A fast approach for person detection and tracking
Ahmed Ali, Kenji Terada · International Journal of Computer Applications in Technology · 2012
Object detection and tracking is one of the most popular areas of video processing and the essential requirement of any surveillance system. A fast approach for person detection and tracking is presented. This work proposes to do target tracking with Kalman filter. In case of a misdetection, which would lead a wrong update of the filter, a fast mean shift iteration based on integral computation is performed to propose a more accurate detection. Tracking results are demonstrated for complex scenes and evaluation of the proposed tracking approach is presented.