High performance multi-camera tracking using shapes-from-silhouettes and occlusion removal

Reliable indoor tracking of objects and persons is still a major challenge in computer vision. As GPS is unavailable indoors, other methods have to be used. Multi-camera systems using colour cameras is one approach to tackle this problem. In this paper we will present a method based on shapes-from-silhouettes where the foreground/background segmentation videos are produced with state of the art methods. We will show that our tracker outperforms all the other trackers we evaluated and obtains an accuracy of 97.89% within 50 cm from the ground truth position on the proposed dataset.