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A model for simulation of color vision deficiency and a color contrast enhancement technique for dichromats; Um modelo para simulação das deˇciências na percepção de cores e uma técnica de aumento do contraste de cores para dicromátas

Machado, Gustavo Mello
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Dissertação Formato: application/pdf
Português
Relevância na Pesquisa
35.86%
As Deficiências na Percepção de Cores (DPC) afetam aproximadamente 200 milhões de pessoas em todo o mundo, comprometendo suas habilidades para efetivamente realizar tarefas relacionadas com cores e com visualização. Isto impacta significantemente os âmbitos pessoais e profissionais de suas vidas. Este trabalho apresenta um modelo baseado na fisiologia para simulação da percepção de cores. Além de modelar visão de cores normal, ele também compreende os tipos mais predominantes de deficiências na visão de cores (i.e., protanopia, deuteranopia, protanomalia e deuteranomalia), cujas causas são hereditárias. Juntos estes representam aproximadamente 99.96% de todos os casos de DPC. Para modelar a percepção de cores da visão humana, este modelo é baseado na teoria dos estágios e é derivado de dados reportados em estudos eletrofisiológicos. Ele é o primeiro modelo a consistentemente tratar visão de cores normal, tricromacia anômala e dicromacia de modo unificados. Seus resultados foram validados por avaliações experimentais envolvendo grupos de indivíduos com deficiência na percepção de cores e outros com visão de cores normal. Além disso, ele pode proporcionar a melhor compreensão e um feedback sobre como aperfeiçoar as experiências de visualização por indivíduos com DPC. Ele também proporciona um framework para se testar hipóteses sobre alguns aspectos acerca das células fotoreceptoras na retina de indivíduos com deficiência na percepção de cores. Este trabalho também apresenta uma técnica automática de recoloração de imagens que visa realçar o contraste de cores para indivíduos dicromatas com custo computacional variando linearmente com o número de pixels. O algoritmo proposto pode ser eficientemente implementado em GPUs...

Human Motion Analysis: methodologies and applications

Maria João M. Vasconcelos; João Manuel R. S. Tavares
Fonte: Universidade do Porto Publicador: Universidade do Porto
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
35.92%
The study of motion is one of the most interesting areas in Computational Vision, particularly the human motion research. During these last decades several works were presented regarding this subject. Human motion analysis is complex, non-linear and time variant and its tracking can be done using Computational Vision through, for example, human modeling.In order to make human motion analysis more computational tractable, some assumptions are often made. For instance: regarding to movements involved, if the images have one or more persons in the workspace at the same time, if the cameras are static or not or the subject remains inside the workspace being acquired; regarding the environment, if light conditions are constant, the background is static and uniform or not; and regarding the subject in analysis, if its shape and motion are known, if has special markers or clothes.In this work, we intend to present a review about the computational methodologies used in human motion, their advantages and disadvantages and some of their main applications. The study of human motion in image sequences usually follows a general framework: feature extraction, feature correspondence and high-level processing. Feature extraction is related to human motion modeling; these models can be built using stick figures...

Modular models of task based visually guided behavior

Rothkopf, Constantin A. (1969 - ); Ballard, Dana Harry ; Hayhoe, Mary M.
Fonte: University of Rochester Publicador: University of Rochester
Tipo: Tese de Doutorado Formato: Number of Pages:xix, 136 leaves
Português
Relevância na Pesquisa
35.82%
Thesis (Ph. D.)--University of Rochester. Dept. of Brain and Cognitive Sciences, Dept. of Computer Science, 2009.; Human behavior in extended visuomotor tasks is not well understood. This thesis considers the visuomotor task of navigating along a walkway while avoiding obstacles and approaching targets. Behavioral data of humans executing this task is presented together with a model of sidewalk navigation based on the reinforcement-learning framework. The connection between model and empirical data is made by using a new inverse reinforcement learning algorithm that estimates the parameters of the learning model so as to best match the observed human behavior. Thus, this work proposes to understand human visuomotor behavior in terms of learned solutions to specific tasks. First, the analysis of behavioral data shows the limitations of current saliency-based models describing human gaze selection and quantifies the influences of task on gaze selection. The analysis furthermore demonstrates the similarity in walked trajectories and gaze patterns between subjects and how the similarities in behavior impose regularities on the input to the visual system, such as contrast and model simple cell response statistics. If human vision is understood as an active process that has to learn how to select relevant information in time...

Improving Human Vision Modeling in Analytical Combat Simulations

Balogh, Imre
Fonte: Escola de Pós-Graduação Naval Publicador: Escola de Pós-Graduação Naval
Tipo: Conferência ou Objeto de Conferência
Português
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45.69%
The 11th Annual MOVES Research and Education Summit, July 12-14, 2011. SESSION #5: Agents and Combat Modeling. Moderator

Soviet Visual Perception Research: Application to Target Acquisition Modeling

Lind, Judith H.
Fonte: Monterey, California. Naval Postgraduate School Publicador: Monterey, California. Naval Postgraduate School
Tipo: Relatório
Português
Relevância na Pesquisa
35.99%
Five Soviet books have been reviewed to ascertain how target acquisition was modeled in the former Soviet Union and to determine if information is sufficient to program a comprehensive model. Authors include V.D. Glezer and K.N. Dudicin of the Pavlov Institute of Physiology, St. Petersburg. Since the books (published between 1961 and 1985) were machine-translated from the Russian, some original concepts may have not been correctly interpreted. Still, they provide an excellent overview of 30 years of vision research at the Pavlov Institute and of Russian thought on vision and the brain. The Soviet texts emphasize cognitive mechanisms of vision more than is common in U.S. military models. Mental models and the observer's mindset are considered very important. More emphasis is given to modeling recognition and identification (versus detection) than in the U.S. The result of this study is a sketchy and incomplete search and target acquisition model, unsuitable for programming at present. The reviewed books mostly provide information about vision in general, with emphasis on proposed neurophysiological and psychological processes that may explain experimental results. They obviously were not written with computer programs in mind. Extensive data collection would be required to quantify the Soviet vision concepts for use in a computer model; U.S. Army Training and Doctrine Analysis Command...

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

Ghodrati, Masoud; Farzmahdi, Amirhossein; Rajaei, Karim; Ebrahimpour, Reza; Khaligh-Razavi, Seyed-Mahdi
Fonte: Frontiers Media S.A. Publicador: Frontiers Media S.A.
Tipo: Artigo de Revista Científica
Publicado em 18/07/2014 Português
Relevância na Pesquisa
35.86%
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...

From perception to action and vice versa: A new architecture showing how perception and action can modulate each other simultaneously

Palomino, Antonio Jesús; García Olaya, Ángel; Fernández Rebollo, Fernando; Bandera, Juan Pedro
Fonte: IEEE - The Institute of Electrical and Electronics Engineers, Inc Publicador: IEEE - The Institute of Electrical and Electronics Engineers, Inc
Tipo: info:eu-repo/semantics/acceptedVersion; info:eu-repo/semantics/bookPart; info:eu-repo/semantics/conferenceObject
Publicado em /09/2013 Português
Relevância na Pesquisa
35.78%
Artificial vision systems can not process all the information that they receive from the world in real time because it is highly expensive and inefficient in terms of computational cost. However, inspired by biological perception systems, it is possible to develop an artificial attention model able to select only the relevant part of the scene, as human vision does. From the Automated Planning point of view, a relevant area can be seen as an area where the objects involved in the execution of a plan are located. Thus, the planning system should guide the attention model to track relevant objects. But, at the same time, the perceived objects may constrain or provide new information that could suggest the modification of a current plan. Therefore, a plan that is being executed should be adapted or recomputed taking into account actual information perceived from the world. In this work, we introduce an architecture that creates a symbiosis between the planning and the attention modules of a robotic system, linking visual features with high level behaviours. The architecture is based on the interaction of an oversubscription planner, that produces plans constrained by the information perceived from the vision system, and an object-based attention system...

First-Order Modeling and Stability Analysis of Illusory Contours

Jung, Yoon-Mo; Shen, Jianhong
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 19/10/2005 Português
Relevância na Pesquisa
45.83%
In visual cognition, illusions help elucidate certain intriguing latent perceptual functions of the human vision system, and their proper mathematical modeling and computational simulation are therefore deeply beneficial to both biological and computer vision. Inspired by existent prior works, the current paper proposes a first-order energy-based model for analyzing and simulating illusory contours. The lower complexity of the proposed model facilitates rigorous mathematical analysis on the detailed geometric structures of illusory contours. After being asymptotically approximated by classical active contours, the proposed model is then robustly computed using the celebrated level-set method of Osher and Sethian (J. Comput. Phys., 79:12-49, 1988) with a natural supervising scheme. Potential cognitive implications of the mathematical results are addressed, and generic computational examples are demonstrated and discussed.; Comment: 21 pages

Cooking in the kitchen: A generative approach to the recognition, parsing and segmentation of human daily activities

Kuehne, Hilde; Serre, Thomas
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 25/08/2015 Português
Relevância na Pesquisa
35.79%
As research on action recognition matures, the focus is shifting away from categorizing basic task-oriented actions using hand-segmented video datasets to understanding complex goal-oriented daily human activities in real-world settings. Temporally structured models would seem obvious to tackle this set of problems, but so far, cases where these models have outperformed simpler unstructured bag-of-word types of models are scarce. With the increasing availability of large human activity datasets, combined with the development of novel feature coding techniques that yield more compact representations, it is time to revisit structured generative approaches. Here, we describe an end-to-end generative approach from the encoding of features to the structural modeling of complex human activities by applying Fisher vectors and temporal models for the analysis of video sequences. We systematically evaluate the proposed approach on several available datasets (ADL, MPIICooking, and Breakfast datasets) using a variety of performance metrics. Through extensive system evaluations, we demonstrate that combining compact video representations based on Fisher Vectors with HMM-based modeling yields very significant gains in accuracy and when properly trained with sufficient training samples...

Learning Object Arrangements in 3D Scenes using Human Context

Jiang, Yun; Lim, Marcus; Saxena, Ashutosh
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 27/06/2012 Português
Relevância na Pesquisa
35.8%
We consider the problem of learning object arrangements in a 3D scene. The key idea here is to learn how objects relate to human poses based on their affordances, ease of use and reachability. In contrast to modeling object-object relationships, modeling human-object relationships scales linearly in the number of objects. We design appropriate density functions based on 3D spatial features to capture this. We learn the distribution of human poses in a scene using a variant of the Dirichlet process mixture model that allows sharing of the density function parameters across the same object types. Then we can reason about arrangements of the objects in the room based on these meaningful human poses. In our extensive experiments on 20 different rooms with a total of 47 objects, our algorithm predicted correct placements with an average error of 1.6 meters from ground truth. In arranging five real scenes, it received a score of 4.3/5 compared to 3.7 for the best baseline method.; Comment: Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)

Geometric Analysis of the Conformal Camera for Intermediate-Level Vision and Perisaccadic Perception

Turski, Jacek
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
35.94%
A binocular system developed by the author in terms of projective Fourier transform (PFT) of the conformal camera, which numerically integrates the head, eyes, and visual cortex, is used to process visual information during saccadic eye movements. Although we make three saccades per second at the eyeball's maximum speed of 700 deg/sec, our visual system accounts for these incisive eye movements to produce a stable percept of the world. This visual constancy is maintained by neuronal receptive field shifts in various retinotopically organized cortical areas prior to saccade onset, giving the brain access to visual information from the saccade's target before the eyes' arrival. It integrates visual information acquisition across saccades. Our modeling utilizes basic properties of PFT. First, PFT is computable by FFT in complex logarithmic coordinates that approximate the retinotopy. Second, a translation in retinotopic (logarithmic) coordinates, modeled by the shift property of the Fourier transform, remaps the presaccadic scene into a postsaccadic reference frame. It also accounts for the perisaccadic mislocalization observed by human subjects in laboratory experiments. Because our modeling involves cross-disciplinary areas of conformal geometry...

Kinects and Human Kinetics: A New Approach for Studying Crowd Behavior

Seer, Stefan; Brändle, Norbert; Ratti, Carlo
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 10/10/2012 Português
Relevância na Pesquisa
35.79%
Modeling crowd behavior relies on accurate data of pedestrian movements at a high level of detail. Imaging sensors such as cameras provide a good basis for capturing such detailed pedestrian motion data. However, currently available computer vision technologies, when applied to conventional video footage, still cannot automatically unveil accurate motions of groups of people or crowds from the image sequences. We present a novel data collection approach for studying crowd behavior which uses the increasingly popular low-cost sensor Microsoft Kinect. The Kinect captures both standard camera data and a three-dimensional depth map. Our human detection and tracking algorithm is based on agglomerative clustering of depth data captured from an elevated view - in contrast to the lateral view used for gesture recognition in Kinect gaming applications. Our approach transforms local Kinect 3D data to a common world coordinate system in order to stitch together human trajectories from multiple Kinects, which allows for a scalable and flexible capturing area. At a testbed with real-world pedestrian traffic we demonstrate that our approach can provide accurate trajectories from three Kinects with a Pedestrian Detection Rate of up to 94% and a Multiple Object Tracking Precision of 4 cm. Using a comprehensive dataset of 2240 captured human trajectories we calibrate three variations of the Social Force model. The results of our model validations indicate their particular ability to reproduce the observed crowd behavior in microscopic simulations.; Comment: Preprint submitted to Transportation Research Part C: Emerging Technologies...

An Integrated System for 3D Gaze Recovery and Semantic Analysis of Human Attention

Paletta, Lucas; Santner, Katrin; Fritz, Gerald
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 30/07/2013 Português
Relevância na Pesquisa
35.81%
This work describes a computer vision system that enables pervasive mapping and monitoring of human attention. The key contribution is that our methodology enables full 3D recovery of the gaze pointer, human view frustum and associated human centered measurements directly into an automatically computed 3D model in real-time. We apply RGB-D SLAM and descriptor matching methodologies for the 3D modeling, localization and fully automated annotation of ROIs (regions of interest) within the acquired 3D model. This innovative methodology will open new avenues for attention studies in real world environments, bringing new potential into automated processing for human factors technologies.

Modeling Visual Information Processing in Brain: A Computer Vision Point of View and Approach

Diamant, Emanuel
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 07/08/2007 Português
Relevância na Pesquisa
35.85%
We live in the Information Age, and information has become a critically important component of our life. The success of the Internet made huge amounts of it easily available and accessible to everyone. To keep the flow of this information manageable, means for its faultless circulation and effective handling have become urgently required. Considerable research efforts are dedicated today to address this necessity, but they are seriously hampered by the lack of a common agreement about "What is information?" In particular, what is "visual information" - human's primary input from the surrounding world. The problem is further aggravated by a long-lasting stance borrowed from the biological vision research that assumes human-like information processing as an enigmatic mix of perceptual and cognitive vision faculties. I am trying to find a remedy for this bizarre situation. Relying on a new definition of "information", which can be derived from Kolmogorov's compexity theory and Chaitin's notion of algorithmic information, I propose a unifying framework for visual information processing, which explicitly accounts for the perceptual and cognitive image processing peculiarities. I believe that this framework will be useful to overcome the difficulties that are impeding our attempts to develop the right model of human-like intelligent image processing.; Comment: That is a journal version of a paper that in 2007 has been submitted to 15 computer vision conferences and was discarded by 11 of them

Unsupervised Temporal Segmentation of Repetitive Human Actions Based on Kinematic Modeling and Frequency Analysis

Wang, Qifei; Kurillo, Gregorij; Ofli, Ferda; Bajcsy, Ruzena
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 13/12/2015 Português
Relevância na Pesquisa
35.78%
In this paper, we propose a method for temporal segmentation of human repetitive actions based on frequency analysis of kinematic parameters, zero-velocity crossing detection, and adaptive k-means clustering. Since the human motion data may be captured with different modalities which have different temporal sampling rate and accuracy (e.g., optical motion capture systems vs. Microsoft Kinect), we first apply a generic full-body kinematic model with an unscented Kalman filter to convert the motion data into a unified representation that is robust to noise. Furthermore, we extract the most representative kinematic parameters via the primary frequency analysis. The sequences are segmented based on zero-velocity crossing of the selected parameters followed by an adaptive k-means clustering to identify the repetition segments. Experimental results demonstrate that for the motion data captured by both the motion capture system and the Microsoft Kinect, our proposed algorithm obtains robust segmentation of repetitive action sequences.; Comment: 9 pages, International Conference on 3D Vision 2015

Pixels to Voxels: Modeling Visual Representation in the Human Brain

Agrawal, Pulkit; Stansbury, Dustin; Malik, Jitendra; Gallant, Jack L.
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 18/07/2014 Português
Relevância na Pesquisa
45.92%
The human brain is adept at solving difficult high-level visual processing problems such as image interpretation and object recognition in natural scenes. Over the past few years neuroscientists have made remarkable progress in understanding how the human brain represents categories of objects and actions in natural scenes. However, all current models of high-level human vision operate on hand annotated images in which the objects and actions have been assigned semantic tags by a human operator. No current models can account for high-level visual function directly in terms of low-level visual input (i.e., pixels). To overcome this fundamental limitation we sought to develop a new class of models that can predict human brain activity directly from low-level visual input (i.e., pixels). We explored two classes of models drawn from computer vision and machine learning. The first class of models was based on Fisher Vectors (FV) and the second was based on Convolutional Neural Networks (ConvNets). We find that both classes of models accurately predict brain activity in high-level visual areas, directly from pixels and without the need for any semantic tags or hand annotation of images. This is the first time that such a mapping has been obtained. The fit models provide a new platform for exploring the functional principles of human vision...

Building Statistical Shape Spaces for 3D Human Modeling

Pishchulin, Leonid; Wuhrer, Stefanie; Helten, Thomas; Theobalt, Christian; Schiele, Bernt
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 19/03/2015 Português
Relevância na Pesquisa
35.79%
Statistical models of 3D human shape and pose learned from scan databases have developed into valuable tools to solve a variety of vision and graphics problems. Unfortunately, most publicly available models are of limited expressiveness as they were learned on very small databases that hardly reflect the true variety in human body shapes. In this paper, we contribute by rebuilding a widely used statistical body representation from the largest commercially available scan database, and making the resulting model available to the community (visit http://humanshape.mpi-inf.mpg.de). As preprocessing several thousand scans for learning the model is a challenge in itself, we contribute by developing robust best practice solutions for scan alignment that quantitatively lead to the best learned models. We make implementations of these preprocessing steps also publicly available. We extensively evaluate the improved accuracy and generality of our new model, and show its improved performance for human body reconstruction from sparse input data.

Analysis of the optical field on the human retina from wavefront aberration data

Barbero, Sergio; Marcos, Susana
Fonte: Optical Society of America Publicador: Optical Society of America
Tipo: Artículo Formato: 365532 bytes; application/pdf
Português
Relevância na Pesquisa
35.78%
6 pages, 4 figures.-- OCIS codes: 050.1970, 330.5370, 330.7326.-- PMID: 18758554 [PubMed].-- Printed version published on Sep 2008.; Wave aberrations in the human eye are usually known with respect to the ideal spherical wavefront in the exit pupil. Using Kirchhoff ’s diffraction theory, we have derived a diffraction integral to compute the optical field on the retina from the wave aberration data. We have proposed a numerical algorithm based on the Stamnes–Spjelkavik–Pedersen (SSP) method to solve that integral. We have shown which approximations are admissible to reduce the complexity of the diffraction integral. In addition, we have compared our results with those of the conventional procedure used to compute intensities on the retina. We have found significant differences between our results and the conventional ones.; The authors acknowledge funding from an EURYI Award (ESF-EUROHORCs), from FIS2005-04382 (Ministerio de Educación y Ciencia) to S. Marcos, and from the I3P (CSIC) Program to S. Barbero.; Peer reviewed

Color in scientific visualization: Perception and image-based data display

Zhang, Hongqin
Fonte: Rochester Instituto de Tecnologia Publicador: Rochester Instituto de Tecnologia
Tipo: Dissertação
Português
Relevância na Pesquisa
65.93%
Visualization is the transformation of information into a visual display that enhances users understanding and interpretation of the data. This thesis project has investigated the use of color and human vision modeling for visualization of image-based scientific data. Two preliminary psychophysical experiments were first conducted on uniform color patches to analyze the perception and understanding of different color attributes, which provided psychophysical evidence and guidance for the choice of color space/attributes for color encoding. Perceptual color scales were then designed for univariate and bivariate image data display and their effectiveness was evaluated through three psychophysical experiments. Some general guidelines were derived for effective color scales design. Extending to high-dimensional data, two visualization techniques were developed for hyperspectral imagery. The first approach takes advantage of the underlying relationships between PCA/ICA of hyperspectral images and the human opponent color model, and maps the first three PCs or ICs to several opponent color spaces including CIELAB, HSV, YCbCr, and YUV. The gray world assumption was adopted to automatically set the mapping origins. The rendered images are well color balanced and can offer a first look capability or initial classification for a wide variety of spectral scenes. The second approach combines a true color image and a PCA image based on a biologically inspired visual attention model that simulates the center-surround structure of visual receptive fields as the difference between fine and coarse scales. The model was extended to take into account human contrast sensitivity and include high-level information such as the second order statistical structure in the form of local variance map...

Visual Abilities in older Adults Explain Age-Differences in Stroop and Fluid Intellegence but Not Face Recognition: Implications for the Vision-Cognition Connection

Anstey, Kaarin; Dain, Stephen; Andrews, Sally; Drobny, Juliette V
Fonte: Swets Zeitlinger BV Publicador: Swets Zeitlinger BV
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
35.8%
The associations among age, visual abilities and cognitive abilities were investigated using structural equation modeling. Measures of Visual Acuity, Colour Vision, Contrast Sensitivity, Stroop, Face Recognition and Fluid intelligence (Gf) were administered to a volunteer sample (n = 90) aged 60-87. Visual Acuity was associated with Gf even after controlling for chronological age. Age differences in Stroop were explained entirely by Colour Vision performance. However, neither Visual Acuity nor Colour Vision explained age-differences in Face Recognition. The results show that performance on some neuropsychological tests is influenced by visual ability and challenge the conventional identification of ageing effects on the Stroop task with deficits in frontal executive functioning. Visual abilities do not, however, contribute to age-differences in all cognitive domains suggesting that sensory and cognitive performance declines are not necessarily due to common biological ageing processes.