{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/22874"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/22874","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Dynamical systems approach to binocular stereopsis","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.","abstract_html":"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.","abstract_has_math":false,"creators":["Altman, Edward James"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Electrical and Computer Engineering","degree_department":null,"school":null,"contributors":["Ahuja, Narendra"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011-05-07T13:54:22Z","date_published":"2011-05-07T13:54:22Z","updated_at":"2026-07-22T22:25:20Z","subjects":["Engineering, Electronics and Electrical","Artificial Intelligence"],"languages":["eng"],"rights":["Copyright 1990 Altman, Edward James"],"rights_urls":[],"identifier_entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9114160","(UMI)AAI9114160"],"render_values":[{"text":"AAI9114160","href":null,"code":true},{"text":"(UMI)AAI9114160","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/2142/22874","outbound_label":"Handle","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Ahuja, Narendra"]},{"key":"dc:creator","label":"Author","values":["Altman, Edward James"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2011-05-07T13:54:22Z","10000-01-01","1990"]},{"key":"dc:type","label":"Dc Type","values":["text"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Electrical and Computer Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Dissertation"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Ph.D."]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["University of Illinois at Urbana-Champaign"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Engineering, Electronics and Electrical","Artificial Intelligence"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["Copyright 1990 Altman, Edward James"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["AAI9114160","(UMI)AAI9114160","http://hdl.handle.net/2142/22874"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["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.","Made available in DSpace on 2011-05-07T13:54:22Z (GMT). No. of bitstreams: 2 license.txt: 4922 bytes, checksum: 910b249b4beec47e7ab768910c8f966f (MD5) 9114160.pdf: 9661350 bytes, checksum: f962f2804a2e71d27f6f1e14453afaca (MD5) Previous issue date: 1990","Item marked as restricted to the 'UIUC Users [automated]' Group (id=2) by Howard Ding (hding2@illinois.edu) on 2011-05-07T15:00:36Z Item is restricted indefinitely.","Restriction data tranferred 2014-07-01T11:28:41-05:00 Original Data Group with Access UIUC Users [automated] Release Date: none Reason: ETDs are only available to UIUC Users without author permission","ETDs are only available to UIUC Users without author permission","U of I Only"]},{"key":"dc:title","label":"Title","values":["Dynamical systems approach to binocular stereopsis"]}]}],"canonical_facts":{"dc:contributor":["Ahuja, Narendra"],"dc:creator":["Altman, Edward James"],"dc:date":["2011-05-07T13:54:22Z","10000-01-01","1990"],"dc:description":["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.","Made available in DSpace on 2011-05-07T13:54:22Z (GMT). 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