Shape-Regulated Particle Filtering for Tracking Non-Rigid Objects

This paper presents an active contour based algorithm for tracking non-rigid objects in heavily cluttered scenes. We decompose the non-rigid contour tracking problem into three subproblems: 2D motion estimation, deformation detection, and shape regulation. First, we employ a particle filter to estimate the affine transform parameters between successive frames. Second, by using a dynamic object model, we generate a probabilistic map of deformation to reshape its contour. Finally, we project the updated model onto a trained shape subspace to constrain deformations to be within possible object appearances. Our experiments show that the proposed algorithm significantly improves the performance of the tracker.