Face Tracking In Non-Head And Shoulder Image Sequence

Automatic face detection and tracking is an important and front-line subject in computer vision domain. In this paper, we have made a deep study on the face detection and tracking in the non-head and shoulder image sequence. According to the characteristic of non-head and shoulder image sequence, we present an approach that the face detection is based on the object detection and tracking. This approach relates to the fields of object detection object tracking and face detection, which is proved effective. Though using the method of both multi-frame difference and backgroud estimation to sequence images, the detection result is acquired. Then the Kalman filter is used to predict the moving object. Combined with the improved SSDA match method, we can track the moving object exactly on real time. We detect face in the part of the tracked body image. The face-template match is used to get the probably face area. Then after doing harr-wavelet transformation to the probably face area, we use support vector machine to distinguish face accurately. All the programs for testing are written in Visual C++.