This paper proposed a face detection algorithm combined skin color segmentation with AdaBoost algorithm. The method utilizes clustering characteristic of skin color and builds Gaussian color model in the YCbCr color space, screening the skin color regions by morphological processing. Then the AdaBoost algorithm is used to train the weak classifier and a strong classifier is formed. The strong classifier is combined to form a cascade classifier and the candidate regions can be detected by AdaBoost cascade classifier, nonface regions in skin color regions can be excluded and then the correct detection of different angles of the faces is achieved. This method can solve the problem of high false detection rate of skin color segmentation with complex background color images and the problem of low detection rate of multipose images based on the method of AdaBoost algorithm. Simulation experiments show that this method has high detection rate, low false detection rate, good adaptability and strong robustness. It has better detection effect for multipose and multiface images and the images of the complex background information, and the practicability is enhanced.