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Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06)
Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images
University of Southampton,UK
April 10-April 12
ISBN: 0-7695-2503-2
Joachim Schmidt, Bielefeld University, Germany
Jannik Fritsch, Bielefeld University, Germany
Bogdan Kwolek, Rzeszow University of Technology, Poland
This paper presents the application of a kernel particle filter for 3D body tracking in a video stream acquired from a single uncalibrated camera. Using intensity-based and color-based cues as well as an articulated 3D body model with shape represented by cylinders, a real-time body tracking in monocular cluttered image sequences has been realized. The algorithm runs at 7.5 Hz on a laptop computer and tracks the upper body of a human with two arms. First experimental results show that the proposed approach has good tracking as well as recovering capabilities despite using a small number of particles. The approach is intended for use on a mobile robot to improve human robot interaction.
Citation:
Joachim Schmidt, Jannik Fritsch, Bogdan Kwolek, "Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images," fg, pp.567-572, Seventh IEEE International Conference on Automatic Face and Gesture Recognition (FG'06), 2006
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