Face Detection And Face Tracking Combined With Hair Color

Face detection and face tracking are the foundational and key technologies in the field of facial analysis, and are applied in many fields, such as video surveillance, human computer interaction, biometrics, content based image retrieval and image coding, etc. In this paper, face detection in color images and face tracking in video sequences are studied with the main work including the following two parts:1. The two typical algorithms for face detection are given, which are the color-based face detection algorithm and AdaBoost face detection algorithm. Besides, the hair color information is also considered to further enhance the detection performance. For the face detection in static image, the face and hair color model for verification are used to reduce the error detection rate of the AdaBoost face detection algorithm.2. For face tracking in video sequences, the Mean Shift tracking algorithm is investigated in detail. An improved CamShift algorithm based on Mean-Shift is introduced. By using the color histogram as the tracking clues, face tracking can be performed more rapidly and accurately. Then after adding hair color model to test and verify the tracking results, the sudden change of the tracking window can be effectively prevented and the performance is improved too. Finally on the application environment based on VS2008, the experimental system of the automatic single-face detection and tracking is developed. The experimental system uses a Brickcom IP camera to make a real-time video image.