Research Of Face Detection Based On AdaBoost Algorithm

Human face recognition and detection are the most active and challenging tasks for computer vision and pattern recognition. It can be widely applied to such fields as personal identification, human-computer interface, visual communication, criminal archive administration, content-based image retrieval, etc.As the first step of face recognition, the task of face detection is to detect human faces from background of image. However, face detection result is usually affected by the background, brightness or head posture of image and so on, which makes the process of detection more complicated.A great amount of literatures, surveys and research papers concerning up-to-date techniques of face detection and face recognition are read and analyzed. Some hot issues about face detection are discussed and studied in this paper. The experiments indicate that the methods of face detection proposed in this paper are reasonable, showing a certain degree of theoretical and practical value. The research work of this paper mainly includes the following several aspects:1. Using face detection method based on AdaBoost learning algorithm, which selects few key haar-like features from a large set of features, to build a robust cascade classifier. Focusing on the disadvantages of classical AdaBoost algorithm, this paper analyses the issues of overfitting and distortion of sample weights in training process and come up with a new method to avoid the phenomenon of overfitting. The experimental results show that the new method will not lead to overfitting like classical AdaBoost often does, and it will reduce false alarm rate while holding a high detection rate.2.Face detection algorithm based on the model of faces' skin color is carried out by using the skin color information of color image. YCbCr color space in which chrominance and luminance are separated is adopted because of its high suitability to the face detection application comparing with other color spaces. The results show that skin color information plays a practical role in the fast face detection.3. As skin color detection achieves high false acceptance rate in color image...