Face Detection In Complex Background And Location

Automatic face detection and recognition has been receiving increasing attention from researchers in the fields of image processing and computer vision during the past few years. It has a lot of applications in smart surveillance system, virtual reality, advanced user interface, emotion analysis and model-based coding, etc. Generally speaking, the procedure of the automatic face detection and recognition from images or a sequence of images involves three main stages: (1) face detection and location in a scene; (2) face tracking; (3) face recognition and understanding. As the base of the face detection and recognition, face detection and location is the key of the whole procedure. Face detection in complex backgrounds is the advanced stage of the automatic face detection and location. And it is focus in the recent face detection research. This paper describes two methods of the face detection in complex backgrounds automatically.Algorithm I is based on color information, and constitutes two sections. First, the technique approximately detects the image positions where the probability of finding a face is high; then the location accuracy of the candidate faces is improved and their existence is verified and marked. It can be used to detect many faces with differentsizes and directions ( - 90 - 90) in a color static image.Algorithm II is based on support vector machine and made of training section and detecting section. A lot of face samples and "not face" samples are used to train the SVM classifier, to get optimal separating hyperplane in the training. And SVM classifier is used to detect faces in the detecting. This algorithm can be used to detect many frontal faces with different sizes in a color image or gray image.The paper respectively gives the experimental results of algorithm I and algorithm II, and compares the detection performance of the two algorithms. Experimental results show that algorithm I is better than algorithm II.