Automatic detection of abnormal gait on stairs.
Published: 2007
Language: eng
Number of pages: 81
ISBN-13: 9780494272961
Description: This thesis presents a method for automatically detecting unusual human gait on stairs from video data. The motivation is to provide a tool for biomedical researchers to rapidly find the events of interest within large quantities of video data. The system identifies potential sequences containing anomalies, and reduces the amount of data that needs to be searched by a human. Optical flow is computed over a background subtracted silhouette to capture the overall motion of a person descending stairs. The person's feet are tracked using a mixed state particle filter with an appearance model based on histograms of gradient orientations. A hidden Markov model (HMM) is then used to create a statistical model of the temporal progression of features derived from the optical flow and tracked foot positions for normal stair descents. Classification is performed based on the statistical likelihood that a stair descent is normal.
Notes: Source: Masters Abstracts International, Volume: 45-06, page: 3192.

Thesis (M.Sc.)--University of Toronto, 2007.

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