3D head tracking for fall detection using a single calibrated camera

Authors:
Caroline Rougier;Jean Meunier;Alain St-Arnaud;Jacqueline Rousseau
Affiliations:
Department of Computer Science and Operations Research (DIRO), University of Montreal, QC, Canada;Department of Computer Science and Operations Research (DIRO), University of Montreal, QC, Canada;Health and Social Service Center Lucille-Teasdale, Montreal, QC, Canada;Research Center of the Geriatric Institute, University of Montreal, QC, Canada
Venue:
Image and Vision Computing
Year:
2013

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Abstract

The head trajectory is an interesting source of information for behavior recognition and can be very useful for video surveillance applications, especially for fall detection. Consequently, much work has been done to track the head in the 2D image plane using a single camera or in a 3D world using multiple cameras. Tracking the head in real-time with a single camera could be very useful for fall detection. Thus, in this article, an original method to extract the 3D head trajectory of a person in a room is proposed using only one calibrated camera. The head is represented as a 3D ellipsoid, which is tracked with a hierarchical particle filter based on color histograms and shape information. Experiments demonstrated that this method can run in quasi-real-time, providing reasonable 3D errors for a monocular system. Results on fall detection using the head 3D vertical velocity or height obtained from the 3D trajectory are also presented.