Oscillatory binocular system and temporal segmentation of stereoscopic depth surfaces.
A dynamical neural network model of binocular stereopsis is proposed to solve the problem of segmentation which remains ambiguous even when the problem of binocular correspondence is solved. Being compatible with the recent neurophysiological findings (Engel et al. 1991), the model assumes that neural cells show oscillatory activities and that segmentation into a coherent depth surface is coded by synchronization of activities. Employing appropriate constraints for segmentation, the present model shows proper segmentation of depth surfaces and also solves segmentational ambiguity caused by a gap. It is newly shown that binocularly-unmatched monocular cells are discriminated in temporal segmentation of monocular cells caused by recurrent interactions between monocular and binocular cells. Integrative interactions with the other visual components through temporal segmentation are also discussed.
Murata
T
T
Faculty of Pharmaceutical Sciences, University of Tokyo, Japan.
Shimizu
H
H
D003198:Computer Simulation; D003491:Cybernetics; D003867:Depth Perception / Q000502:physiology*; D006801:Humans; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology; D009991:Oscillometry