Wheelchair-user Detection Combined with Parts-based Tracking

In recent years, there has been an increasing demand for automatic wheelchair-user detection from a surveillance video to support wheelchair users. However, it is difficult to detect them due to occlusions by surrounding pedestrians in a crowded scene. In this paper, we propose a detection method of wheelchair users robust to such occlusions. Concretely, in case the detector cannot a detect wheelchair user, the proposed method estimates his/her location by parts-based tracking based on parts relationship through time. This makes it possible to detect occluded wheelchair users even though he/she is heavily occluded. As a result of an experiment, the detection of wheelchair users with the proposed method achieved the highest accuracy in crowded scenes, compared with comparative methods.