5 March 2014 Template matching based people tracking using a smart camera network
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Abstract
In this paper, we proposes a people tracking system composed of multiple calibrated smart cameras and one fusion server which fuses the information from all cameras. Each smart camera estimates the ground plane positions of people based on the current frame and feedback from the server from the previous time. Correlation coefficient based template matching, which is invariant to illumination changes, is proposed to estimate the position of people in each smart camera. Only the estimated position and the corresponding correlation coefficient are sent to the server. This minimal amount of information exchange makes the system highly scalable with the number of cameras. The paper focuses on creating and updating a good template for the tracked person using feedback from the server. Additionally, a static background image of the empty room is used to improve the results of template matching. We evaluated the performance of the tracker in scenarios where persons are often occluded by other persons or furniture, and illumination changes occur frequently e.g., due to switching the light on or off. For two sequences (one minute for each, one with table in the room, one without table) with frequent illumination changes, the proposed tracker never lose track of the persons. We compare the performance of our tracking system to a state-of-the-art tracking system. Our approach outperforms it in terms of tracking accuracy and people loss.
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Junzhi Guan, Peter Van Hese, Jorge Oswaldo Niño-Castañeda, Nyan Bo Bo, Sebastian Gruenwedel, Dirk Van Haerenborgh, Dimitri Van Cauwelaert, Peter Veelaert, Wilfried Philips, "Template matching based people tracking using a smart camera network", Proc. SPIE 9026, Video Surveillance and Transportation Imaging Applications 2014, 90260Y (5 March 2014); doi: 10.1117/12.2036745; https://doi.org/10.1117/12.2036745
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