Continuously tracking objects across multiple widely separated cameras

Authors:
Yinghao Cai;Wei Chen;Kaiqi Huang;Tieniu Tan
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Year:
2007

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Abstract

In this paper, we present a new solution to the problem of multi-camera tracking with non-overlapping fields of view. The identities of moving objects are maintained when they are traveling from one camera to another. Appearance information and spatio-temporal information are explored and combined in a maximum a posteriori (MAP) framework. In computing appearance probability, a two-layered histogram representation is proposed to incorporate spatial information of objects. Diffusion distance is employed to histogram matching to compensate for illumination changes and camera distortions. In deriving spatio-temporal probability, transition time distribution between each pair of entry zone and exit zone is modeled as a mixture of Gaussian distributions. Experimental results demonstrate the effectiveness of the proposed method.