TRACKING MULTI-TARGETS WITH UNIFIED HANDLING OF VIDEO

Data association is an essential component of the human detection and tracking system. The majority of the existing methods, such as Bi-partite matching and GMCP methods are incorporated the limited-temporal-locality of the sequence into data association problem. GMCP tracker is considered as an important complete representation of the tracking problem, where all pair wise relationships between the detections in temporal span of a video is considered and makes the input to the data association as a complete Bi-partite graph. In Bi-partite graph a track of a person will form a clique (a subgraph in which all the nodes are connected to each other). A cost is assigned to each clique and it maximizes the score function, which is selected as the best clique (track), but it is sub-optimal. GMCP tracker does not follow the joint optimization for all the tracks simultaneously and finds the tracks one by one which makes difficulties caused by cluttered background, and crowded scenes to detect and tracking Tracking-by-detection methods are used to track multiple targets with unified handling of complex scenarios, where current detection responses are linked to the previous trajectories. By adding the standard Hungarian algorithm, dummy nodes to each trajectory to allow nodes to temporally disappear and solve the data association implicitly in a global manner even though it is formulated between two consecutive frames. If a trajectory fails to find its matching detection, it is linked to its corresponding dummy nodes until its emergence of matching detection. The source nodes are also incorporated into the account of new targets. The dummy nodes tend to accumulate in fake or disappeared trajectories while they occasionally appear in real trajectories and improve detection inevitable failures, which include the miss detection, the false detection and the occlusion, where an object is partially or fully invisible because of the limited camera view. Extended hybrid Hungarian algorithm is relatively better when compared with GMCP and Hybrid Hungarian algorithm in accuracy. Experiments show that the proposed method makes significant improvement in tracking and detection of different length of videos, specifically with short length videos.