Smith, Benjamin Andrew2014-03-142014-03-142007-04-06etd-04202007-152929http://hdl.handle.net/10919/31795The 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.In CopyrightGaitAbnormality DetectionPattern RecognitionComputer VisionThesishttp://scholar.lib.vt.edu/theses/available/etd-04202007-152929/