Continuously tracking objects across multiple widely separated cameras

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. © Springer-Verlag Berlin Heidelberg 2007.