Detecting and tracking body parts of multiple people
Ediz Polat, Mohammed Yeasin, R. Sharrna · 2002
Tracking of people and their body parts has found application in image processing and computer vision. This paper describes a framework for tracking body parts (eg, hands and face) of multiple people in image sequences. We use a probabilistic model to fuse color and motion information to localize the body parts and employ the multiple hypothesis tracking (MHT) algorithm to track these features simultaneously. We incorporate a path coherence function along with MHT to reduce the negative effects of spurious measurements that produce unconvincing tracks and needless computations. The performance of the framework is validated using experiments on synthetic and real sequences of images.