Wireless Video Surveillance System Based on Incremental Learning Face Detection

As an important supplement to wired video in video surveillance applications, wireless video has taken increasing attentions and has been extensively applied into projects like “Safe City”. Despite of in taxis, buses, emergency command vehicles, or temporary monitory point, there will definitely produce massive surveillance videos. In order to retrieve and browse these videos in an efficient way, key video browsing system and technique based on face detection is accepted and put into promotion. Face detection is widely studied and used in many practical applications; however, because of the distinct features of different factors in experiments and applications, such as orientation, pose, illumination, etc., challenges usually obstruct the practical usage. To perform successful application in wireless video browsing system, this paper proposes an incremental learned face detection method based on auto-captured samples. Experiments demonstrate that our proposed incremental learning algorithm has favorable face detection performance and can work in the proposed system.