A new algorithm for small object tracking based on super-resolution technique

Object tracking in a video is a problem of estimating the trajectory of an object in the image plane as it moves around a scene. In general, object tracking is a quite complicated problem. Difficulties in object tracking occur due to some constraints or conditions such as object motion, changing appearance patterns, non-rigid object structures, occlusions, and camera motion. Level of problems would be higher if the object tracking has relatively small. If it happens, an object will be difficult to identify and tracking becomes less precision because small object has little information. In order to overcome these problem, the tracking will be integrated with super-resolution where a high-resolution image will be built from several low-resolution image. In this research, tracking of moving object using adaptive particle filter which adaptive motion model is applied to get better proposal distribution approach. The simulation shows that tracking integration with super-resolution significantly increase the accuracy of small object tracking.