A border-ownership model based on computational electromagnetism

The mathematical relation between a vector electric field and its corresponding scalar potential field is useful to formulate computational problems of lower/middle-order visual processing, specifically related to the assignment of borders to the side of the object: so-called border ownership (BO). BO coding is a key process for extracting the objects from the background, allowing one to organize a cluttered scene. We propose that the problem is solvable simultaneously by application of a theorem of electromagnetism, i.e., “conservative vector fields have zero rotation, or “curl.” We hypothesize that (i) the BO signal is definable as a vector electric field with arrowheads pointing to the inner side of perceived objects, and (ii) its corresponding scalar field carries information related to perceived order in depth of occluding/occluded objects. A simple model was developed based on this computational theory. Model results qualitatively agree with object-side selectivity of BO-coding neurons, and with perceptions of object order. The model update rule can be reproduced as a plausible neural network that presents new interpretations of existing physiological results. Results of this study also suggest that T-junction detectors are unnecessary to calculate depth order

Cognitive evaluation of computer-drawn sketches

CISRG discussion paper ; 1

A topological solution to object segmentation and tracking

The world is composed of objects, the ground, and the sky. Visual perception of objects requires solving two fundamental challenges: segmenting visual input into discrete units, and tracking identities of these units despite appearance changes due to object deformation, changing perspective, and dynamic occlusion. Current computer vision approaches to segmentation and tracking that approach human performance all require learning, raising the question: can objects be segmented and tracked without learning? Here, we show that the mathematical structure of light rays reflected from environment surfaces yields a natural representation of persistent surfaces, and this surface representation provides a solution to both the segmentation and tracking problems. We describe how to generate this surface representation from continuous visual input, and demonstrate that our approach can segment and invariantly track objects in cluttered synthetic video despite severe appearance changes, without requiring learning.Comment: 21 pages, 6 main figures, 3 supplemental figures, and supplementary material containing mathematical proof

Perception of depth and motion from ambiguous binocular information

AbstractThe visual system can determine motion and depth from ambiguous information contained in images projected onto both retinas over space and time. The key to the way the system overcomes such ambiguity lies in dependency among multiple cues—such as spatial displacement over time, binocular disparity, and interocular time delay—which might be established based on prior knowledge or experience, and stored in spatiotemporal response characteristics of neurons at an early cortical stage. We conducted a psychophysical investigation of whether a single ambiguous cue (specifically, interocular time delay) permits depth discrimination and motion perception. Data from this investigation are consistent with the predictions derived from the response profiles of V1 neurons, which show interdependency in their responses to each cue, indicating that spatial and temporal information is jointly encoded in early vision

On the Functional Significance of the P1 and N1 Effects to Illusory Figures in the Notch Mode of Presentation

The processing of Kanizsa figures have classically been studied by flashing the full “pacmen” inducers at stimulus onset. A recent study, however, has shown that it is advantageous to present illusory figures in the “notch” mode of presentation, that is by leaving the round inducers on screen at all times and by removing the inward-oriented notches delineating the illusory figure at stimulus onset. Indeed, using the notch mode of presentation, novel P1and N1 effects have been found when comparing visual potentials (VEPs) evoked by an illusory figure and the VEPs to a control figure whose onset corresponds to the removal of outward-oriented notches, which prevents their integration into one delineated form. In Experiment 1, we replicated these findings, the illusory figure was found to evoke a larger P1 and a smaller N1 than its control. In Experiment 2, real grey squares were placed over the notches so that one condition, that with inward-oriented notches, shows a large central grey square and the other condition, that with outward-oriented notches, shows four unconnected smaller grey squares. In response to these “real” figures, no P1 effect was found but a N1 effect comparable to the one obtained with illusory figures was observed. Taken together, these results suggest that the P1 effect observed with illusory figures is likely specific to the processing of the illusory features of the figures. Conversely, the fact that the N1 effect was also obtained with real figures indicates that this effect may be due to more global processes related to depth segmentation or surface/object perception

Kinetic occlusion

Thesis (Elec. E.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1995.Includes bibliographical references (leaves 58-66).by Sourabh Arun Niyogi.Elec.E

Predicting Illusory Contours Without Extracting Special Image Features

Boundary completion is one of the desired properties of a robust object boundary detection model, since in real-word images the object boundaries are commonly not fully and clearly seen. An extreme example of boundary completion occurs in images with illusory contours, where the visual system completes boundaries in locations without intensity gradient. Most illusory contour models extract special image features, such as L and T junctions, while the task is known to be a difficult issue in real-world images. The proposed model uses a functional optimization approach, in which a cost value is assigned to any boundary arrangement to find the arrangement with minimal cost. The functional accounts for basic object properties, such as alignment with the image, object boundary continuity, and boundary simplicity. The encoding of these properties in the functional does not require special features extraction, since the alignment with the image only requires extraction of the image edges. The boundary arrangement is represented by a border ownership map, holding object boundary segments in discrete locations and directions. The model finds multiple possible image interpretations, which are ranked according to the probability that they are supposed to be perceived. This is achieved by using a novel approach to represent the different image interpretations by multiple functional local minima. The model is successfully applied to objects with real and illusory contours. In the case of Kanizsa illusion the model predicts both illusory and real (pacman) image interpretations. The model is a proof of concept and is currently restricted to synthetic gray-scale images with solid regions

Perceptual organization and consciousness

With chapter written by leading researchers in the field, this is the state-of-the-art reference work on this topic, and will be so for many years to come

The development of contour processing : evidence from physiology and psychophysics

Object perception and pattern vision depend fundamentally upon the extraction of contours from the visual environment. In adulthood, contour or edge-level processing is supported by the Gestalt heuristics of proximity, collinearity, and closure. Less is known, however, about the developmental trajectory of contour detection and contour integration. Within the physiology of the visual system, long-range horizontal connections in V1 and V2 are the likely candidates for implementing these heuristics. While post-mortem anatomical studies of human infants suggest that horizontal interconnections reach maturity by the second year of life, psychophysical research with infants and children suggests a considerably more protracted development. In the present review, data from infancy to adulthood will be discussed in order to track the development of contour detection and integration. The goal of this review is thus to integrate the development of contour detection and integration with research regarding the development of underlying neural circuitry.We conclude that the ontogeny of this system is best characterized as a developmentally extended period of associative acquisition whereby horizontal connectivity becomes functional over longer and longer distances, thus becoming able to effectively integrate over greater spans of visual space. Keywords

The development of contour processing: evidence from physiology and psychophysics

Object perception and pattern vision depend fundamentally upon the extraction of contours from the visual environment. In adulthood, contour or edge-level processing is supported by the Gestalt heuristics of proximity, collinearity, and closure. Less is known, however, about the developmental trajectory of contour detection and contour integration. Within the physiology of the visual system, long-range horizontal connections in V1 and V2 are the likely candidates for implementing these heuristics. While post-mortem anatomical studies of human infants suggest that horizontal interconnections reach maturity by the second year of life, psychophysical research with infants and children suggests a considerably more protracted development. In the present review, data from infancy to adulthood will be discussed in order to track the development of contour detection and integration. The goal of this review is thus to integrate the development of contour detection and integration with research regarding the development of underlying neural circuitry. We conclude that the ontogeny of this system is best characterized as a developmentally extended period of associative acquisition whereby horizontal connectivity becomes functional over longer and longer distances, thus becoming able to effectively integrate over greater spans of visual space