Multi-camera Tracking and Segmentation of Occluded People on Ground Plane Using Search-Guided Particle Filtering

A multi-view multi-hypothesis approach to segmenting and tracking multiple (possibly occluded) persons on a ground plane is proposed. During tracking, several iterations of segmentation are performed using information from human appearance models and ground plane homography. To more precisely locate the ground location of a person, all center vertical axes of the person across views are mapped to the top-view plane and their intersection point on the ground is estimated. To tackle the explosive state space due to multiple targets and views, iterative segmentation-searching is incorporated into a particle filtering framework. By searching for people’s ground point locations from segmentations, a set of a few good particles can be identified, resulting in low computational cost. In addition, even if all the particles are away from the true ground point, some of them move towards the true one through the iterated process as long as they are located nearby. We demonstrate the performance of the approach on several video sequences.