Dynamic Object Tracking by Partial Shape Matching for Video Surveillance Applications

In this paper, we propose an algorithm for object tracking through frames of video using a fast partial shape matching technique. The tracking is divided into two modules: 1) moving object extraction followed by color/edge segmentation, and 2) tracking through frames using partial shape matching. The major challenges of object tracking, such as occlusions, splitting of one object and appearance and disappearance of objects, are effectively resolved. The proposed algorithm is tested on several synthetic and real life video sequences and has proven to be very effective in identifying and tracking moving objects independent of translations, rotations, scale variations and occlusions.