Real time head tracking via camera saccade and shape-fitting

Authors:
Jason Z. Zhang;Ye Lu;Q. M. Jonathan Wu
Affiliations:
Micro-technology and Sensing Group, Institute for Fuel Cell Innovation, National Research Council of Canada, Vancouver, B.C., Canada;Vision and Media Laboratory, School of Computing Science, Simon Fraser University, Burnaby, B.C., Canada;Department of Electrical and Computer Engineering, University of Windsor, Ontario, Canada
Venue:
ICIAR'05 Proceedings of the Second international conference on Image Analysis and Recognition
Year:
2005

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Abstract

This paper presents a system that tracks human heads in real-time under unconstrained environments where target occlusion, varying illumination, and cluttered backgrounds exist. Tracking is formulated as an active visual servo problem based on the integration of a saccade and a smooth pursuit processes. The head is modelled as an ellipse computed from the color clusters of candidate targets using a robust least square ellipse fitting algorithm. The Farnsworth Perceptually Uniform Color Model is employed to represent the color information of the visual objects. Kalman filtering is applied to the head ellipse to track the evolution of the position, size, and orientation of the target such that the occlusion of objects with similar color and shape as those of the target are effectively accommodated. Experiments with tracking scenarios demonstrate the effectiveness of the system.