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Title:Dynamical systems approach to binocular stereopsis
Author(s):Altman, Edward James
Doctoral Committee Chair(s):Ahuja, Narendra
Department / Program:Electrical and Computer Engineering
Discipline:Electrical and Computer Engineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Engineering, Electronics and Electrical
Artificial Intelligence
Abstract:The extraction of depth in binocular stereopsis relies upon the ability to detect the co-occurrence of similar features in a stereo pair of images and the subsequent extraction of positional disparity. The fundamental problem of stereopsis is to achieve coordinated activity through the linkage of co-occurring features. This thesis investigates a model for stereopsis in which the linkage of features is achieved by interactions among low-order dynamical systems serving as feature detectors. In this model, a dynamical system is an ensemble of nonlinear oscillators associated with an image location. The initial state of each oscillator is determined by the gray-level context of the image location. Distinct features can be identified through the convergence of the dynamical system to a stable mode of coherent oscillations. The recovery of binocular disparity is achieved by the interactions between two such dynamical systems associated with corresponding epipolar lines in the two images.
The dynamical systems examined in this thesis have multiple stable states, which can be used for pattern classification and exhibit behavior similar to that of neural networks. Our approach differs from that of neural networks in that the stable states of the system are characterized by limit cycle oscillations rather than stable fixed points. In the course of this thesis, it is shown that the nonlinearities of the dynamical systems play a key role in maintaining coherent oscillations among the coupled elements, as well as establishing stable interactions between dynamical systems responding to the co-occurrence of similar features in the stereo pair of images.
Issue Date:1990
Rights Information:Copyright 1990 Altman, Edward James
Date Available in IDEALS:2011-05-07
Identifier in Online Catalog:AAI9114160
OCLC Identifier:(UMI)AAI9114160

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