Abstract
Visual surveillance, which relies on human motion recognition and people recognition, has received a lot of attention for its use in effective monitoring of public places. However, there is a concern of loss of privacy due to distinguishable facial information. To deal with this issue, we developed a camera system which does riot capture any facial information. In this paper we propose an abnormal-behavior detection method using privacy-protected videos taken by the proposed camera system. In the proposed method, we extract both motion-based and appearance-based features, and we combine these two methods by taking advantages of each of them. We build a database including normal and abnormal behaviors, and we show the effectiveness of the proposed method on cases from the database.
