Dynamic layer representation with applications to tracking

A dynamic layer representation is proposed for tracking moving objects. Previous work on layered representations has largely concentrated on two-/multi-frame batch formulations, and tracking research has not addressed the issue of joint estimation of object motion ownership and appearance. The paper extends the estimation of layers in a dynamic scene to incremental estimation formulation and demonstrates how this naturally solves the tracking problem. The three components of the dynamic layer representation, namely, layer motion, ownership, and appearance, are estimated simultaneously over time in a MAP framework. In order to enforce a global shape constraint and to maintain the layer segmentation over time, a parametric segmentation prior is proposed. The generalized EM algorithm is employed to compute the optimal solution. We show the results on real-time tracking of multiple moving or static objects in a cluttered scene imaged from a moving aerial video camera. The moving objects may do complex motions, and have complex interactions such as passing. By using both the appearance and the segmentation information, many difficult tracking tasks are reliably handled.