Abnormal Depth Perception from Motion Parallax in Amblyopic Observers
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The Hodgkin-Huxley Neuron Model for Motion Detection in Image Sequences Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray
The Hodgkin-Huxley neuron model for motion detection in image sequences Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray To cite this version: Hayat Yedjour, Boudjelal Meftah, Dounia Yedjour, Olivier Lézoray. The Hodgkin-Huxley neuron model for motion detection in image sequences. Neural Computing and Applications, Springer Verlag, In press, 10.1007/s00521-021-06446-0. hal-03331961 HAL Id: hal-03331961 https://hal.archives-ouvertes.fr/hal-03331961 Submitted on 2 Sep 2021 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Noname manuscript No. (will be inserted by the editor) The Hodgkin{Huxley neuron model for motion detection in image sequences Hayat Yedjour · Boudjelal Meftah · Dounia Yedjour · Olivier L´ezoray Received: date / Accepted: date Abstract In this paper, we consider a biologically-inspired spiking neural network model for motion detection. The proposed model simulates the neu- rons' behavior in the cortical area MT to detect different kinds of motion in image sequences. We choose the conductance-based neuron model of the Hodgkin-Huxley to define MT cell responses. Based on the center-surround antagonism of MT receptive fields, we model the area MT by its great pro- portion of cells with directional selective responses. -
3D Computational Modeling and Perceptual Analysis of Kinetic Depth Effects
Computational Visual Media DOI 10.1007/s41095-xxx-xxxx-x Vol. x, No. x, month year, xx–xx Research Article 3D Computational Modeling and Perceptual Analysis of Kinetic Depth Effects Meng-Yao Cui1, Shao-Ping Lu1( ), Miao Wang2, Yong-Liang Yang3, Yu-Kun Lai4, and Paul L. Rosin4 c The Author(s) 2020. This article is published with open access at Springerlink.com Abstract Humans have the ability to perceive 3D shapes from 2D projections of rotating 3D objects, which is called Kinetic Depth Effects. This process is based on a variety of visual cues such as lighting and shading effects. However, when such cues are weakened or missing, perception can become faulty, as demonstrated by the famous silhouette illusion example – the Spinning Dancer. Inspired by this, we establish objective and subjective evaluation models of rotated 3D objects by taking their projected 2D images as input. We investigate five different cues: ambient Fig. 1 The Spinning Dancer. Due to the lack of visual cues, it confuses humans luminance, shading, rotation speed, perspective, and color as to whether rotation is clockwise or counterclockwise. Here we show 3 of 34 difference between the objects and background. In the frames from the original animation [21]. Image courtesy of Nobuyuki Kayahara. objective evaluation model, we first apply 3D reconstruction algorithms to obtain an objective reconstruction quality 1 Introduction metric, and then use a quadratic stepwise regression analysis method to determine the weights among depth cues to The human perception mechanism of the 3D world has represent the reconstruction quality. In the subjective long been studied. -
Capture of Stereopsis and Apparent Motion by Illusory Contours
Perception & Psychophysics 1986, 39 (5), 361-373 Capture of stereopsis and apparent motion by illusory contours V. S. RAMACHANDRAN University of California, San Diego, La Jolla, California The removal of right-angle sectors from four circular black disks created the impression of a white "subjective" square with its four corners occluding the disks ("illusory contours"). The dis play in one eye was identical to that in the other except that for one eye a horizontal disparity was introduced between the edges of the cut sectors so that an illusory white square floated out in front of the paper. When a "template" ofthis stereogram was superimposed on a vertical square wave grating (6 cycles/deg) the illusory square pulled the corresponding lines of grating forward even though the grating was at zero disparity. (Capture was not observed if the template was superimposed on horizontal gratings; the grating remained flush with the background). Analo gous effects were observed in apparent motion ("motion capture"). Removal of sectors from disks in an appropriately timed sequence generated apparent motion of an illusory square. When a template of this display was superimposed on a grating, the lines appeared to move vividly with the square even though they were physically stationary. It was concluded that segmentation of the visual scene into surfaces and objects can profoundly influence the early visual processing of stereopsis and apparent motion. However, there are interesting differences between stereo cap ture and motion capture, which probably reflect differences in natural constraints. The implica tions of these findings for computational models of vision are discussed. -
Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: from Events to Global Motion Perception
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2019 1 Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception Federico Paredes-Valles´ , Kirk Y. W. Scheper , and Guido C. H. E. de Croon , Member, IEEE Abstract—The combination of spiking neural networks and event-based vision sensors holds the potential of highly efficient and high-bandwidth optical flow estimation. This paper presents the first hierarchical spiking architecture in which motion (direction and speed) selectivity emerges in an unsupervised fashion from the raw stimuli generated with an event-based camera. A novel adaptive neuron model and stable spike-timing-dependent plasticity formulation are at the core of this neural network governing its spike-based processing and learning, respectively. After convergence, the neural architecture exhibits the main properties of biological visual motion systems, namely feature extraction and local and global motion perception. Convolutional layers with input synapses characterized by single and multiple transmission delays are employed for feature and local motion perception, respectively; while global motion selectivity emerges in a final fully-connected layer. The proposed solution is validated using synthetic and real event sequences. Along with this paper, we provide the cuSNN library, a framework that enables GPU-accelerated simulations of large-scale spiking neural networks. Source code and samples are available at https://github.com/tudelft/cuSNN. Index Terms—Event-based vision, feature extraction, motion detection, neural nets, neuromorphic computing, unsupervised learning F 1 INTRODUCTION HENEVER an animal endowed with a visual system interconnected cells for motion estimation, among other W navigates through an environment, turns its gaze, or tasks. -
Interacting with Autostereograms
See discussions, stats, and author profiles for this publication at: https://www.researchgate.net/publication/336204498 Interacting with Autostereograms Conference Paper · October 2019 DOI: 10.1145/3338286.3340141 CITATIONS READS 0 39 5 authors, including: William Delamare Pourang Irani Kochi University of Technology University of Manitoba 14 PUBLICATIONS 55 CITATIONS 184 PUBLICATIONS 2,641 CITATIONS SEE PROFILE SEE PROFILE Xiangshi Ren Kochi University of Technology 182 PUBLICATIONS 1,280 CITATIONS SEE PROFILE Some of the authors of this publication are also working on these related projects: Color Perception in Augmented Reality HMDs View project Collaboration Meets Interactive Spaces: A Springer Book View project All content following this page was uploaded by William Delamare on 21 October 2019. The user has requested enhancement of the downloaded file. Interacting with Autostereograms William Delamare∗ Junhyeok Kim Kochi University of Technology University of Waterloo Kochi, Japan Ontario, Canada University of Manitoba University of Manitoba Winnipeg, Canada Winnipeg, Canada [email protected] [email protected] Daichi Harada Pourang Irani Xiangshi Ren Kochi University of Technology University of Manitoba Kochi University of Technology Kochi, Japan Winnipeg, Canada Kochi, Japan [email protected] [email protected] [email protected] Figure 1: Illustrative examples using autostereograms. a) Password input. b) Wearable e-mail notification. c) Private space in collaborative conditions. d) 3D video game. e) Bar gamified special menu. Black elements represent the hidden 3D scene content. ABSTRACT practice. This learning effect transfers across display devices Autostereograms are 2D images that can reveal 3D content (smartphone to desktop screen). when viewed with a specific eye convergence, without using CCS CONCEPTS extra-apparatus. -
Stereopsis and Stereoblindness
Exp. Brain Res. 10, 380-388 (1970) Stereopsis and Stereoblindness WHITMAN RICHARDS Department of Psychology, Massachusetts Institute of Technology, Cambridge (USA) Received December 20, 1969 Summary. Psychophysical tests reveal three classes of wide-field disparity detectors in man, responding respectively to crossed (near), uncrossed (far), and zero disparities. The probability of lacking one of these classes of detectors is about 30% which means that 2.7% of the population possess no wide-field stereopsis in one hemisphere. This small percentage corresponds to the probability of squint among adults, suggesting that fusional mechanisms might be disrupted when stereopsis is absent in one hemisphere. Key Words: Stereopsis -- Squint -- Depth perception -- Visual perception Stereopsis was discovered in 1838, when Wheatstone invented the stereoscope. By presenting separate images to each eye, a three dimensional impression could be obtained from two pictures that differed only in the relative horizontal disparities of the components of the picture. Because the impression of depth from the two combined disparate images is unique and clearly not present when viewing each picture alone, the disparity cue to distance is presumably processed and interpreted by the visual system (Ogle, 1962). This conjecture by the psychophysicists has received recent support from microelectrode recordings, which show that a sizeable portion of the binocular units in the visual cortex of the cat are sensitive to horizontal disparities (Barlow et al., 1967; Pettigrew et al., 1968a). Thus, as expected, there in fact appears to be a physiological basis for stereopsis that involves the analysis of spatially disparate retinal signals from each eye. Without such an analysing mechanism, man would be unable to detect horizontal binocular disparities and would be "stereoblind". -
Relative Importance of Binocular Disparity and Motion Parallax for Depth Estimation: a Computer Vision Approach
remote sensing Article Relative Importance of Binocular Disparity and Motion Parallax for Depth Estimation: A Computer Vision Approach Mostafa Mansour 1,2 , Pavel Davidson 1,* , Oleg Stepanov 2 and Robert Piché 1 1 Faculty of Information Technology and Communication Sciences, Tampere University, 33720 Tampere, Finland 2 Department of Information and Navigation Systems, ITMO University, 197101 St. Petersburg, Russia * Correspondence: pavel.davidson@tuni.fi Received: 4 July 2019; Accepted: 20 August 2019; Published: 23 August 2019 Abstract: Binocular disparity and motion parallax are the most important cues for depth estimation in human and computer vision. Here, we present an experimental study to evaluate the accuracy of these two cues in depth estimation to stationary objects in a static environment. Depth estimation via binocular disparity is most commonly implemented using stereo vision, which uses images from two or more cameras to triangulate and estimate distances. We use a commercial stereo camera mounted on a wheeled robot to create a depth map of the environment. The sequence of images obtained by one of these two cameras as well as the camera motion parameters serve as the input to our motion parallax-based depth estimation algorithm. The measured camera motion parameters include translational and angular velocities. Reference distance to the tracked features is provided by a LiDAR. Overall, our results show that at short distances stereo vision is more accurate, but at large distances the combination of parallax and camera motion provide better depth estimation. Therefore, by combining the two cues, one obtains depth estimation with greater range than is possible using either cue individually. -
Human Visual Motion Perception Shows Hallmarks of Bayesian Structural Inference Sichao Yang1,2,6*, Johannes Bill3,4,6*, Jan Drugowitsch3,5,7 & Samuel J
www.nature.com/scientificreports OPEN Human visual motion perception shows hallmarks of Bayesian structural inference Sichao Yang1,2,6*, Johannes Bill3,4,6*, Jan Drugowitsch3,5,7 & Samuel J. Gershman4,5,7 Motion relations in visual scenes carry an abundance of behaviorally relevant information, but little is known about how humans identify the structure underlying a scene’s motion in the frst place. We studied the computations governing human motion structure identifcation in two psychophysics experiments and found that perception of motion relations showed hallmarks of Bayesian structural inference. At the heart of our research lies a tractable task design that enabled us to reveal the signatures of probabilistic reasoning about latent structure. We found that a choice model based on the task’s Bayesian ideal observer accurately matched many facets of human structural inference, including task performance, perceptual error patterns, single-trial responses, participant-specifc diferences, and subjective decision confdence—especially, when motion scenes were ambiguous and when object motion was hierarchically nested within other moving reference frames. Our work can guide future neuroscience experiments to reveal the neural mechanisms underlying higher-level visual motion perception. Motion relations in visual scenes are a rich source of information for our brains to make sense of our environ- ment. We group coherently fying birds together to form a fock, predict the future trajectory of cars from the trafc fow, and infer our own velocity from a high-dimensional stream of retinal input by decomposing self- motion and object motion in the scene. We refer to these relations between velocities as motion structure. -
Chromostereo.Pdf
ChromoStereoscopic Rendering for Trichromatic Displays Le¨ıla Schemali1;2 Elmar Eisemann3 1Telecom ParisTech CNRS LTCI 2XtremViz 3Delft University of Technology Figure 1: ChromaDepth R glasses act like a prism that disperses incoming light and induces a differing depth perception for different light wavelengths. As most displays are limited to mixing three primaries (RGB), the depth effect can be significantly reduced, when using the usual mapping of depth to hue. Our red to white to blue mapping and shading cues achieve a significant improvement. Abstract The chromostereopsis phenomenom leads to a differing depth per- ception of different color hues, e.g., red is perceived slightly in front of blue. In chromostereoscopic rendering 2D images are produced that encode depth in color. While the natural chromostereopsis of our human visual system is rather low, it can be enhanced via ChromaDepth R glasses, which induce chromatic aberrations in one Figure 2: Chromostereopsis can be due to: (a) longitunal chro- eye by refracting light of different wavelengths differently, hereby matic aberration, focus of blue shifts forward with respect to red, offsetting the projected position slightly in one eye. Although, it or (b) transverse chromatic aberration, blue shifts further toward might seem natural to map depth linearly to hue, which was also the the nasal part of the retina than red. (c) Shift in position leads to a basis of previous solutions, we demonstrate that such a mapping re- depth impression. duces the stereoscopic effect when using standard trichromatic dis- plays or printing systems. We propose an algorithm, which enables an improved stereoscopic experience with reduced artifacts. -
Two Eyes See More Than One Human Beings Have Two Eyes Located About 6 Cm (About 2.4 In.) Apart
ivi act ty 2 TTwowo EyesEyes SeeSee MoreMore ThanThan OneOne OBJECTIVES 1 straw 1 card, index (cut in half widthwise) Students discover how having two eyes helps us see in three dimensions and 3 pennies* increases our field of vision. 1 ruler, metric* The students For the class discover that each eye sees objects from a 1 roll string slightly different viewpoint to give us depth 1 roll tape, masking perception 1 pair scissors* observe that depth perception decreases *provided by the teacher with the use of just one eye measure their field of vision observe that their field of vision decreases PREPARATION with the use of just one eye Session I 1 Make a copy of Activity Sheet 2, Part A, for each student. SCHEDULE 2 Each team of two will need a metric ruler, Session I About 30 minutes three paper cups, and three pennies. Session II About 40 minutes Students will either close or cover their eyes, or you may use blindfolds. (Students should use their own blindfold—a bandanna or long strip VOCABULARY of cloth brought from home and stored in their science journals for use—in this depth perception and other activities.) field of vision peripheral vision Session II 1 Make a copy of Activity Sheet 2, Part B, for each student. MATERIALS 2 For each team, cut a length of string 50 cm (about 20 in.) long. Cut enough index For each student cards in half (widthwise) to give each team 1 Activity Sheet 2, Parts A and B half a card. Snip the corners of the cards to eliminate sharp edges. -
Motion-In-Depth Perception and Prey Capture in the Praying Mantis Sphodromantis Lineola
© 2019. Published by The Company of Biologists Ltd | Journal of Experimental Biology (2019) 222, jeb198614. doi:10.1242/jeb.198614 RESEARCH ARTICLE Motion-in-depth perception and prey capture in the praying mantis Sphodromantis lineola Vivek Nityananda1,*, Coline Joubier1,2, Jerry Tan1, Ghaith Tarawneh1 and Jenny C. A. Read1 ABSTRACT prey as they come near. Just as with depth perception, several cues Perceiving motion-in-depth is essential to detecting approaching could contribute to the perception of motion-in-depth. or receding objects, predators and prey. This can be achieved Two of the motion-in-depth cues that have received the most using several cues, including binocular stereoscopic cues such attention in humans are binocular: changing disparity and as changing disparity and interocular velocity differences, and interocular velocity differences (IOVDs) (Cormack et al., 2017). monocular cues such as looming. Although these have been Stereoscopic disparity refers to the difference in the position of an studied in detail in humans, only looming responses have been well object as seen by the two eyes. This disparity reflects the distance to characterized in insects and we know nothing about the role of an object. Thus as an object approaches, the disparity between the stereoscopic cues and how they might interact with looming cues. We two views changes. This changing disparity cue suffices to create a used our 3D insect cinema in a series of experiments to investigate perception of motion-in-depth for human observers, even in the the role of the stereoscopic cues mentioned above, as well as absence of other cues (Cumming and Parker, 1994). -
From Stereogram to Surface: How the Brain Sees the World in Depth
Spatial Vision, Vol. 22, No. 1, pp. 45–82 (2009) © Koninklijke Brill NV, Leiden, 2009. Also available online - www.brill.nl/sv From stereogram to surface: how the brain sees the world in depth LIANG FANG and STEPHEN GROSSBERG ∗ Department of Cognitive and Neural Systems, Center for Adaptive Systems and Center of Excellence for Learning in Education, Science, and Technology, Boston University, 677 Beacon St., Boston, MA 02215, USA Received 19 April 2007; accepted 31 August 2007 Abstract—When we look at a scene, how do we consciously see surfaces infused with lightness and color at the correct depths? Random-Dot Stereograms (RDS) probe how binocular disparity between the two eyes can generate such conscious surface percepts. Dense RDS do so despite the fact that they include multiple false binocular matches. Sparse stereograms do so even across large contrast-free regions with no binocular matches. Stereograms that define occluding and occluded surfaces lead to surface percepts wherein partially occluded textured surfaces are completed behind occluding textured surfaces at a spatial scale much larger than that of the texture elements themselves. Earlier models suggest how the brain detects binocular disparity, but not how RDS generate conscious percepts of 3D surfaces. This article proposes a neural network model that predicts how the layered circuits of visual cortex generate these 3D surface percepts using interactions between visual boundary and surface representations that obey complementary computational rules. The model clarifies how interactions between layers 4, 3B and 2/3A in V1 and V2 contribute to stereopsis, and proposes how 3D perceptual grouping laws in V2 interact with 3D surface filling-in operations in V1, V2 and V4 to generate 3D surface percepts in which figures are separated from their backgrounds.