Face detection and tracking for intelligent surveillance system

Aiming at rectifying the shortcomings of traditional video surveillance system, an intelligent surveillance system that can automatically detect and track human faces in the scene is presented. Symmetrical frame difference is used to acquire the area of motion and the skin-color segmentation algorithm based on BP neural network is used to extract the face candidates. Then, the candidate face regions are verified with the knowledge of human faces. A recorded face buffer is maintained to track moving faces in the scene. The captured faces and event of interest are used to generate video indexing database. Experimental results show that the intelligent surveillance system can detect and track the faces rapidly and accurately in the scene.