{"id":{"repo_id":"vt","oai_identifier":"oai:vtechworks.lib.vt.edu:10919/31795"},"canonical_url":"https://search.dev.ndltd.org/etd/vt/oai:vtechworks.lib.vt.edu:10919/31795","repository":{"repo_id":"vt","name":"Virginia Tech","base_url":"https://vtechworks.lib.vt.edu/oai/request"},"display":{"title":"Determination of Normal or Abnormal Gait Using a Two-Dimensional Video Camera","abstract":"The extraction and analysis of human gait characteristics using image sequences and the subsequent classification of these characteristics are currently an intense area of research. Recently, the focus of this research area has turned to the realm of computer vision as an unobtrusive way of performing this analysis. With such systems becoming more common, a gait analysis system that will quickly and accurately determine if a subject is walking normally becomes more valuable. Such a system could be used as a preprocessing step in a more sophisticated gait analysis system or could be used for rehabilitation purposes. In this thesis a system is proposed which utilizes a novel fusion of spatial computer vision operations as well as motion in order to accurately and efficiently determine if a subject moving through a scene is walking normally or abnormally. Specifically this system will yield a classification of the type of motion being observed, whether it is a human walking normally or some other kind of motion taking place within the frame. Experimental results will show that the system provides accurate detection of normal walking and can distinguish abnormalities as subtle as limping or walking with a straight leg reliably.","abstract_html":"The extraction and analysis of human gait characteristics using image sequences and the subsequent classification of these characteristics are currently an intense area of research. Recently, the focus of this research area has turned to the realm of computer vision as an unobtrusive way of performing this analysis. With such systems becoming more common, a gait analysis system that will quickly and accurately determine if a subject is walking normally becomes more valuable. Such a system could be used as a preprocessing step in a more sophisticated gait analysis system or could be used for rehabilitation purposes. In this thesis a system is proposed which utilizes a novel fusion of spatial computer vision operations as well as motion in order to accurately and efficiently determine if a subject moving through a scene is walking normally or abnormally. Specifically this system will yield a classification of the type of motion being observed, whether it is a human walking normally or some other kind of motion taking place within the frame. Experimental results will show that the system provides accurate detection of normal walking and can distinguish abnormalities as subtle as limping or walking with a straight leg reliably.","abstract_has_math":false,"creators":["Smith, Benjamin Andrew"],"institution":"Virginia Tech","degree_name":"Master of Science","degree_level":"masters","degree_discipline":"Mechanical Engineering","degree_department":"Mechanical Engineering","school":null,"contributors":[],"advisors":[],"committee_chairs":["Roach, John W."],"committee_members":["Lockhart, Thurmon E.","Johnson, Martin E."],"year":2007,"date_issued":"2007-04-06","date_published":"2007-04-06","updated_at":"2026-07-22T22:18:39Z","subjects":["Gait","Abnormality Detection","Pattern Recognition","Computer Vision"],"languages":[],"rights":["In Copyright"],"rights_urls":["http://rightsstatements.org/vocab/InC/1.0/"],"identifier_entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-04202007-152929"],"render_values":[{"text":"etd-04202007-152929","href":null,"code":true}]}]},"links":{"outbound_url":"http://hdl.handle.net/10919/31795","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.committeechair","label":"Committee Chair","values":["Roach, John W."]},{"key":"dc:contributor.committeemember","label":"Committee Member","values":["Lockhart, Thurmon E.","Johnson, Martin E."]},{"key":"dc:contributor.department","label":"Department","values":["Mechanical Engineering"]},{"key":"dc:creator","label":"Author","values":["Smith, Benjamin Andrew"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2014-03-14T20:33:57Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2014-03-14T20:33:57Z","2007-06-19"]},{"key":"dc:date.issued","label":"Date","values":["2007-04-06"]},{"key":"dc:publisher","label":"Institution","values":["Virginia Tech"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_discipline","label":"Discipline","values":["Mechanical Engineering"]},{"key":"thesis:degree_level","label":"Degree Level","values":["masters"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science"]},{"key":"thesis:institution_name","label":"Thesis Institution Name","values":["Virginia Polytechnic Institute and State University"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Gait","Abnormality Detection","Pattern Recognition","Computer Vision"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:rights","label":"Dc Rights","values":["In Copyright"]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://rightsstatements.org/vocab/InC/1.0/"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.other","label":"Dc Identifier Other","values":["etd-04202007-152929"]},{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/10919/31795"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["The extraction and analysis of human gait characteristics using image sequences and the subsequent classification of these characteristics are currently an intense area of research. 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