, E.; High, J.; Ruoff, C.

1981-01-01

The field of computer vision is surveyed and assessed, key research issues are identified, and possibilities for a future vision system are discussed. The problems of descriptions of two and three dimensional worlds are discussed. The representation of such features as texture, edges, curves, and corners are detailed. Recognition methods are described in which cross correlation coefficients are maximized or numerical values for a set of features are measured. Object tracking is discussed in terms of the robust matching algorithms that must be devised. Stereo vision, camera control and calibration, and the hardware and systems architecture are discussed.

Comparative randomised active drug controlled clinical trial of a herbal eye drop in computer vision syndrome.

PubMed

Chatterjee, Pranab Kr; Bairagi, Debasis; Roy, Sudipta; Majumder, Nilay Kr; Paul, Ratish Ch; Bagchi, Sunil Ch

2005-07-01

A comparative double-blind placebo-controlled clinical trial of a herbal eye drop (itone) was conducted to find out its efficacy and safety in 120 patients with computer vision syndrome. Patients using computers for more than 3 hours continuously per day having symptoms of watering, redness, asthenia, irritation, foreign body sensation and signs of conjunctival hyperaemia, corneal filaments and mucus were studied. One hundred and twenty patients were randomly given either placebo, tears substitute (tears plus) or itone in identical vials with specific code number and were instructed to put one drop four times daily for 6 weeks. Subjective and objective assessments were done at bi-weekly intervals. In computer vision syndrome both subjective and objective improvements were noticed with itone drops. Itone drop was found significantly better than placebo (p<0.01) and almost identical results were observed with tears plus (difference was not statistically significant). Itone is considered to be a useful drug in computer vision syndrome.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline.

PubMed

Zhang, Jie; Li, Qingyang; Caselli, Richard J; Thompson, Paul M; Ye, Jieping; Wang, Yalin

2017-06-01

Alzheimer's Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms.

Real Time Target Tracking Using Dedicated Vision Hardware

NASA Astrophysics Data System (ADS)

Kambies, Keith; Walsh, Peter

1988-03-01

This paper describes a real-time vision target tracking system developed by Adaptive Automation, Inc. and delivered to NASA's Launch Equipment Test Facility, Kennedy Space Center, Florida. The target tracking system is part of the Robotic Application Development Laboratory (RADL) which was designed to provide NASA with a general purpose robotic research and development test bed for the integration of robot and sensor systems. One of the first RADL system applications is the closing of a position control loop around a six-axis articulated arm industrial robot using a camera and dedicated vision processor as the input sensor so that the robot can locate and track a moving target. The vision system is inside of the loop closure of the robot tracking system, therefore, tight throughput and latency constraints are imposed on the vision system that can only be met with specialized hardware and a concurrent approach to the processing algorithms. State of the art VME based vision boards capable of processing the image at frame rates were used with a real-time, multi-tasking operating system to achieve the performance required. This paper describes the high speed vision based tracking task, the system throughput requirements, the use of dedicated vision hardware architecture, and the implementation design details. Important to the overall philosophy of the complete system was the hierarchical and modular approach applied to all aspects of the system, hardware and software alike, so there is special emphasis placed on this topic in the paper.

Visual Search in the Real World: Color Vision Deficiency Affects Peripheral Guidance, but Leaves Foveal Verification Largely Unaffected

PubMed Central

Kugler, Günter; 't Hart, Bernard M.; Kohlbecher, Stefan; Bartl, Klaus; Schumann, Frank; Einhäuser, Wolfgang; Schneider, Erich

2015-01-01

Background: People with color vision deficiencies report numerous limitations in daily life, restricting, for example, their access to some professions. However, they use basic color terms systematically and in a similar manner as people with normal color vision. We hypothesize that a possible explanation for this discrepancy between color perception and behavioral consequences might be found in the gaze behavior of people with color vision deficiency. Methods: A group of participants with color vision deficiencies and a control group performed several search tasks in a naturalistic setting on a lawn. All participants wore a mobile eye-tracking-driven camera with a high foveal image resolution (EyeSeeCam). Search performance as well as fixations of objects of different colors were examined. Results: Search performance was similar in both groups in a color-unrelated search task as well as in a search for yellow targets. While searching for red targets, participants with color vision deficiencies exhibited a strongly degraded performance. This was closely matched by the number of fixations on red objects shown by the two groups. Importantly, once they fixated a target, participants with color vision deficiencies exhibited only few identification errors. Conclusions: In contrast to controls, participants with color vision deficiencies are not able to enhance their search for red targets on a (green) lawn by an efficient guiding mechanism. The data indicate that the impaired guiding is the main influence on search performance, while foveal identification (verification) is largely unaffected by the color vision deficiency. PMID:26733851

Integrating Mobile Robotics and Vision with Undergraduate Computer Science

ERIC Educational Resources Information Center

Cielniak, G.; Bellotto, N.; Duckett, T.

2013-01-01

This paper describes the integration of robotics education into an undergraduate Computer Science curriculum. The proposed approach delivers mobile robotics as well as covering the closely related field of Computer Vision and is directly linked to the research conducted at the authors' institution. The paper describes the most relevant details of…

Parallel computer vision

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

Uhr, L.

1987-01-01

This book is written by research scientists involved in the development of massively parallel, but hierarchically structured, algorithms, architectures, and programs for image processing, pattern recognition, and computer vision. The book gives an integrated picture of the programs and algorithms that are being developed, and also of the multi-computer hardware architectures for which these systems are designed.

Rationale, Design and Implementation of a Computer Vision-Based Interactive E-Learning System

ERIC Educational Resources Information Center

Xu, Richard Y. D.; Jin, Jesse S.

2007-01-01

This article presents a schematic application of computer vision technologies to e-learning that is synchronous, peer-to-peer-based, and supports an instructor's interaction with non-computer teaching equipments. The article first discusses the importance of these focused e-learning areas, where the properties include accurate bidirectional…

Perception-based synthetic cueing for night vision device rotorcraft hover operations

NASA Astrophysics Data System (ADS)

Bachelder, Edward N.; McRuer, Duane

2002-08-01

Helicopter flight using night-vision devices (NVDs) is difficult to perform, as evidenced by the high accident rate associated with NVD flight compared to day operation. The approach proposed in this paper is to augment the NVD image with synthetic cueing, whereby the cues would emulate position and motion and appear to be actually occurring in physical space on which they are overlaid. Synthetic cues allow for selective enhancement of perceptual state gains to match the task requirements. A hover cue set was developed based on an analogue of a physical target used in a flight handling qualities tracking task, a perceptual task analysis for hover, and fundamentals of human spatial perception. The display was implemented on a simulation environment, constructed using a virtual reality device, an ultrasound head-tracker, and a fixed-base helicopter simulator. Seven highly trained helicopter pilots were used as experimental subjects and tasked to maintain hover in the presence of aircraft positional disturbances while viewing a synthesized NVD environment and the experimental hover cues. Significant performance improvements were observed when using synthetic cue augmentation. This paper demonstrates that artificial magnification of perceptual states through synthetic cueing can be an effective method of improving night-vision helicopter hover operations.

The dual rod system of amphibians supports colour discrimination at the absolute visual threshold

PubMed Central

Yovanovich, Carola A. M.; Koskela, Sanna M.; Nevala, Noora; Kondrashev, Sergei L.

2017-01-01

The presence of two spectrally different kinds of rod photoreceptors in amphibians has been hypothesized to enable purely rod-based colour vision at very low light levels. The hypothesis has never been properly tested, so we performed three behavioural experiments at different light intensities with toads (Bufo) and frogs (Rana) to determine the thresholds for colour discrimination. The thresholds of toads were different in mate choice and prey-catching tasks, suggesting that the differential sensitivities of different spectral cone types as well as task-specific factors set limits for the use of colour in these behavioural contexts. In neither task was there any indication of rod-based colour discrimination. By contrast, frogs performing phototactic jumping were able to distinguish blue from green light down to the absolute visual threshold, where vision relies only on rod signals. The remarkable sensitivity of this mechanism comparing signals from the two spectrally different rod types approaches theoretical limits set by photon fluctuations and intrinsic noise. Together, the results indicate that different pathways are involved in processing colour cues depending on the ecological relevance of this information for each task. This article is part of the themed issue ‘Vision in dim light’. PMID:28193811

Sensor Control of Robot Arc Welding

NASA Technical Reports Server (NTRS)

Sias, F. R., Jr.

1983-01-01

The potential for using computer vision as sensory feedback for robot gas-tungsten arc welding is investigated. The basic parameters that must be controlled while directing the movement of an arc welding torch are defined. The actions of a human welder are examined to aid in determining the sensory information that would permit a robot to make reproducible high strength welds. Special constraints imposed by both robot hardware and software are considered. Several sensory modalities that would potentially improve weld quality are examined. Special emphasis is directed to the use of computer vision for controlling gas-tungsten arc welding. Vendors of available automated seam tracking arc welding systems and of computer vision systems are surveyed. An assessment is made of the state of the art and the problems that must be solved in order to apply computer vision to robot controlled arc welding on the Space Shuttle Main Engine.

Tracking by Identification Using Computer Vision and Radio

PubMed Central

Mandeljc, Rok; Kovačič, Stanislav; Kristan, Matej; Perš, Janez

2013-01-01

We present a novel system for detection, localization and tracking of multiple people, which fuses a multi-view computer vision approach with a radio-based localization system. The proposed fusion combines the best of both worlds, excellent computer-vision-based localization, and strong identity information provided by the radio system, and is therefore able to perform tracking by identification, which makes it impervious to propagated identity switches. We present comprehensive methodology for evaluation of systems that perform person localization in world coordinate system and use it to evaluate the proposed system as well as its components. Experimental results on a challenging indoor dataset, which involves multiple people walking around a realistically cluttered room, confirm that proposed fusion of both systems significantly outperforms its individual components. Compared to the radio-based system, it achieves better localization results, while at the same time it successfully prevents propagation of identity switches that occur in pure computer-vision-based tracking. PMID:23262485

Color vision predicts processing modes of goal activation during action cascading.

PubMed

Jongkees, Bryant J; Steenbergen, Laura; Colzato, Lorenza S

2017-09-01

One of the most important functions of cognitive control is action cascading: the ability to cope with multiple response options when confronted with various task goals. A recent study implicates a key role for dopamine (DA) in this process, suggesting higher D1 efficiency shifts the action cascading strategy toward a more serial processing mode, whereas higher D2 efficiency promotes a shift in the opposite direction by inducing a more parallel processing mode (Stock, Arning, Epplen, & Beste, 2014). Given that DA is found in high concentration in the retina and modulation of retinal DA release displays characteristics of D2-receptors (Peters, Schweibold, Przuntek, & Müller, 2000), color vision discrimination might serve as an index of D2 efficiency. We used color discrimination, assessed with the Lanthony Desaturated Panel D-15 test, to predict individual differences (N = 85) in a stop-change paradigm that provides a well-established measure of action cascading. In this task it is possible to calculate an individual slope value for each participant that estimates the degree of overlap in task goal activation. When the stopping process of a previous task goal has not finished at the time the change process toward a new task goal is initiated (parallel processing), the slope value becomes steeper. In case of less overlap (more serial processing), the slope value becomes flatter. As expected, participants showing better color vision were more prone to activate goals in a parallel manner as indicated by a steeper slope. Our findings suggest that color vision might represent a predictor of D2 efficiency and the predisposed processing mode of goal activation during action cascading. Copyright © 2017 Elsevier Ltd. All rights reserved.

CIFAR10-DVS: An Event-Stream Dataset for Object Classification

PubMed Central

Li, Hongmin; Liu, Hanchao; Ji, Xiangyang; Li, Guoqi; Shi, Luping

2017-01-01

Neuromorphic vision research requires high-quality and appropriately challenging event-stream datasets to support continuous improvement of algorithms and methods. However, creating event-stream datasets is a time-consuming task, which needs to be recorded using the neuromorphic cameras. Currently, there are limited event-stream datasets available. In this work, by utilizing the popular computer vision dataset CIFAR-10, we converted 10,000 frame-based images into 10,000 event streams using a dynamic vision sensor (DVS), providing an event-stream dataset of intermediate difficulty in 10 different classes, named as “CIFAR10-DVS.” The conversion of event-stream dataset was implemented by a repeated closed-loop smooth (RCLS) movement of frame-based images. Unlike the conversion of frame-based images by moving the camera, the image movement is more realistic in respect of its practical applications. The repeated closed-loop image movement generates rich local intensity changes in continuous time which are quantized by each pixel of the DVS camera to generate events. Furthermore, a performance benchmark in event-driven object classification is provided based on state-of-the-art classification algorithms. This work provides a large event-stream dataset and an initial benchmark for comparison, which may boost algorithm developments in even-driven pattern recognition and object classification. PMID:28611582

Application of parallelized software architecture to an autonomous ground vehicle

NASA Astrophysics Data System (ADS)

Shakya, Rahul; Wright, Adam; Shin, Young Ho; Momin, Orko; Petkovsek, Steven; Wortman, Paul; Gautam, Prasanna; Norton, Adam

2011-01-01

This paper presents improvements made to Q, an autonomous ground vehicle designed to participate in the Intelligent Ground Vehicle Competition (IGVC). For the 2010 IGVC, Q was upgraded with a new parallelized software architecture and a new vision processor. Improvements were made to the power system reducing the number of batteries required for operation from six to one. In previous years, a single state machine was used to execute the bulk of processing activities including sensor interfacing, data processing, path planning, navigation algorithms and motor control. This inefficient approach led to poor software performance and made it difficult to maintain or modify. For IGVC 2010, the team implemented a modular parallel architecture using the National Instruments (NI) LabVIEW programming language. The new architecture divides all the necessary tasks - motor control, navigation, sensor data collection, etc. into well-organized components that execute in parallel, providing considerable flexibility and facilitating efficient use of processing power. Computer vision is used to detect white lines on the ground and determine their location relative to the robot. With the new vision processor and some optimization of the image processing algorithm used last year, two frames can be acquired and processed in 70ms. With all these improvements, Q placed 2nd in the autonomous challenge.

CIFAR10-DVS: An Event-Stream Dataset for Object Classification.

PubMed

Li, Hongmin; Liu, Hanchao; Ji, Xiangyang; Li, Guoqi; Shi, Luping

2017-01-01

Neuromorphic vision research requires high-quality and appropriately challenging event-stream datasets to support continuous improvement of algorithms and methods. However, creating event-stream datasets is a time-consuming task, which needs to be recorded using the neuromorphic cameras. Currently, there are limited event-stream datasets available. In this work, by utilizing the popular computer vision dataset CIFAR-10, we converted 10,000 frame-based images into 10,000 event streams using a dynamic vision sensor (DVS), providing an event-stream dataset of intermediate difficulty in 10 different classes, named as "CIFAR10-DVS." The conversion of event-stream dataset was implemented by a repeated closed-loop smooth (RCLS) movement of frame-based images. Unlike the conversion of frame-based images by moving the camera, the image movement is more realistic in respect of its practical applications. The repeated closed-loop image movement generates rich local intensity changes in continuous time which are quantized by each pixel of the DVS camera to generate events. Furthermore, a performance benchmark in event-driven object classification is provided based on state-of-the-art classification algorithms. This work provides a large event-stream dataset and an initial benchmark for comparison, which may boost algorithm developments in even-driven pattern recognition and object classification.

Toothguide Trainer tests with color vision deficiency simulation monitor.

PubMed

Borbély, Judit; Varsányi, Balázs; Fejérdy, Pál; Hermann, Péter; Jakstat, Holger A

2010-01-01

The aim of this study was to evaluate whether simulated severe red and green color vision deficiency (CVD) influenced color matching results and to investigate whether training with Toothguide Trainer (TT) computer program enabled better color matching results. A total of 31 color normal dental students participated in the study. Every participant had to pass the Ishihara Test. Participants with a red/green color vision deficiency were excluded. A lecture on tooth color matching was given, and individual training with TT was performed. To measure the individual tooth color matching results in normal and color deficient display modes, the TT final exam was displayed on a calibrated monitor that served as a hardware-based method of simulating protanopy and deuteranopy. Data from the TT final exams were collected in normal and in severe red and green CVD-simulating monitor display modes. Color difference values for each participant in each display mode were computed (∑ΔE(ab)(*)), and the respective means and standard deviations were calculated. The Student's t-test was used in statistical evaluation. Participants made larger ΔE(ab)(*) errors in severe color vision deficient display modes than in the normal monitor mode. TT tests showed significant (p<0.05) difference in the tooth color matching results of severe green color vision deficiency simulation mode compared to normal vision mode. Students' shade matching results were significantly better after training (p=0.009). Computer-simulated severe color vision deficiency mode resulted in significantly worse color matching quality compared to normal color vision mode. Toothguide Trainer computer program improved color matching results. Copyright © 2010 Elsevier Ltd. All rights reserved.

Colour vision deficiency and physics teaching

NASA Astrophysics Data System (ADS)

Maule, Louise; Featonby, David

2016-05-01

1 in 12 males suffer from some form of colour vision deficiency (CVD) which in the present colour dominated world of education presentation can be a severe disadvantage. Although aware of ‘colourblindness’ most teachers make little or no adjustment for these pupils for whom tasks may be more difficult. This article examines colour vision deficiency and looks at ways in which we can help the many students who have this problem.

[Meibomian gland disfunction in computer vision syndrome].

PubMed

Pimenidi, M K; Polunin, G S; Safonova, T N

2010-01-01

This article reviews ethiology and pathogenesis of dry eye syndrome due to meibomian gland disfunction (MDG). It is showed that blink rate influences meibomian gland functioning and computer vision syndrome development. Current diagnosis and treatment options of MDG are presented.

Age and visual impairment decrease driving performance as measured on a closed-road circuit.

PubMed

Wood, Joanne M

2002-01-01

In this study the effects of visual impairment and age on driving were investigated and related to visual function. Participants were 139 licensed drivers (young, middle-aged, and older participants with normal vision, and older participants with ocular disease). Driving performance was assessed during the daytime on a closed-road driving circuit. Visual performance was assessed using a vision testing battery. Age and visual impairment had a significant detrimental effect on recognition tasks (detection and recognition of signs and hazards), time to complete driving tasks (overall course time, reversing, and maneuvering), maneuvering ability, divided attention, and an overall driving performance index. All vision measures were significantly affected by group membership. A combination of motion sensitivity, useful field of view (UFOV), Pelli-Robson letter contrast sensitivity, and dynamic acuity could predict 50% of the variance in overall driving scores. These results indicate that older drivers with either normal vision or visual impairment had poorer driving performance compared with younger or middle-aged drivers with normal vision. The inclusion of tests such as motion sensitivity and the UFOV significantly improve the predictive power of vision tests for driving performance. Although such measures may not be practical for widespread screening, their application in selected cases should be considered.

Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images †

PubMed Central

Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao

2017-01-01

Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the “navigation via classification” task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications. PMID:28604624

Convolutional Neural Network-Based Robot Navigation Using Uncalibrated Spherical Images.

PubMed

Ran, Lingyan; Zhang, Yanning; Zhang, Qilin; Yang, Tao

2017-06-12

Vision-based mobile robot navigation is a vibrant area of research with numerous algorithms having been developed, the vast majority of which either belong to the scene-oriented simultaneous localization and mapping (SLAM) or fall into the category of robot-oriented lane-detection/trajectory tracking. These methods suffer from high computational cost and require stringent labelling and calibration efforts. To address these challenges, this paper proposes a lightweight robot navigation framework based purely on uncalibrated spherical images. To simplify the orientation estimation, path prediction and improve computational efficiency, the navigation problem is decomposed into a series of classification tasks. To mitigate the adverse effects of insufficient negative samples in the "navigation via classification" task, we introduce the spherical camera for scene capturing, which enables 360° fisheye panorama as training samples and generation of sufficient positive and negative heading directions. The classification is implemented as an end-to-end Convolutional Neural Network (CNN), trained on our proposed Spherical-Navi image dataset, whose category labels can be efficiently collected. This CNN is capable of predicting potential path directions with high confidence levels based on a single, uncalibrated spherical image. Experimental results demonstrate that the proposed framework outperforms competing ones in realistic applications.

Binary Image Classification: A Genetic Programming Approach to the Problem of Limited Training Instances.

PubMed

Al-Sahaf, Harith; Zhang, Mengjie; Johnston, Mark

2016-01-01

In the computer vision and pattern recognition fields, image classification represents an important yet difficult task. It is a challenge to build effective computer models to replicate the remarkable ability of the human visual system, which relies on only one or a few instances to learn a completely new class or an object of a class. Recently we proposed two genetic programming (GP) methods, one-shot GP and compound-GP, that aim to evolve a program for the task of binary classification in images. The two methods are designed to use only one or a few instances per class to evolve the model. In this study, we investigate these two methods in terms of performance, robustness, and complexity of the evolved programs. We use ten data sets that vary in difficulty to evaluate these two methods. We also compare them with two other GP and six non-GP methods. The results show that one-shot GP and compound-GP outperform or achieve results comparable to competitor methods. Moreover, the features extracted by these two methods improve the performance of other classifiers with handcrafted features and those extracted by a recently developed GP-based method in most cases.

An intelligent robot for helping astronauts

NASA Technical Reports Server (NTRS)

Erickson, J. D.; Grimm, K. A.; Pendleton, T. W.

1994-01-01

This paper describes the development status of a prototype supervised intelligent robot for space application for purposes of (1) helping the crew of a spacecraft such as the Space Station with various tasks, such as holding objects and retrieving/replacing tools and other objects from/into storage, and (2) for purposes of retrieving detached objects, such as equipment or crew, that have become separated from their spacecraft. In addition to this set of tasks in this low-Earth-orbiting spacecraft environment, it is argued that certain aspects of the technology can be viewed as generic in approach, thereby offering insight into intelligent robots for other tasks and environments. Candidate software architectures and their key technical issues which enable real work in real environments to be accomplished safely and robustly are addressed. Results of computer simulations of grasping floating objects are presented. Also described are characterization results on the usable reduced gravity environment in an aircraft flying parabola (to simulate weightlessness) and results on hardware performance there. These results show it is feasible to use that environment for evaluative testing of dexterous grasping based on real-time vision of freely rotating and translating objects.

A sharp image or a sharp knife: norms for the modality-exclusivity of 774 concept-property items.

PubMed

van Dantzig, Saskia; Cowell, Rosemary A; Zeelenberg, René; Pecher, Diane

2011-03-01

According to recent embodied cognition theories, mental concepts are represented by modality-specific sensory-motor systems. Much of the evidence for modality-specificity in conceptual processing comes from the property-verification task. When applying this and other tasks, it is important to select items based on their modality-exclusivity. We collected modality ratings for a set of 387 properties, each of which was paired with two different concepts, yielding a total of 774 concept-property items. For each item, participants rated the degree to which the property could be experienced through five perceptual modalities (vision, audition, touch, smell, and taste). Based on these ratings, we computed a measure of modality exclusivity, the degree to which a property is perceived exclusively through one sensory modality. In this paper, we briefly sketch the theoretical background of conceptual knowledge, discuss the use of the property-verification task in cognitive research, provide our norms and statistics, and validate the norms in a memory experiment. We conclude that our norms are important for researchers studying modality-specific effects in conceptual processing.

Sensing qualitative events to control manipulation

NASA Astrophysics Data System (ADS)

Pook, Polly K.; Ballard, Dana H.

1992-11-01

Dexterous robotic hands have numerous sensors distributed over a flexible high-degree-of- freedom framework. Control of these hands often relies on a detailed task description that is either specified a priori or computed on-line from sensory feedback. Such controllers are complex and may use unnecessary precision. In contrast, one can incorporate plan cues that provide a contextual backdrop in order to simplify the control task. To demonstrate, a Utah/MIT dexterous hand mounted on a Puma 760 arm flips a plastic egg, using the finger tendon tensions as the sole control signal. The completion of each subtask, such as picking up the spatula, finding the pan, and sliding the spatula under the egg, is detected by sensing tension states. The strategy depends on the task context but does not require precise positioning knowledge. We term this qualitative manipulation to draw a parallel with qualitative vision strategies. The approach is to design closed-loop programs that detect significant events to control manipulation but ignore inessential details. The strategy is generalized by analyzing the robot state dynamics during teleoperated hand actions to reveal the essential features that control each action.

Freezing of Gait in Parkinson's Disease: An Overload Problem?

PubMed

Beck, Eric N; Ehgoetz Martens, Kaylena A; Almeida, Quincy J

2015-01-01

Freezing of gait (FOG) is arguably the most severe symptom associated with Parkinson's disease (PD), and often occurs while performing dual tasks or approaching narrowed and cluttered spaces. While it is well known that visual cues alleviate FOG, it is not clear if this effect may be the result of cognitive or sensorimotor mechanisms. Nevertheless, the role of vision may be a critical link that might allow us to disentangle this question. Gaze behaviour has yet to be carefully investigated while freezers approach narrow spaces, thus the overall objective of this study was to explore the interaction between cognitive and sensory-perceptual influences on FOG. In experiment #1, if cognitive load is the underlying factor leading to FOG, then one might expect that a dual-task would elicit FOG episodes even in the presence of visual cues, since the load on attention would interfere with utilization of visual cues. Alternatively, if visual cues alleviate gait despite performance of a dual-task, then it may be more probable that sensory mechanisms are at play. In compliment to this, the aim of experiment#2 was to further challenge the sensory systems, by removing vision of the lower-limbs and thereby forcing participants to rely on other forms of sensory feedback rather than vision while walking toward the narrow space. Spatiotemporal aspects of gait, percentage of gaze fixation frequency and duration, as well as skin conductance levels were measured in freezers and non-freezers across both experiments. Results from experiment#1 indicated that although freezers and non-freezers both walked with worse gait while performing the dual-task, in freezers, gait was relieved by visual cues regardless of whether the cognitive demands of the dual-task were present. At baseline and while dual-tasking, freezers demonstrated a gaze behaviour that neglected the doorway and instead focused primarily on the pathway, a strategy that non-freezers adopted only when performing the dual-task. Interestingly, with the combination of visual cues and dual-task, freezers increased the frequency and duration of fixations toward the doorway, compared to non-freezers. These results suggest that although increasing demand on attention does significantly deteriorate gait in freezers, an increase in cognitive demand is not exclusively responsible for freezing (since visual cues were able to overcome any interference elicited by the dual-task). When vision of the lower limbs was removed in experiment#2, only the freezers' gait was affected. However, when visual cues were present, freezers' gait improved regardless of the dual-task. This gait behaviour was accompanied by greater amount of time spent looking at the visual cues irrespective of the dual-task. Since removing vision of the lower-limbs hindered gait even under low attentional demand, restricted sensory feedback may be an important factor to the mechanisms underlying FOG.

Freezing of Gait in Parkinson’s Disease: An Overload Problem?

PubMed Central

Beck, Eric N.; Ehgoetz Martens, Kaylena A.; Almeida, Quincy J.

2015-01-01

Freezing of gait (FOG) is arguably the most severe symptom associated with Parkinson’s disease (PD), and often occurs while performing dual tasks or approaching narrowed and cluttered spaces. While it is well known that visual cues alleviate FOG, it is not clear if this effect may be the result of cognitive or sensorimotor mechanisms. Nevertheless, the role of vision may be a critical link that might allow us to disentangle this question. Gaze behaviour has yet to be carefully investigated while freezers approach narrow spaces, thus the overall objective of this study was to explore the interaction between cognitive and sensory-perceptual influences on FOG. In experiment #1, if cognitive load is the underlying factor leading to FOG, then one might expect that a dual-task would elicit FOG episodes even in the presence of visual cues, since the load on attention would interfere with utilization of visual cues. Alternatively, if visual cues alleviate gait despite performance of a dual-task, then it may be more probable that sensory mechanisms are at play. In compliment to this, the aim of experiment#2 was to further challenge the sensory systems, by removing vision of the lower-limbs and thereby forcing participants to rely on other forms of sensory feedback rather than vision while walking toward the narrow space. Spatiotemporal aspects of gait, percentage of gaze fixation frequency and duration, as well as skin conductance levels were measured in freezers and non-freezers across both experiments. Results from experiment#1 indicated that although freezers and non-freezers both walked with worse gait while performing the dual-task, in freezers, gait was relieved by visual cues regardless of whether the cognitive demands of the dual-task were present. At baseline and while dual-tasking, freezers demonstrated a gaze behaviour that neglected the doorway and instead focused primarily on the pathway, a strategy that non-freezers adopted only when performing the dual-task. Interestingly, with the combination of visual cues and dual-task, freezers increased the frequency and duration of fixations toward the doorway, compared to non-freezers. These results suggest that although increasing demand on attention does significantly deteriorate gait in freezers, an increase in cognitive demand is not exclusively responsible for freezing (since visual cues were able to overcome any interference elicited by the dual-task). When vision of the lower limbs was removed in experiment#2, only the freezers’ gait was affected. However, when visual cues were present, freezers’ gait improved regardless of the dual-task. This gait behaviour was accompanied by greater amount of time spent looking at the visual cues irrespective of the dual-task. Since removing vision of the lower-limbs hindered gait even under low attentional demand, restricted sensory feedback may be an important factor to the mechanisms underlying FOG. PMID:26678262

Optimizing a mobile robot control system using GPU acceleration

NASA Astrophysics Data System (ADS)

Tuck, Nat; McGuinness, Michael; Martin, Fred

2012-01-01

This paper describes our attempt to optimize a robot control program for the Intelligent Ground Vehicle Competition (IGVC) by running computationally intensive portions of the system on a commodity graphics processing unit (GPU). The IGVC Autonomous Challenge requires a control program that performs a number of different computationally intensive tasks ranging from computer vision to path planning. For the 2011 competition our Robot Operating System (ROS) based control system would not run comfortably on the multicore CPU on our custom robot platform. The process of profiling the ROS control program and selecting appropriate modules for porting to run on a GPU is described. A GPU-targeting compiler, Bacon, is used to speed up development and help optimize the ported modules. The impact of the ported modules on overall performance is discussed. We conclude that GPU optimization can free a significant amount of CPU resources with minimal effort for expensive user-written code, but that replacing heavily-optimized library functions is more difficult, and a much less efficient use of time.

Pilot response to peripheral vision cues during instrument flying tasks.

DOT National Transportation Integrated Search

1968-02-01

In an attempt to more closely associate the visual aspects of instrument flying with that of contact flight, a study was made of human response to peripheral vision cues relating to aircraft roll attitude. Pilots, ranging from 52 to 12,000 flying hou...

Exploration Requirements Development Utilizing the Strategy-to-Task-to-Technology Development Approach

NASA Technical Reports Server (NTRS)

Drake, Bret G.; Josten, B. Kent; Monell, Donald W.

2004-01-01

The Vision for Space Exploration provides direction for the National Aeronautics and Space Administration to embark on a robust space exploration program that will advance the Nation s scientific, security, and economic interests. This plan calls for a progressive expansion of human capabilities beyond low earth orbit seeking to answer profound scientific and philosophical questions while responding to discoveries along the way. In addition, the Vision articulates the strategy for developing the revolutionary new technologies and capabilities required for the future exploration of the solar system. The National Aeronautics and Space Administration faces new challenges in successfully implementing the Vision. In order to implement a sustained and affordable exploration endeavor it is vital for NASA to do business differently. This paper provides an overview of the strategy-to-task-to-technology process being used by NASA s Exploration Systems Mission Directorate to develop the requirements and system acquisition details necessary for implementing a sustainable exploration vision.

The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas.

PubMed

Friedman, Robert J; Gutkowicz-Krusin, Dina; Farber, Michele J; Warycha, Melanie; Schneider-Kels, Lori; Papastathis, Nicole; Mihm, Martin C; Googe, Paul; King, Roy; Prieto, Victor G; Kopf, Alfred W; Polsky, David; Rabinovitz, Harold; Oliviero, Margaret; Cognetta, Armand; Rigel, Darrell S; Marghoob, Ashfaq; Rivers, Jason; Johr, Robert; Grant-Kels, Jane M; Tsao, Hensin

2008-04-01

To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter

Investigation into the use of smartphone as a machine vision device for engineering metrology and flaw detection, with focus on drilling

NASA Astrophysics Data System (ADS)

Razdan, Vikram; Bateman, Richard

2015-05-01

This study investigates the use of a Smartphone and its camera vision capabilities in Engineering metrology and flaw detection, with a view to develop a low cost alternative to Machine vision systems which are out of range for small scale manufacturers. A Smartphone has to provide a similar level of accuracy as Machine Vision devices like Smart cameras. The objective set out was to develop an App on an Android Smartphone, incorporating advanced Computer vision algorithms written in java code. The App could then be used for recording measurements of Twist Drill bits and hole geometry, and analysing the results for accuracy. A detailed literature review was carried out for in-depth study of Machine vision systems and their capabilities, including a comparison between the HTC One X Android Smartphone and the Teledyne Dalsa BOA Smart camera. A review of the existing metrology Apps in the market was also undertaken. In addition, the drilling operation was evaluated to establish key measurement parameters of a twist Drill bit, especially flank wear and diameter. The methodology covers software development of the Android App, including the use of image processing algorithms like Gaussian Blur, Sobel and Canny available from OpenCV software library, as well as designing and developing the experimental set-up for carrying out the measurements. The results obtained from the experimental set-up were analysed for geometry of Twist Drill bits and holes, including diametrical measurements and flaw detection. The results show that Smartphones like the HTC One X have the processing power and the camera capability to carry out metrological tasks, although dimensional accuracy achievable from the Smartphone App is below the level provided by Machine vision devices like Smart cameras. A Smartphone with mechanical attachments, capable of image processing and having a reasonable level of accuracy in dimensional measurement, has the potential to become a handy low-cost Machine vision system for small scale manufacturers, especially in field metrology and flaw detection.

Light Battalion Task Force Reconnaissance and Surveillance: Clear Vision or Groping in the Dark

DTIC Science & Technology

1990-12-23

1 gP.Oi. t@PO n b fl lot this colita n of information s etimated to a.’vae I hout car reions. including " tme for arviewing r r ct ,O matc ng eaiting...SUBTITLE S . FUNDING NUMBERS LIGHT BATTALION TASK FORCE RECONNAISSANCE AND SURVEILLANCE: CLEAR VISION OR GROPING IN TIHE DARK (U) 6. AUTHOR( S ) XAJ...DAVID B. LACQUEMENT 7. PERFORMING ORGANIZATION NAME( S ) AND ADDRESS(ES) B. PERFORMING ORGANIZATION SCHOOL OF ADVANCED MILITARY STUDIES REPORT NUMBER ATTN

Benchmarking Spike-Based Visual Recognition: A Dataset and Evaluation

PubMed Central

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

2016-01-01

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

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

PubMed

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

2016-01-01

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

Taming Crowded Visual Scenes

DTIC Science & Technology

2014-08-12

Nolan Warner, Mubarak Shah. Tracking in Dense Crowds Using Prominenceand Neighborhood Motion Concurrence, IEEE Transactions on Pattern Analysis...of  computer  vision,   computer   graphics  and  evacuation  dynamics  by  providing  a  common  platform,  and  provides...areas  that  includes  Computer  Vision,  Computer   Graphics ,  and  Pedestrian   Evacuation  Dynamics.  Despite  the

Computer vision syndrome: a review of ocular causes and potential treatments.

PubMed

Rosenfield, Mark

2011-09-01

Computer vision syndrome (CVS) is the combination of eye and vision problems associated with the use of computers. In modern western society the use of computers for both vocational and avocational activities is almost universal. However, CVS may have a significant impact not only on visual comfort but also occupational productivity since between 64% and 90% of computer users experience visual symptoms which may include eyestrain, headaches, ocular discomfort, dry eye, diplopia and blurred vision either at near or when looking into the distance after prolonged computer use. This paper reviews the principal ocular causes for this condition, namely oculomotor anomalies and dry eye. Accommodation and vergence responses to electronic screens appear to be similar to those found when viewing printed materials, whereas the prevalence of dry eye symptoms is greater during computer operation. The latter is probably due to a decrease in blink rate and blink amplitude, as well as increased corneal exposure resulting from the monitor frequently being positioned in primary gaze. However, the efficacy of proposed treatments to reduce symptoms of CVS is unproven. A better understanding of the physiology underlying CVS is critical to allow more accurate diagnosis and treatment. This will enable practitioners to optimize visual comfort and efficiency during computer operation. Ophthalmic & Physiological Optics © 2011 The College of Optometrists.

An Enduring Dialogue between Computational and Empirical Vision.

PubMed

Martinez-Conde, Susana; Macknik, Stephen L; Heeger, David J

2018-04-01

In the late 1970s, key discoveries in neurophysiology, psychophysics, computer vision, and image processing had reached a tipping point that would shape visual science for decades to come. David Marr and Ellen Hildreth's 'Theory of edge detection', published in 1980, set out to integrate the newly available wealth of data from behavioral, physiological, and computational approaches in a unifying theory. Although their work had wide and enduring ramifications, their most important contribution may have been to consolidate the foundations of the ongoing dialogue between theoretical and empirical vision science. Copyright © 2018 Elsevier Ltd. All rights reserved.

Maze learning by a hybrid brain-computer system

NASA Astrophysics Data System (ADS)

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system.

PubMed

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-09-13

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

Maze learning by a hybrid brain-computer system

PubMed Central

Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

2016-01-01

The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation. PMID:27619326

Low computation vision-based navigation for a Martian rover

NASA Technical Reports Server (NTRS)

Gavin, Andrew S.; Brooks, Rodney A.

1994-01-01

Construction and design details of the Mobot Vision System, a small, self-contained, mobile vision system, are presented. This system uses the view from the top of a small, roving, robotic vehicle to supply data that is processed in real-time to safely navigate the surface of Mars. A simple, low-computation algorithm for constructing a 3-D navigational map of the Martian environment to be used by the rover is discussed.

Computational models of human vision with applications

NASA Technical Reports Server (NTRS)

Wandell, B. A.

1985-01-01

Perceptual problems in aeronautics were studied. The mechanism by which color constancy is achieved in human vision was examined. A computable algorithm was developed to model the arrangement of retinal cones in spatial vision. The spatial frequency spectra are similar to the spectra of actual cone mosaics. The Hartley transform as a tool of image processing was evaluated and it is suggested that it could be used in signal processing applications, GR image processing.

A robotic vision system to measure tree traits

USDA-ARS?s Scientific Manuscript database

The autonomous measurement of tree traits, such as branching structure, branch diameters, branch lengths, and branch angles, is required for tasks such as robotic pruning of trees as well as structural phenotyping. We propose a robotic vision system called the Robotic System for Tree Shape Estimati...

Robot Acting on Moving Bodies (RAMBO): Interaction with tumbling objects

NASA Technical Reports Server (NTRS)

Davis, Larry S.; Dementhon, Daniel; Bestul, Thor; Ziavras, Sotirios; Srinivasan, H. V.; Siddalingaiah, Madhu; Harwood, David

1989-01-01

Interaction with tumbling objects will become more common as human activities in space expand. Attempting to interact with a large complex object translating and rotating in space, a human operator using only his visual and mental capacities may not be able to estimate the object motion, plan actions or control those actions. A robot system (RAMBO) equipped with a camera, which, given a sequence of simple tasks, can perform these tasks on a tumbling object, is being developed. RAMBO is given a complete geometric model of the object. A low level vision module extracts and groups characteristic features in images of the object. The positions of the object are determined in a sequence of images, and a motion estimate of the object is obtained. This motion estimate is used to plan trajectories of the robot tool to relative locations rearby the object sufficient for achieving the tasks. More specifically, low level vision uses parallel algorithms for image enhancement by symmetric nearest neighbor filtering, edge detection by local gradient operators, and corner extraction by sector filtering. The object pose estimation is a Hough transform method accumulating position hypotheses obtained by matching triples of image features (corners) to triples of model features. To maximize computing speed, the estimate of the position in space of a triple of features is obtained by decomposing its perspective view into a product of rotations and a scaled orthographic projection. This allows use of 2-D lookup tables at each stage of the decomposition. The position hypotheses for each possible match of model feature triples and image feature triples are calculated in parallel. Trajectory planning combines heuristic and dynamic programming techniques. Then trajectories are created using dynamic interpolations between initial and goal trajectories. All the parallel algorithms run on a Connection Machine CM-2 with 16K processors.

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

PubMed

Leinonen, Henri; Tanila, Heikki

2017-07-29

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

Color Vision and the Railways: Part 1. The Railway LED Lantern Test.

PubMed

Dain, Stephen J; Casolin, Armand; Long, Jennifer; Hilmi, Mohd Radzi

2015-02-01

Lantern tests and practical tests are often used in the assessment of prospective railway employees. The lantern tests rarely embody the actual colors used in signaling on the railways. Practical tests have a number of problems, most notably consistency of application and practicability. This work was carried out to provide the Railway LED Lantern Test (RLLT) as a validated method of assessing the color vision of railway workers. The RLLT, a simulated practical test using the same LEDs (light-emitting diodes) as are used in modern railway signals, was developed. It was tested on 46 color vision-normal (CVN) and 37 color vision-deficient (CVD) subjects. A modified prototype was then tested on 106 CVN subjects. All 106 CVN subjects and most mildly affected CVD subjects passed the modified lantern at 3 m. At 6 m, 1 of the 106 normal color vision subjects failed by missing a single red light. All the CVD subjects failed. The RLLT carried out at 3 m allowed mildly affected CVD subjects to pass and demonstrate adequate color vision for the less demanding railway tasks. Carried out at 6 m, it essentially reinforced normal color vision as the standard. The RLLT is a simply administered test that has a direct link to the actual visual task of the rail worker. The RLLT lantern has been adopted as an approved test in the Australian National Standard for Health Assessment of Rail Safety Workers in place of a practical test. It has the potential to be a valid part of any railway color vision standard.

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

Physiological complexity and system adaptability: evidence from postural control dynamics of older adults.

PubMed

Manor, Brad; Costa, Madalena D; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C K; Novak, Vera; Lipsitz, Lewis A

2010-12-01

The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (<20/40 vision, n = 81, 77 ± 4 yr old), somatosensory impairment only (inability to perceive 5.07 monofilament on plantar halluxes, n = 48, 80 ± 5 yr old), and combined impairments (n = 25, 80 ± 4 yr old). Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P < 0.01). Lower complexity during quiet standing correlated with greater absolute (R = -0.34, P = 0.002) and percent (R = -0.45, P < 0.001) increases in postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors.

Physiological complexity and system adaptability: evidence from postural control dynamics of older adults

PubMed Central

Costa, Madalena D.; Hu, Kun; Newton, Elizabeth; Starobinets, Olga; Kang, Hyun Gu; Peng, C. K.; Novak, Vera; Lipsitz, Lewis A.

2010-01-01

The degree of multiscale complexity in human behavioral regulation, such as that required for postural control, appears to decrease with advanced aging or disease. To help delineate causes and functional consequences of complexity loss, we examined the effects of visual and somatosensory impairment on the complexity of postural sway during quiet standing and its relationship to postural adaptation to cognitive dual tasking. Participants of the MOBILIZE Boston Study were classified into mutually exclusive groups: controls [intact vision and foot somatosensation, n = 299, 76 ± 5 (SD) yr old], visual impairment only (<20/40 vision, n = 81, 77 ± 4 yr old), somatosensory impairment only (inability to perceive 5.07 monofilament on plantar halluxes, n = 48, 80 ± 5 yr old), and combined impairments (n = 25, 80 ± 4 yr old). Postural sway (i.e., center-of-pressure) dynamics were assessed during quiet standing and cognitive dual tasking, and a complexity index was quantified using multiscale entropy analysis. Postural sway speed and area, which did not correlate with complexity, were also computed. During quiet standing, the complexity index (mean ± SD) was highest in controls (9.5 ± 1.2) and successively lower in the visual (9.1 ± 1.1), somatosensory (8.6 ± 1.6), and combined (7.8 ± 1.3) impairment groups (P = 0.001). Dual tasking resulted in increased sway speed and area but reduced complexity (P < 0.01). Lower complexity during quiet standing correlated with greater absolute (R = −0.34, P = 0.002) and percent (R = −0.45, P < 0.001) increases in postural sway speed from quiet standing to dual-tasking conditions. Sensory impairments contributed to decreased postural sway complexity, which reflected reduced adaptive capacity of the postural control system. Relatively low baseline complexity may, therefore, indicate control systems that are more vulnerable to cognitive and other stressors. PMID:20947715

Computer vision syndrome-A common cause of unexplained visual symptoms in the modern era.

PubMed

Munshi, Sunil; Varghese, Ashley; Dhar-Munshi, Sushma

2017-07-01

The aim of this study was to assess the evidence and available literature on the clinical, pathogenetic, prognostic and therapeutic aspects of Computer vision syndrome. Information was collected from Medline, Embase & National Library of Medicine over the last 30 years up to March 2016. The bibliographies of relevant articles were searched for additional references. Patients with Computer vision syndrome present to a variety of different specialists, including General Practitioners, Neurologists, Stroke physicians and Ophthalmologists. While the condition is common, there is a poor awareness in the public and among health professionals. Recognising this condition in the clinic or in emergency situations like the TIA clinic is crucial. The implications are potentially huge in view of the extensive and widespread use of computers and visual display units. Greater public awareness of Computer vision syndrome and education of health professionals is vital. Preventive strategies should form part of work place ergonomics routinely. Prompt and correct recognition is important to allow management and avoid unnecessary treatments. © 2017 John Wiley & Sons Ltd.

Comparative randomised controlled clinical trial of a herbal eye drop with artificial tear and placebo in computer vision syndrome.

PubMed

Biswas, N R; Nainiwal, S K; Das, G K; Langan, U; Dadeya, S C; Mongre, P K; Ravi, A K; Baidya, P

2003-03-01

A comparative randomised double masked multicentric clinical trial has been conducted to find out the efficacy and safety of a herbal eye drop preparation, itone eye drops with artificial tear and placebo in 120 patients with computer vision syndrome. Patients using computer for at least 2 hours continuosly per day having symptoms of irritation, foreign body sensation, watering, redness, headache, eyeache and signs of conjunctival congestion, mucous/debris, corneal filaments, corneal staining or lacrimal lake were included in this study. Every patient was instructed to put two drops of either herbal drugs or placebo or artificial tear in the eyes regularly four times for 6 weeks. Objective and subjective findings were recorded at bi-weekly intervals up to six weeks. Side-effects, if any, were also noted. In computer vision syndrome the herbal eye drop preparation was found significantly better than artificial tear (p < 0.01). No side-effects were noted by any of the drugs. Both subjective and objective improvements were observed in itone treated cases. So, itone can be considered as a useful drug in computer vision syndrome.

Colour vision deficiency.

PubMed

Simunovic, M P

2010-05-01

Colour vision deficiency is one of the commonest disorders of vision and can be divided into congenital and acquired forms. Congenital colour vision deficiency affects as many as 8% of males and 0.5% of females--the difference in prevalence reflects the fact that the commonest forms of congenital colour vision deficiency are inherited in an X-linked recessive manner. Until relatively recently, our understanding of the pathophysiological basis of colour vision deficiency largely rested on behavioural data; however, modern molecular genetic techniques have helped to elucidate its mechanisms. The current management of congenital colour vision deficiency lies chiefly in appropriate counselling (including career counselling). Although visual aids may be of benefit to those with colour vision deficiency when performing certain tasks, the evidence suggests that they do not enable wearers to obtain normal colour discrimination. In the future, gene therapy remains a possibility, with animal models demonstrating amelioration following treatment.

A physiologically-based model for simulation of color vision deficiency.

PubMed

Machado, Gustavo M; Oliveira, Manuel M; Fernandes, Leandro A F

2009-01-01

Color vision deficiency (CVD) affects approximately 200 million people worldwide, compromising the ability of these individuals to effectively perform color and visualization-related tasks. This has a significant impact on their private and professional lives. We present a physiologically-based model for simulating color vision. Our model is based on the stage theory of human color vision and is derived from data reported in electrophysiological studies. It is the first model to consistently handle normal color vision, anomalous trichromacy, and dichromacy in a unified way. We have validated the proposed model through an experimental evaluation involving groups of color vision deficient individuals and normal color vision ones. Our model can provide insights and feedback on how to improve visualization experiences for individuals with CVD. It also provides a framework for testing hypotheses about some aspects of the retinal photoreceptors in color vision deficient individuals.

Hand grips strength effect on motor function in human brain using fMRI: a pilot study

NASA Astrophysics Data System (ADS)

Ismail, S. S.; Mohamad, M.; Syazarina, S. O.; Nafisah, W. Y.

2014-11-01

Several methods of motor tasks for fMRI scanning have been evolving from simple to more complex tasks. Motor tasks on upper extremity were applied in order to excite the increscent of motor activation on contralesional and ipsilateral hemispheres in brain. The main objective of this study is to study the different conditions for motor tasks on upper extremity that affected the brain activation. Ten healthy right handed with normal vision (3 male and 7 female, age range=20-30 years, mean=24.6 years, SD=2.21) participated in this study. Prior to the scanning, participants were trained on hand grip tasks using rubber ball and pressure gauge tool outside the scanner. During fMRI session, a block design with 30-s task blocks and alternating 30-s rest periods was employed while participants viewed a computer screen via a back projection-mirror system and instructed to follow the instruction by gripping their hand with normal and strong grips using a rubber ball. Statistical Parametric mapping (SPM8) software was used to determine the brain activation. Both tasks activated the primary motor (M1), supplementary motor area (SMA), dorsal and ventral of premotor cortex area (PMA) in left hemisphere while in right hemisphere the area of primary motor (M1) somatosensory was activated. However, the comparison between both tasks revealed that the strong hand grip showed the higher activation at M1, PMA and SMA on left hemisphere and also the area of SMA on right hemisphere. Both conditions of motor tasks could provide insights the functional organization on human brain.

Image understanding systems based on the unifying representation of perceptual and conceptual information and the solution of mid-level and high-level vision problems

NASA Astrophysics Data System (ADS)

Kuvychko, Igor

2001-10-01

Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolving ambiguity and uncertainty via feedback, and provide image understanding, that is an interpretation of visual information in terms of such knowledge models. A computer vision system based on such principles requires unifying representation of perceptual and conceptual information. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/networks models is found. That means a very important shift of paradigm in our knowledge about brain from neural networks to the cortical software. Starting from the primary visual areas, brain analyzes an image as a graph-type spatial structure. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. The spatial combination of different neighbor features cannot be described as a statistical/integral characteristic of the analyzed region, but uniquely characterizes such region itself. Spatial logic and topology naturally present in such structures. Mid-level vision processes like clustering, perceptual grouping, multilevel hierarchical compression, separation of figure from ground, etc. are special kinds of graph/network transformations. They convert low-level image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena like shape from shading, occlusion, etc. are results of such analysis. Such approach gives opportunity not only to explain frequently unexplainable results of the cognitive science, but also to create intelligent computer vision systems that simulate perceptional processes in both what and where visual pathways. Such systems can open new horizons for robotic and computer vision industries.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

Design and implementation of practical bidirectional texture function measurement devices focusing on the developments at the University of Bonn.

PubMed

Schwartz, Christopher; Sarlette, Ralf; Weinmann, Michael; Rump, Martin; Klein, Reinhard

2014-04-28

Understanding as well as realistic reproduction of the appearance of materials play an important role in computer graphics, computer vision and industry. They enable applications such as digital material design, virtual prototyping and faithful virtual surrogates for entertainment, marketing, education or cultural heritage documentation. A particularly fruitful way to obtain the digital appearance is the acquisition of reflectance from real-world material samples. Therefore, a great variety of devices to perform this task has been proposed. In this work, we investigate their practical usefulness. We first identify a set of necessary attributes and establish a general categorization of different designs that have been realized. Subsequently, we provide an in-depth discussion of three particular implementations by our work group, demonstrating advantages and disadvantages of different system designs with respect to the previously established attributes. Finally, we survey the existing literature to compare our implementation with related approaches.

Application of Multi-task Lasso Regression in the Parametrization of Stellar Spectra

NASA Astrophysics Data System (ADS)

Chang, Li-Na; Zhang, Pei-Ai

2015-07-01

The multi-task learning approaches have attracted the increasing attention in the fields of machine learning, computer vision, and artificial intelligence. By utilizing the correlations in tasks, learning multiple related tasks simultaneously is better than learning each task independently. An efficient multi-task Lasso (Least Absolute Shrinkage Selection and Operator) regression algorithm is proposed in this paper to estimate the physical parameters of stellar spectra. It not only can obtain the information about the common features of the different physical parameters, but also can preserve effectively their own peculiar features. Experiments were done based on the ELODIE synthetic spectral data simulated with the stellar atmospheric model, and on the SDSS data released by the American large-scale survey Sloan. The estimation precision of our model is better than those of the methods in the related literature, especially for the estimates of the gravitational acceleration (lg g) and the chemical abundance ([Fe/H]). In the experiments we changed the spectral resolution, and applied the noises with different signal-to-noise ratios (SNRs) to the spectral data, so as to illustrate the stability of the model. The results show that the model is influenced by both the resolution and the noise. But the influence of the noise is larger than that of the resolution. In general, the multi-task Lasso regression algorithm is easy to operate, it has a strong stability, and can also improve the overall prediction accuracy of the model.

Experiencing the Impact of Organizational Structure on Planning and Visioning Tasks

ERIC Educational Resources Information Center

Pennisi, Lisa

2012-01-01

The various ways natural resource agencies and programs are structured and how that impacts leadership style and products is an important concept for students to understand. Leadership style and organizational structure determine visions, missions, goals and objectives that set the tone for organizations. This exercise demonstrates organizational…

Low-Latency Embedded Vision Processor (LLEVS)

DTIC Science & Technology

2016-03-01

26 3.2.3 Task 3 Projected Performance Analysis of FPGA- based Vision Processor ........... 31 3.2.3.1 Algorithms Latency Analysis ...Programmable Gate Array Custom Hardware for Real- Time Multiresolution Analysis . ............................................... 35...conduct data analysis for performance projections. The data acquired through measurements , simulation and estimation provide the requisite platform for

Performance of color-dependent tasks of air traffic control specialists as a function of type and degree of color vision deficiency.

DOT National Transportation Integrated Search

1992-08-01

This experiment was conducted to expand initial efforts to validate the requirement for normal color vision in Air Traffic Control Specialist (ATCS) personnel who work at en route center, terminal, and flight service station facilities. An enlarged d...

77 FR 539 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2012-01-05

..., please include a self-addressed, stamped envelope or postcard or print the acknowledgment page that..., Rene Amaya has sufficient vision to perform the driving tasks required to operate a commercial vehicle.'' Mr. Amaya reported that he has driven straight trucks for 2 years, accumulating 78,000 miles and...

The Impact of Early Visual Deprivation on Spatial Hearing: A Comparison between Totally and Partially Visually Deprived Children

PubMed Central

Cappagli, Giulia; Finocchietti, Sara; Cocchi, Elena; Gori, Monica

2017-01-01

The specific role of early visual deprivation on spatial hearing is still unclear, mainly due to the difficulty of comparing similar spatial skills at different ages and to the difficulty in recruiting young blind children from birth. In this study, the effects of early visual deprivation on the development of auditory spatial localization have been assessed in a group of seven 3–5 years old children with congenital blindness (n = 2; light perception or no perception of light) or low vision (n = 5; visual acuity range 1.1–1.7 LogMAR), with the main aim to understand if visual experience is fundamental to the development of specific spatial skills. Our study led to three main findings: firstly, totally blind children performed overall more poorly compared sighted and low vision children in all the spatial tasks performed; secondly, low vision children performed equally or better than sighted children in the same auditory spatial tasks; thirdly, higher residual levels of visual acuity are positively correlated with better spatial performance in the dynamic condition of the auditory localization task indicating that the more residual vision the better spatial performance. These results suggest that early visual experience has an important role in the development of spatial cognition, even when the visual input during the critical period of visual calibration is partially degraded like in the case of low vision children. Overall these results shed light on the importance of early assessment of spatial impairments in visually impaired children and early intervention to prevent the risk of isolation and social exclusion. PMID:28443040

Color Vision and Performance on Color-Coded Cockpit Displays.

PubMed

Gaska, James P; Wright, Steven T; Winterbottom, Marc D; Hadley, Steven C

Although there are numerous studies that demonstrate that color vision deficient (CVD) individuals perform less well than color vision normal (CVN) individuals in tasks that require discrimination or identification of colored stimuli, there remains a need to quantify the relationship between the type and severity of CVD and performance on operationally relevant tasks. Participants were classified as CVN (N = 45) or CVD (N = 49) using the Rabin cone contrast test, which is the standard color vision screening test used by the United States Air Force. In the color condition, test images that were representative of the size, shape, and color of symbols and lines used on fifth-generation fighter aircraft displays were used to measure operational performance. In the achromatic condition, all symbols and lines had the same chromaticity but differed in luminance. Subjects were asked to locate and discriminate between friend vs. foe symbols (red vs. green, or brighter vs. dimmer) while speed and accuracy were recorded. Increasing color deficiency was associated with decreasing speed and accuracy for the color condition (R 2 > 0.2), but not for the achromatic condition. Mean differences between CVN and CVD individuals showed the same pattern. Although lower CCT scores are clearly associated with lower performance in color related tasks, the magnitude of the performance loss was relatively small and there were multiple examples of high-performing CVD individuals who had higher operational scores than low-performing CVN individuals. Gaska JP, Wright ST, Winterbottom MD, Hadley SC. Color vision and performance on color-coded cockpit displays. Aerosp Med Hum Perform. 2016; 87(11):921-927.

Milestones on the road to independence for the blind

NASA Astrophysics Data System (ADS)

Reed, Kenneth

1997-02-01

Ken will talk about his experiences as an end user of technology. Even moderate technological progress in the field of pattern recognition and artificial intelligence can be, often surprisingly, of great help to the blind. An example is the providing of portable bar code scanners so that a blind person knows what he is buying and what color it is. In this age of microprocessors controlling everything, how can a blind person find out what his VCR is doing? Is there some technique that will allow a blind musician to convert print music into midi files to drive a synthesizer? Can computer vision help the blind cross a road including predictions of where oncoming traffic will be located? Can computer vision technology provide spoken description of scenes so a blind person can figure out where doors and entrances are located, and what the signage on the building says? He asks 'can computer vision help me flip a pancake?' His challenge to those in the computer vision field is 'where can we go from here?'

A large-scale solar dynamics observatory image dataset for computer vision applications.

PubMed

Kucuk, Ahmet; Banda, Juan M; Angryk, Rafal A

2017-01-01

The National Aeronautics Space Agency (NASA) Solar Dynamics Observatory (SDO) mission has given us unprecedented insight into the Sun's activity. By capturing approximately 70,000 images a day, this mission has created one of the richest and biggest repositories of solar image data available to mankind. With such massive amounts of information, researchers have been able to produce great advances in detecting solar events. In this resource, we compile SDO solar data into a single repository in order to provide the computer vision community with a standardized and curated large-scale dataset of several hundred thousand solar events found on high resolution solar images. This publicly available resource, along with the generation source code, will accelerate computer vision research on NASA's solar image data by reducing the amount of time spent performing data acquisition and curation from the multiple sources we have compiled. By improving the quality of the data with thorough curation, we anticipate a wider adoption and interest from the computer vision to the solar physics community.

Scene and human face recognition in the central vision of patients with glaucoma

PubMed Central

Aptel, Florent; Attye, Arnaud; Guyader, Nathalie; Boucart, Muriel; Chiquet, Christophe; Peyrin, Carole

2018-01-01

Primary open-angle glaucoma (POAG) firstly mainly affects peripheral vision. Current behavioral studies support the idea that visual defects of patients with POAG extend into parts of the central visual field classified as normal by static automated perimetry analysis. This is particularly true for visual tasks involving processes of a higher level than mere detection. The purpose of this study was to assess visual abilities of POAG patients in central vision. Patients were assigned to two groups following a visual field examination (Humphrey 24–2 SITA-Standard test). Patients with both peripheral and central defects and patients with peripheral but no central defect, as well as age-matched controls, participated in the experiment. All participants had to perform two visual tasks where low-contrast stimuli were presented in the central 6° of the visual field. A categorization task of scene images and human face images assessed high-level visual recognition abilities. In contrast, a detection task using the same stimuli assessed low-level visual function. The difference in performance between detection and categorization revealed the cost of high-level visual processing. Compared to controls, patients with a central visual defect showed a deficit in both detection and categorization of all low-contrast images. This is consistent with the abnormal retinal sensitivity as assessed by perimetry. However, the deficit was greater for categorization than detection. Patients without a central defect showed similar performances to the controls concerning the detection and categorization of faces. However, while the detection of scene images was well-maintained, these patients showed a deficit in their categorization. This suggests that the simple loss of peripheral vision could be detrimental to scene recognition, even when the information is displayed in central vision. This study revealed subtle defects in the central visual field of POAG patients that cannot be predicted by static automated perimetry assessment using Humphrey 24–2 SITA-Standard test. PMID:29481572

The effects of moon illumination, moon angle, cloud cover, and sky glow on night vision goggle flight performance

NASA Astrophysics Data System (ADS)

Loro, Stephen Lee

This study was designed to examine moon illumination, moon angle, cloud cover, sky glow, and Night Vision Goggle (NVG) flight performance to determine possible effects. The research was a causal-comparative design. The sample consisted of 194 Fort Rucker Initial Entry Rotary Wing NVG flight students being observed by 69 NVG Instructor Pilots. The students participated in NVG flight training from September 1992 through January 1993. Data were collected using a questionnaire. Observations were analyzed using a Kruskal-Wallis one-way analysis of variance and a Wilcox matched pairs signed-ranks test for difference. Correlations were analyzed using Pearson's r. The analyses results indicated that performance at high moon illumination levels is superior to zero moon illumination, and in most task maneuvers, superior to >0%--50% moon illumination. No differences were found in performance at moon illumination levels above 50%. Moon angle had no effect on night vision goggle flight performance. Cloud cover and sky glow have selective effects on different maneuvers. For most task maneuvers, cloud cover does not affect performance. Overcast cloud cover had a significant effect on seven of the 14 task maneuvers. Sky glow did not affect eight out of 14 task maneuvers at any level of sky glow.

A New Font, Specifically Designed for Peripheral Vision, Improves Peripheral Letter and Word Recognition, but Not Eye-Mediated Reading Performance

PubMed Central

Bernard, Jean-Baptiste; Aguilar, Carlos; Castet, Eric

2016-01-01

Reading speed is dramatically reduced when readers cannot use their central vision. This is because low visual acuity and crowding negatively impact letter recognition in the periphery. In this study, we designed a new font (referred to as the Eido font) in order to reduce inter-letter similarity and consequently to increase peripheral letter recognition performance. We tested this font by running five experiments that compared the Eido font with the standard Courier font. Letter spacing and x-height were identical for the two monospaced fonts. Six normally-sighted subjects used exclusively their peripheral vision to run two aloud reading tasks (with eye movements), a letter recognition task (without eye movements), a word recognition task (without eye movements) and a lexical decision task. Results show that reading speed was not significantly different between the Eido and the Courier font when subjects had to read single sentences with a round simulated gaze-contingent central scotoma (10° diameter). In contrast, Eido significantly decreased perceptual errors in peripheral crowded letter recognition (-30% errors on average for letters briefly presented at 6° eccentricity) and in peripheral word recognition (-32% errors on average for words briefly presented at 6° eccentricity). PMID:27074013

A New Font, Specifically Designed for Peripheral Vision, Improves Peripheral Letter and Word Recognition, but Not Eye-Mediated Reading Performance.

PubMed

Bernard, Jean-Baptiste; Aguilar, Carlos; Castet, Eric

2016-01-01

Reading speed is dramatically reduced when readers cannot use their central vision. This is because low visual acuity and crowding negatively impact letter recognition in the periphery. In this study, we designed a new font (referred to as the Eido font) in order to reduce inter-letter similarity and consequently to increase peripheral letter recognition performance. We tested this font by running five experiments that compared the Eido font with the standard Courier font. Letter spacing and x-height were identical for the two monospaced fonts. Six normally-sighted subjects used exclusively their peripheral vision to run two aloud reading tasks (with eye movements), a letter recognition task (without eye movements), a word recognition task (without eye movements) and a lexical decision task. Results show that reading speed was not significantly different between the Eido and the Courier font when subjects had to read single sentences with a round simulated gaze-contingent central scotoma (10° diameter). In contrast, Eido significantly decreased perceptual errors in peripheral crowded letter recognition (-30% errors on average for letters briefly presented at 6° eccentricity) and in peripheral word recognition (-32% errors on average for words briefly presented at 6° eccentricity).

Is Mc Leod's Patent Pending Naturoptic Method for Restoring Healthy Vision Easy and Verifiable?

NASA Astrophysics Data System (ADS)

Niemi, Paul; McLeod, David; McLeod, Roger

2006-10-01

RDM asserts that he and people he has trained can assign visual tasks from standard vision assessment charts, or better replacements, proceeding through incremental changes and such rapid improvements that healthy vision can be restored. Mc Leod predicts that in visual tasks with pupil diameter changes, wavelengths change proportionally. A longer, quasimonochromatic wavelength interval is coincident with foveal cones, and rods. A shorter, partially overlapping interval separately aligns with extrafoveal cones. Wavelengths follow the Airy disk radius formula. Niemi can evaluate if it is true that visual health merely requires triggering and facilitating the demands of possibly overridden feedback signals. The method and process are designed so that potential Naturopathic and other select graduate students should be able to self-fund their higher- level educations from preferential franchising arrangements of earnings while they are in certain programs.

[Computer eyeglasses--aspects of a confusing topic].

PubMed

Huber-Spitzy, V; Janeba, E

1997-01-01

With the coming into force of the new Austrian Employee Protection Act the issue of the so called "computer glasses" will also gain added importance in our country. Such glasses have been defined as vision aids to be exclusively used for the work on computer monitors and include single-vision glasses solely intended for reading computer screen, glasses with bifocal lenses for reading computer screen and hard-copy documents as well as those with varifocal lenses featuring a thickened central section. There is still a considerable controversy among those concerned as to who will bear the costs for such glasses--most likely it will be the employer. Prescription of such vision aids will be exclusively restricted to ophthalmologists, based on a thorough ophthalmological examination under adequate consideration of the specific working environment and the workplace requirements of the individual employee concerned.

Computer Vision for High-Throughput Quantitative Phenotyping: A Case Study of Grapevine Downy Mildew Sporulation and Leaf Trichomes.

PubMed

Divilov, Konstantin; Wiesner-Hanks, Tyr; Barba, Paola; Cadle-Davidson, Lance; Reisch, Bruce I

2017-12-01

Quantitative phenotyping of downy mildew sporulation is frequently used in plant breeding and genetic studies, as well as in studies focused on pathogen biology such as chemical efficacy trials. In these scenarios, phenotyping a large number of genotypes or treatments can be advantageous but is often limited by time and cost. We present a novel computational pipeline dedicated to estimating the percent area of downy mildew sporulation from images of inoculated grapevine leaf discs in a manner that is time and cost efficient. The pipeline was tested on images from leaf disc assay experiments involving two F 1 grapevine families, one that had glabrous leaves (Vitis rupestris B38 × 'Horizon' [RH]) and another that had leaf trichomes (Horizon × V. cinerea B9 [HC]). Correlations between computer vision and manual visual ratings reached 0.89 in the RH family and 0.43 in the HC family. Additionally, we were able to use the computer vision system prior to sporulation to measure the percent leaf trichome area. We estimate that an experienced rater scoring sporulation would spend at least 90% less time using the computer vision system compared with the manual visual method. This will allow more treatments to be phenotyped in order to better understand the genetic architecture of downy mildew resistance and of leaf trichome density. We anticipate that this computer vision system will find applications in other pathosystems or traits where responses can be imaged with sufficient contrast from the background.

Model-based vision for space applications

NASA Technical Reports Server (NTRS)

Chaconas, Karen; Nashman, Marilyn; Lumia, Ronald

1992-01-01

This paper describes a method for tracking moving image features by combining spatial and temporal edge information with model based feature information. The algorithm updates the two-dimensional position of object features by correlating predicted model features with current image data. The results of the correlation process are used to compute an updated model. The algorithm makes use of a high temporal sampling rate with respect to spatial changes of the image features and operates in a real-time multiprocessing environment. Preliminary results demonstrate successful tracking for image feature velocities between 1.1 and 4.5 pixels every image frame. This work has applications for docking, assembly, retrieval of floating objects and a host of other space-related tasks.

Detection and Tracking of Moving Objects with Real-Time Onboard Vision System

NASA Astrophysics Data System (ADS)

Erokhin, D. Y.; Feldman, A. B.; Korepanov, S. E.

2017-05-01

Detection of moving objects in video sequence received from moving video sensor is a one of the most important problem in computer vision. The main purpose of this work is developing set of algorithms, which can detect and track moving objects in real time computer vision system. This set includes three main parts: the algorithm for estimation and compensation of geometric transformations of images, an algorithm for detection of moving objects, an algorithm to tracking of the detected objects and prediction their position. The results can be claimed to create onboard vision systems of aircraft, including those relating to small and unmanned aircraft.

Does It Really Matter Where You Look When Walking on Stairs? Insights from a Dual-Task Study

PubMed Central

Miyasike-daSilva, Veronica; McIlroy, William E.

2012-01-01

Although the visual system is known to provide relevant information to guide stair locomotion, there is less understanding of the specific contributions of foveal and peripheral visual field information. The present study investigated the specific role of foveal vision during stair locomotion and ground-stairs transitions by using a dual-task paradigm to influence the ability to rely on foveal vision. Fifteen healthy adults (26.9±3.3 years; 8 females) ascended a 7-step staircase under four conditions: no secondary tasks (CONTROL); gaze fixation on a fixed target located at the end of the pathway (TARGET); visual reaction time task (VRT); and auditory reaction time task (ART). Gaze fixations towards stair features were significantly reduced in TARGET and VRT compared to CONTROL and ART. Despite the reduced fixations, participants were able to successfully ascend stairs and rarely used the handrail. Step time was increased during VRT compared to CONTROL in most stair steps. Navigating on the transition steps did not require more gaze fixations than the middle steps. However, reaction time tended to increase during locomotion on transitions suggesting additional executive demands during this phase. These findings suggest that foveal vision may not be an essential source of visual information regarding stair features to guide stair walking, despite the unique control challenges at transition phases as highlighted by phase-specific challenges in dual-tasking. Instead, the tendency to look at the steps in usual conditions likely provides a stable reference frame for extraction of visual information regarding step features from the entire visual field. PMID:22970297

Computer graphics testbed to simulate and test vision systems for space applications

NASA Technical Reports Server (NTRS)

Cheatham, John B.

1991-01-01

Research activity has shifted from computer graphics and vision systems to the broader scope of applying concepts of artificial intelligence to robotics. Specifically, the research is directed toward developing Artificial Neural Networks, Expert Systems, and Laser Imaging Techniques for Autonomous Space Robots.

Construction, implementation and testing of an image identification system using computer vision methods for fruit flies with economic importance (Diptera: Tephritidae).

PubMed

Wang, Jiang-Ning; Chen, Xiao-Lin; Hou, Xin-Wen; Zhou, Li-Bing; Zhu, Chao-Dong; Ji, Li-Qiang

2017-07-01

Many species of Tephritidae are damaging to fruit, which might negatively impact international fruit trade. Automatic or semi-automatic identification of fruit flies are greatly needed for diagnosing causes of damage and quarantine protocols for economically relevant insects. A fruit fly image identification system named AFIS1.0 has been developed using 74 species belonging to six genera, which include the majority of pests in the Tephritidae. The system combines automated image identification and manual verification, balancing operability and accuracy. AFIS1.0 integrates image analysis and expert system into a content-based image retrieval framework. In the the automatic identification module, AFIS1.0 gives candidate identification results. Afterwards users can do manual selection based on comparing unidentified images with a subset of images corresponding to the automatic identification result. The system uses Gabor surface features in automated identification and yielded an overall classification success rate of 87% to the species level by Independent Multi-part Image Automatic Identification Test. The system is useful for users with or without specific expertise on Tephritidae in the task of rapid and effective identification of fruit flies. It makes the application of computer vision technology to fruit fly recognition much closer to production level. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Blind subjects implanted with the Argus II retinal prosthesis are able to improve performance in a spatial-motor task

PubMed Central

Ahuja, A K; Dorn, J D; Caspi, A; McMahon, M J; Dagnelie, G; daCruz, L; Stanga, P; Humayun, M S; Greenberg, R J

2012-01-01

Background/aims To determine to what extent subjects implanted with the Argus II retinal prosthesis can improve performance compared with residual native vision in a spatial-motor task. Methods High-contrast square stimuli (5.85 cm sides) were displayed in random locations on a 19″ (48.3 cm) touch screen monitor located 12″ (30.5 cm) in front of the subject. Subjects were instructed to locate and touch the square centre with the system on and then off (40 trials each). The coordinates of the square centre and location touched were recorded. Results Ninety-six percent (26/27) of subjects showed a significant improvement in accuracy and 93% (25/27) show a significant improvement in repeatability with the system on compared with off (p<0.05, Student t test). A group of five subjects that had both accuracy and repeatability values <250 pixels (7.4 cm) with the system off (ie, using only their residual vision) was significantly more accurate and repeatable than the remainder of the cohort (p<0.01). Of this group, four subjects showed a significant improvement in both accuracy and repeatability with the system on. Conclusion In a study on the largest cohort of visual prosthesis recipients to date, we found that artificial vision augments information from existing vision in a spatial-motor task. Clinical trials registry no NCT00407602. PMID:20881025

Computer Vision Photogrammetry for Underwater Archaeological Site Recording in a Low-Visibility Environment

NASA Astrophysics Data System (ADS)

Van Damme, T.

2015-04-01

Computer Vision Photogrammetry allows archaeologists to accurately record underwater sites in three dimensions using simple twodimensional picture or video sequences, automatically processed in dedicated software. In this article, I share my experience in working with one such software package, namely PhotoScan, to record a Dutch shipwreck site. In order to demonstrate the method's reliability and flexibility, the site in question is reconstructed from simple GoPro footage, captured in low-visibility conditions. Based on the results of this case study, Computer Vision Photogrammetry compares very favourably to manual recording methods both in recording efficiency, and in the quality of the final results. In a final section, the significance of Computer Vision Photogrammetry is then assessed from a historical perspective, by placing the current research in the wider context of about half a century of successful use of Analytical and later Digital photogrammetry in the field of underwater archaeology. I conclude that while photogrammetry has been used in our discipline for several decades now, for various reasons the method was only ever used by a relatively small percentage of projects. This is likely to change in the near future since, compared to the `traditional' photogrammetry approaches employed in the past, today Computer Vision Photogrammetry is easier to use, more reliable and more affordable than ever before, while at the same time producing more accurate and more detailed three-dimensional results.

Vision-based semi-autonomous outdoor robot system to reduce soldier workload

NASA Astrophysics Data System (ADS)

Richardson, Al; Rodgers, Michael H.

2001-09-01

Sensors and computational capability have not reached the point to enable small robots to navigate autonomously in unconstrained outdoor environments at tactically useful speeds. This problem is greatly reduced, however, if a soldier can lead the robot through terrain that he knows it can traverse. An application of this concept is a small pack-mule robot that follows a foot soldier over outdoor terrain. The solder would be responsible to avoid situations beyond the robot's limitations when encountered. Having learned the route, the robot could autonomously retrace the path carrying supplies and munitions. This would greatly reduce the soldier's workload under normal conditions. This paper presents a description of a developmental robot sensor system using low-cost commercial 3D vision and inertial sensors to address this application. The robot moves at fast walking speed and requires only short-range perception to accomplish its task. 3D-feature information is recorded on a composite route map that the robot uses to negotiate its local environment and retrace the path taught by the soldier leader.

Underwater Inherent Optical Properties Estimation Using a Depth Aided Deep Neural Network.

PubMed

Yu, Zhibin; Wang, Yubo; Zheng, Bing; Zheng, Haiyong; Wang, Nan; Gu, Zhaorui

2017-01-01

Underwater inherent optical properties (IOPs) are the fundamental clues to many research fields such as marine optics, marine biology, and underwater vision. Currently, beam transmissometers and optical sensors are considered as the ideal IOPs measuring methods. But these methods are inflexible and expensive to be deployed. To overcome this problem, we aim to develop a novel measuring method using only a single underwater image with the help of deep artificial neural network. The power of artificial neural network has been proved in image processing and computer vision fields with deep learning technology. However, image-based IOPs estimation is a quite different and challenging task. Unlike the traditional applications such as image classification or localization, IOP estimation looks at the transparency of the water between the camera and the target objects to estimate multiple optical properties simultaneously. In this paper, we propose a novel Depth Aided (DA) deep neural network structure for IOPs estimation based on a single RGB image that is even noisy. The imaging depth information is considered as an aided input to help our model make better decision.

Approximate labeling via graph cuts based on linear programming.

PubMed

Komodakis, Nikos; Tziritas, Georgios

2007-08-01

A new framework is presented for both understanding and developing graph-cut-based combinatorial algorithms suitable for the approximate optimization of a very wide class of Markov Random Fields (MRFs) that are frequently encountered in computer vision. The proposed framework utilizes tools from the duality theory of linear programming in order to provide an alternative and more general view of state-of-the-art techniques like the \\alpha-expansion algorithm, which is included merely as a special case. Moreover, contrary to \\alpha-expansion, the derived algorithms generate solutions with guaranteed optimality properties for a much wider class of problems, for example, even for MRFs with nonmetric potentials. In addition, they are capable of providing per-instance suboptimality bounds in all occasions, including discrete MRFs with an arbitrary potential function. These bounds prove to be very tight in practice (that is, very close to 1), which means that the resulting solutions are almost optimal. Our algorithms' effectiveness is demonstrated by presenting experimental results on a variety of low-level vision tasks, such as stereo matching, image restoration, image completion, and optical flow estimation, as well as on synthetic problems.

Face recognition in age related macular degeneration: perceived disability, measured disability, and performance with a bioptic device.

PubMed

Tejeria, L; Harper, R A; Artes, P H; Dickinson, C M

2002-09-01

(1) To explore the relation between performance on tasks of familiar face recognition (FFR) and face expression difference discrimination (FED) with both perceived disability in face recognition and clinical measures of visual function in subjects with age related macular degeneration (AMD). (2) To quantify the gain in performance for face recognition tasks when subjects use a bioptic telescopic low vision device. 30 subjects with AMD (age range 66-90 years; visual acuity 0.4-1.4 logMAR) were recruited for the study. Perceived (self rated) disability in face recognition was assessed by an eight item questionnaire covering a range of issues relating to face recognition. Visual functions measured were distance visual acuity (ETDRS logMAR charts), continuous text reading acuity (MNRead charts), contrast sensitivity (Pelli-Robson chart), and colour vision (large panel D-15). In the FFR task, images of famous people had to be identified. FED was assessed by a forced choice test where subjects had to decide which one of four images showed a different facial expression. These tasks were repeated with subjects using a bioptic device. Overall perceived disability in face recognition did not correlate with performance on either task, although a specific item on difficulty recognising familiar faces did correlate with FFR (r = 0.49, p<0.05). FFR performance was most closely related to distance acuity (r = -0.69, p<0.001), while FED performance was most closely related to continuous text reading acuity (r = -0.79, p<0.001). In multiple regression, neither contrast sensitivity nor colour vision significantly increased the explained variance. When using a bioptic telescope, FFR performance improved in 86% of subjects (median gain = 49%; p<0.001), while FED performance increased in 79% of subjects (median gain = 50%; p<0.01). Distance and reading visual acuity are closely associated with measured task performance in FFR and FED. A bioptic low vision device can offer a significant improvement in performance for face recognition tasks, and may be useful in reducing the handicap associated with this disability. There is, however, little evidence for a correlation between self rated difficulty in face recognition and measured performance for either task. Further work is needed to explore the complex relation between the perception of disability and measured performance.

Face recognition in age related macular degeneration: perceived disability, measured disability, and performance with a bioptic device

PubMed Central

Tejeria, L; Harper, R A; Artes, P H; Dickinson, C M

2002-01-01

Aims: (1) To explore the relation between performance on tasks of familiar face recognition (FFR) and face expression difference discrimination (FED) with both perceived disability in face recognition and clinical measures of visual function in subjects with age related macular degeneration (AMD). (2) To quantify the gain in performance for face recognition tasks when subjects use a bioptic telescopic low vision device. Methods: 30 subjects with AMD (age range 66–90 years; visual acuity 0.4–1.4 logMAR) were recruited for the study. Perceived (self rated) disability in face recognition was assessed by an eight item questionnaire covering a range of issues relating to face recognition. Visual functions measured were distance visual acuity (ETDRS logMAR charts), continuous text reading acuity (MNRead charts), contrast sensitivity (Pelli-Robson chart), and colour vision (large panel D-15). In the FFR task, images of famous people had to be identified. FED was assessed by a forced choice test where subjects had to decide which one of four images showed a different facial expression. These tasks were repeated with subjects using a bioptic device. Results: Overall perceived disability in face recognition did not correlate with performance on either task, although a specific item on difficulty recognising familiar faces did correlate with FFR (r = 0.49, p<0.05). FFR performance was most closely related to distance acuity (r = −0.69, p<0.001), while FED performance was most closely related to continuous text reading acuity (r = −0.79, p<0.001). In multiple regression, neither contrast sensitivity nor colour vision significantly increased the explained variance. When using a bioptic telescope, FFR performance improved in 86% of subjects (median gain = 49%; p<0.001), while FED performance increased in 79% of subjects (median gain = 50%; p<0.01). Conclusion: Distance and reading visual acuity are closely associated with measured task performance in FFR and FED. A bioptic low vision device can offer a significant improvement in performance for face recognition tasks, and may be useful in reducing the handicap associated with this disability. There is, however, little evidence for a correlation between self rated difficulty in face recognition and measured performance for either task. Further work is needed to explore the complex relation between the perception of disability and measured performance. PMID:12185131

Dynamic Estimation of Rigid Motion from Perspective Views via Recursive Identification of Exterior Differential Systems with Parameters on a Topological Manifold

DTIC Science & Technology

1994-02-15

0. Faugeras. Three dimensional vision, a geometric viewpoint. MIT Press, 1993. [19] 0 . D. Faugeras and S. Maybank . Motion from point mathces...multiplicity of solutions. Int. J. of Computer Vision, 1990. 1201 0.D. Faugeras, Q.T. Luong, and S.J. Maybank . Camera self-calibration: theory and...Kalrnan filter-based algorithms for estimating depth from image sequences. Int. J. of computer vision, 1989. [41] S. Maybank . Theory of

Computational Vision: A Critical Review

DTIC Science & Technology

1989-10-01

Optic News, 15:9-25, 1989. [8] H. B . Barlow and R. W. Levick . The mechanism of directional selectivity in the rabbit’s retina. J. Physiol., 173:477...comparison, other formulations, e.g., [64], used 16 @V A \\E(t=t2) (a) \\ E(t-tl) ( b ) Figure 7: An illustration of the aperture problem. Left: a bar E is...Ballard and C. M. Brown. Computer Vision. Prentice-Hall, Englewood Cliffs, NJ, 1982. [7] D. H. Ballard, R. C. Nelson, and B . Yamauchi. Animate vision

AstroCV: Astronomy computer vision library

NASA Astrophysics Data System (ADS)

González, Roberto E.; Muñoz, Roberto P.; Hernández, Cristian A.

2018-04-01

AstroCV processes and analyzes big astronomical datasets, and is intended to provide a community repository of high performance Python and C++ algorithms used for image processing and computer vision. The library offers methods for object recognition, segmentation and classification, with emphasis in the automatic detection and classification of galaxies.

Association between fine motor skills and binocular visual function in children with reading difficulties.

PubMed

Niechwiej-Szwedo, Ewa; Alramis, Fatimah; Christian, Lisa W

2017-12-01

Performance of fine motor skills (FMS) assessed by a clinical test battery has been associated with reading achievement in school-age children. However, the nature of this association remains to be established. The aim of this study was to assess FMS in children with reading difficulties using two experimental tasks, and to determine if performance is associated with reduced binocular function. We hypothesized that in comparison to an age- and sex-matched control group, children identified with reading difficulties will perform worse only on a motor task that has been shown to rely on binocular input. To test this hypothesis, motor performance was assessed using two tasks: bead-threading and peg-board in 19 children who were reading below expected grade and age-level. Binocular vision assessment included tests for stereoacuity, fusional vergence, amplitude of accommodation, and accommodative facility. In comparison to the control group, children with reading difficulties performed significantly worse on the bead-threading task. In contrast, performance on the peg-board task was similar in both groups. Accommodative facility was the only measure of binocular function significantly associated with motor performance. Findings from our exploratory study suggest that normal binocular vision may provide an important sensory input for the optimal development of FMS and reading. Given the small sample size tested in the current study, further investigation to assess the contribution of binocular vision to the development and performance of FMS and reading is warranted. Copyright © 2017 Elsevier B.V. All rights reserved.

A Research Trilogy: American and Mexican Vision Studies.

ERIC Educational Resources Information Center

Hinds, Lillian R.

1983-01-01

Describes three studies relating to visual functioning. Finds that reading retardation is the result of a clustering of factors, of multiple causation. Discusses the need to determine whether or not a student has the necessary lateral and other functional vision skills to maintain sufficient body energy for the demands of the reading task. (MG)

76 FR 73769 - Qualification of Drivers; Exemption Applications; Vision

Federal Register 2010, 2011, 2012, 2013, 2014

2011-11-29

... moving violations in a CMV. Mark A. Ferris Mr. Ferris, 55, has had amblyopia in his left eye since... an examination in 2011, his optometrist noted, ``In my professional opinion, Mr. Ferris has more than sufficient vision to perform the driving tasks required to operate any commercial motor vehicle.'' Mr. Ferris...

Colour Vision Deficiency and Physics Teaching

ERIC Educational Resources Information Center

Maule, Louise; Featonby, David

2016-01-01

1 in 12 males suffer from some form of colour vision deficiency (CVD) which in the present colour dominated world of education presentation can be a severe disadvantage. Although aware of "colourblindness" most teachers make little or no adjustment for these pupils for whom tasks may be more difficult. This article examines colour vision…

The Influence of Attentional Focus Instructions and Vision on Jump Height Performance

ERIC Educational Resources Information Center

Abdollahipour, Reza; Psotta, Rudolf; Land, William M.

2016-01-01

Purpose: Studies have suggested that the use of visual information may underlie the benefit associated with an external focus of attention. Recent studies exploring this connection have primarily relied on motor tasks that involve manipulation of an object (object projection). The present study examined whether vision influences the effect of…

VISIONS for Greater Employment Opportunities. Final Report.

ERIC Educational Resources Information Center

Orangeburg-Calhoun Technical Coll., Orangeburg, SC.

The VISIONS project, a workplace literacy program held in two manufacturing plants and a regional medical center, was conducted during an 18-month period from July 1, 1993 to December 31, 1994. During the project, staff were hired and trained, task analyses and orientation sessions were held, and tests and curricula were developed. Employees were…

Fine-grained recognition of plants from images.

PubMed

Šulc, Milan; Matas, Jiří

2017-01-01

Fine-grained recognition of plants from images is a challenging computer vision task, due to the diverse appearance and complex structure of plants, high intra-class variability and small inter-class differences. We review the state-of-the-art and discuss plant recognition tasks, from identification of plants from specific plant organs to general plant recognition "in the wild". We propose texture analysis and deep learning methods for different plant recognition tasks. The methods are evaluated and compared them to the state-of-the-art. Texture analysis is only applied to images with unambiguous segmentation (bark and leaf recognition), whereas CNNs are only applied when sufficiently large datasets are available. The results provide an insight in the complexity of different plant recognition tasks. The proposed methods outperform the state-of-the-art in leaf and bark classification and achieve very competitive results in plant recognition "in the wild". The results suggest that recognition of segmented leaves is practically a solved problem, when high volumes of training data are available. The generality and higher capacity of state-of-the-art CNNs makes them suitable for plant recognition "in the wild" where the views on plant organs or plants vary significantly and the difficulty is increased by occlusions and background clutter.

Multi-Source Multi-Target Dictionary Learning for Prediction of Cognitive Decline

PubMed Central

Zhang, Jie; Li, Qingyang; Caselli, Richard J.; Thompson, Paul M.; Ye, Jieping; Wang, Yalin

2017-01-01

Alzheimer’s Disease (AD) is the most common type of dementia. Identifying correct biomarkers may determine pre-symptomatic AD subjects and enable early intervention. Recently, Multi-task sparse feature learning has been successfully applied to many computer vision and biomedical informatics researches. It aims to improve the generalization performance by exploiting the shared features among different tasks. However, most of the existing algorithms are formulated as a supervised learning scheme. Its drawback is with either insufficient feature numbers or missing label information. To address these challenges, we formulate an unsupervised framework for multi-task sparse feature learning based on a novel dictionary learning algorithm. To solve the unsupervised learning problem, we propose a two-stage Multi-Source Multi-Target Dictionary Learning (MMDL) algorithm. In stage 1, we propose a multi-source dictionary learning method to utilize the common and individual sparse features in different time slots. In stage 2, supported by a rigorous theoretical analysis, we develop a multi-task learning method to solve the missing label problem. Empirical studies on an N = 3970 longitudinal brain image data set, which involves 2 sources and 5 targets, demonstrate the improved prediction accuracy and speed efficiency of MMDL in comparison with other state-of-the-art algorithms. PMID:28943731

Evaluation of the impact of deep learning architectural components selection and dataset size on a medical imaging task

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Gros, Eric

2018-03-01

Deep Learning (DL) has been successfully applied in numerous fields fueled by increasing computational power and access to data. However, for medical imaging tasks, limited training set size is a common challenge when applying DL. This paper explores the applicability of DL to the task of classifying a single axial slice from a CT exam into one of six anatomy regions. A total of 29000 images selected from 223 CT exams were manually labeled for ground truth. An additional 54 exams were labeled and used as an independent test set. The network architecture developed for this application is composed of 6 convolutional layers and 2 fully connected layers with RELU non-linear activations between each layer. Max-pooling was used after every second convolutional layer, and a softmax layer was used at the end. Given this base architecture, the effect of inclusion of network architecture components such as Dropout and Batch Normalization on network performance and training is explored. The network performance as a function of training and validation set size is characterized by training each network architecture variation using 5,10,20,40,50 and 100% of the available training data. The performance comparison of the various network architectures was done for anatomy classification as well as two computer vision datasets. The anatomy classifier accuracy varied from 74.1% to 92.3% in this study depending on the training size and network layout used. Dropout layers improved the model accuracy for all training sizes.

Topographic Mapping of Residual Vision by Computer

ERIC Educational Resources Information Center

MacKeben, Manfred

2008-01-01

Many persons with low vision have diseases that damage the retina only in selected areas, which can lead to scotomas (blind spots) in perception. The most frequent of these diseases is age-related macular degeneration (AMD), in which foveal vision is often impaired by a central scotoma that impairs vision of fine detail and causes problems with…

Artificial intelligence, expert systems, computer vision, and natural language processing

NASA Technical Reports Server (NTRS)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

Low-cost real-time automatic wheel classification system

NASA Astrophysics Data System (ADS)

Shabestari, Behrouz N.; Miller, John W. V.; Wedding, Victoria

1992-11-01

This paper describes the design and implementation of a low-cost machine vision system for identifying various types of automotive wheels which are manufactured in several styles and sizes. In this application, a variety of wheels travel on a conveyor in random order through a number of processing steps. One of these processes requires the identification of the wheel type which was performed manually by an operator. A vision system was designed to provide the required identification. The system consisted of an annular illumination source, a CCD TV camera, frame grabber, and 386-compatible computer. Statistical pattern recognition techniques were used to provide robust classification as well as a simple means for adding new wheel designs to the system. Maintenance of the system can be performed by plant personnel with minimal training. The basic steps for identification include image acquisition, segmentation of the regions of interest, extraction of selected features, and classification. The vision system has been installed in a plant and has proven to be extremely effective. The system properly identifies the wheels correctly up to 30 wheels per minute regardless of rotational orientation in the camera's field of view. Correct classification can even be achieved if a portion of the wheel is blocked off from the camera. Significant cost savings have been achieved by a reduction in scrap associated with incorrect manual classification as well as a reduction of labor in a tedious task.

A Machine Vision Quality Control System for Industrial Acrylic Fibre Production

NASA Astrophysics Data System (ADS)

Heleno, Paulo; Davies, Roger; Correia, Bento A. Brázio; Dinis, João

2002-12-01

This paper describes the implementation of INFIBRA, a machine vision system used in the quality control of acrylic fibre production. The system was developed by INETI under a contract with a leading industrial manufacturer of acrylic fibres. It monitors several parameters of the acrylic production process. This paper presents, after a brief overview of the system, a detailed description of the machine vision algorithms developed to perform the inspection tasks unique to this system. Some of the results of online operation are also presented.

Crepuscular and Nocturnal Illumination and Its Effects on Color Perception by the Nocturnal Hawkmoth Deilephila elpenor

DTIC Science & Technology

2006-01-01

vision may enhance recognition of conspecifics or be used in mating. While mating in moths is thought to be entirely mediated by olfaction , most tasks are...time, unambiguous evidence for true color vision under scotopic conditions has only recently been acquired (Kelber et al., 2002; Roth and Kelber, 2004...color under starlight and dim moonlight, respectively, raise at least two issues. First, what is the selective advantage of color vision in these

The Effect of the Usage of Computer-Based Assistive Devices on the Functioning and Quality of Life of Individuals Who Are Blind or Have Low Vision

ERIC Educational Resources Information Center

Rosner, Yotam; Perlman, Amotz

2018-01-01

Introduction: The Israel Ministry of Social Affairs and Social Services subsidizes computer-based assistive devices for individuals with visual impairments (that is, those who are blind or have low vision) to assist these individuals in their interactions with computers and thus to enhance their independence and quality of life. The aim of this…

Software for Real-Time Analysis of Subsonic Test Shot Accuracy

DTIC Science & Technology

2014-03-01

used the C++ programming language, the Open Source Computer Vision ( OpenCV ®) software library, and Microsoft Windows® Application Programming...video for comparison through OpenCV image analysis tools. Based on the comparison, the software then computed the coordinates of each shot relative to...DWB researchers wanted to use the Open Source Computer Vision ( OpenCV ) software library for capturing and analyzing frames of video. OpenCV contains

Improved opponent color local binary patterns: an effective local image descriptor for color texture classification

NASA Astrophysics Data System (ADS)

Bianconi, Francesco; Bello-Cerezo, Raquel; Napoletano, Paolo

2018-01-01

Texture classification plays a major role in many computer vision applications. Local binary patterns (LBP) encoding schemes have largely been proven to be very effective for this task. Improved LBP (ILBP) are conceptually simple, easy to implement, and highly effective LBP variants based on a point-to-average thresholding scheme instead of a point-to-point one. We propose the use of this encoding scheme for extracting intra- and interchannel features for color texture classification. We experimentally evaluated the resulting improved opponent color LBP alone and in concatenation with the ILBP of the local color contrast map on a set of image classification tasks over 9 datasets of generic color textures and 11 datasets of biomedical textures. The proposed approach outperformed other grayscale and color LBP variants in nearly all the datasets considered and proved competitive even against image features from last generation convolutional neural networks, particularly for the classification of biomedical images.

[Functional magnetic resonance imaging of brain of college students with internet addiction].

PubMed

DU, Wanping; Liu, Jun; Gao, Xunping; Li, Lingjiang; Li, Weihui; Li, Xin; Zhang, Yan; Zhou, Shunke

2011-08-01

To explore the functional locations of brain regions related to internet addiction (IA)with task-functional magnetic resonance imaging (fMRI). Nineteen college students who had internet game addition and 19 controls accepted the stimuli of videos via computer. The 3.0 Tesla MRI was used to record the Results of echo plannar imaging. The block design method was used. Intragroup and intergroup analysis Results in the 2 groups were obtained. The differences between the 2 groups were analyzed. The internet game videos markedly activated the brain regions of the college students who had or had no internet game addiction. Compared with the control group, the IA group showed increased activation in the right superior parietal lobule, right insular lobe, right precuneus, right cingulated gyrus, and right superior temporal gyrus. Internet game tasks can activate the vision, space, attention and execution center which are composed of temporal occipital gyrus and frontal parietal gyrus. Abnormal brain function and lateral activation of the right brain may exist in IA.

Object class segmentation of RGB-D video using recurrent convolutional neural networks.

PubMed

Pavel, Mircea Serban; Schulz, Hannes; Behnke, Sven

2017-04-01

Object class segmentation is a computer vision task which requires labeling each pixel of an image with the class of the object it belongs to. Deep convolutional neural networks (DNN) are able to learn and take advantage of local spatial correlations required for this task. They are, however, restricted by their small, fixed-sized filters, which limits their ability to learn long-range dependencies. Recurrent Neural Networks (RNN), on the other hand, do not suffer from this restriction. Their iterative interpretation allows them to model long-range dependencies by propagating activity. This property is especially useful when labeling video sequences, where both spatial and temporal long-range dependencies occur. In this work, a novel RNN architecture for object class segmentation is presented. We investigate several ways to train such a network. We evaluate our models on the challenging NYU Depth v2 dataset for object class segmentation and obtain competitive results. Copyright © 2017 Elsevier Ltd. All rights reserved.

Coordinating complex decision support activities across distributed applications

NASA Technical Reports Server (NTRS)

Adler, Richard M.

1994-01-01

Knowledge-based technologies have been applied successfully to automate planning and scheduling in many problem domains. Automation of decision support can be increased further by integrating task-specific applications with supporting database systems, and by coordinating interactions between such tools to facilitate collaborative activities. Unfortunately, the technical obstacles that must be overcome to achieve this vision of transparent, cooperative problem-solving are daunting. Intelligent decision support tools are typically developed for standalone use, rely on incompatible, task-specific representational models and application programming interfaces (API's), and run on heterogeneous computing platforms. Getting such applications to interact freely calls for platform independent capabilities for distributed communication, as well as tools for mapping information across disparate representations. Symbiotics is developing a layered set of software tools (called NetWorks! for integrating and coordinating heterogeneous distributed applications. he top layer of tools consists of an extensible set of generic, programmable coordination services. Developers access these services via high-level API's to implement the desired interactions between distributed applications.

Insights from Classifying Visual Concepts with Multiple Kernel Learning

PubMed Central

Binder, Alexander; Nakajima, Shinichi; Kloft, Marius; Müller, Christina; Samek, Wojciech; Brefeld, Ulf; Müller, Klaus-Robert; Kawanabe, Motoaki

2012-01-01

Combining information from various image features has become a standard technique in concept recognition tasks. However, the optimal way of fusing the resulting kernel functions is usually unknown in practical applications. Multiple kernel learning (MKL) techniques allow to determine an optimal linear combination of such similarity matrices. Classical approaches to MKL promote sparse mixtures. Unfortunately, 1-norm regularized MKL variants are often observed to be outperformed by an unweighted sum kernel. The main contributions of this paper are the following: we apply a recently developed non-sparse MKL variant to state-of-the-art concept recognition tasks from the application domain of computer vision. We provide insights on benefits and limits of non-sparse MKL and compare it against its direct competitors, the sum-kernel SVM and sparse MKL. We report empirical results for the PASCAL VOC 2009 Classification and ImageCLEF2010 Photo Annotation challenge data sets. Data sets (kernel matrices) as well as further information are available at http://doc.ml.tu-berlin.de/image_mkl/(Accessed 2012 Jun 25). PMID:22936970

[Ophthalmologist and "computer vision syndrome"].

PubMed

Barar, A; Apatachioaie, Ioana Daniela; Apatachioaie, C; Marceanu-Brasov, L

2007-01-01

The authors had tried to collect the data available on the Internet about a subject that we consider as being totally ignored in the Romanian scientific literature and unexpectedly insufficiently treated in the specialized ophthalmologic literature. Known in the specialty literature under the generic name of "Computer vision syndrome", it is defined by the American Optometric Association as a complex of eye and vision problems related to the activities which stress the near vision and which are experienced in relation, or during, the use of the computer. During the consultations we hear frequent complaints of eye-strain - asthenopia, headaches, blurred distance and/or near vision, dry and irritated eyes, slow refocusing, neck and backache, photophobia, sensation of diplopia, light sensitivity, and double vision, but because of the lack of information, we overlooked them too easily, without going thoroughly into the real motives. In most of the developed countries, there are recommendations issued by renowned medical associations with regard to the definition, the diagnosis, and the methods for the prevention, treatment and periodical control of the symptoms found in computer users, in conjunction with an extremely detailed ergonomic legislation. We found out that these problems incite a much too low interest in our country. We would like to rouse the interest of our ophthalmologist colleagues in the understanding and the recognition of these symptoms and in their treatment, or at least their improvement, through specialized measures or through the cooperation with our specialist occupational medicine colleagues.

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

PubMed

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

2013-01-07

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

Acquiring basic and advanced laparoscopic skills in novices using two-dimensional (2D), three-dimensional (3D) and ultra-high definition (4K) vision systems: A randomized control study.

PubMed

Abdelrahman, M; Belramman, A; Salem, R; Patel, B

2018-05-01

To compare the performance of novices in laparoscopic peg transfer and intra-corporeal suturing tasks in two-dimensional (2D), three-dimensional (3D) and ultra-high definition (4K) vision systems. Twenty-four novices were randomly assigned to 2D, 3D and 4K groups, eight in each group. All participants performed the two tasks on a box trainer until reaching proficiency. Their performance was assessed based on completion time, number of errors and number of repetitions using the validated FLS proficiency criteria. Eight candidates in each group completed the training curriculum. The mean performance time (in minutes) for the 2D group was 558.3, which was more than that of the 3D and 4K groups of 316.7 and 310.4 min respectively (P < 0.0001). The mean number of repetitions was lower for the 3D and 4K groups versus the 2D group: 125.9 and 127.4 respectively versus 152.1 (P < 0.0001). The mean number of errors was lower for the 4K group versus the 3D and 2D groups: 1.2 versus 26.1 and 50.2 respectively (P < 0.0001). The 4K vision system improved accuracy in acquiring laparoscopic skills for novices in complex tasks, which was shown in significant reduction in number of errors compared to the 3D and the 2D vision systems. The 3D and the 4K vision systems significantly improved speed and accuracy when compared to the 2D vision system based on shorter performance time, fewer errors and lesser number of repetitions. Copyright © 2018 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.