Automatic face region tracking for highly accurate face recognition in unconstrained environments

We present a combined real-time face region tracking and highly accurate face recognition technique for an intelligent surveillance system. High-resolution face images are very important to achieving accurate identification of a human face. Conventional surveillance or security systems, however, usually provide poor image quality because they use only fixed cameras to record scenes passively. We have implemented a real-time surveillance system that tracks a moving face using four pan-tilt-zoom (PTZ) cameras. While tracking, the region-of-interest (ROI) can be obtained by using a low-pass filter and background subtraction with the PTZ. Color information in the ROI is updated to extract features for optimal tracking and zooming. FaceIt^®, which is one of the most popular face recognition software packages, is evaluated and then used to recognize the faces from the video signal. Experimentation with real human faces showed highly acceptable results in the sense of both accuracy and computational efficiency.