A multi view face detection algorithm based on multi-channel map discriminant projection HAAR feature is proposed. Firstly, the multi-channel map is extracted from the face image by the algorithm, which can reduce the influence of illumination and noise in the image. Secondly, based on the positive and negative training samples, the enhanced HAAR feature is learned by the linear discriminant projection, which can improve the distinguishing ability of the feature. Then the response in multi-channel of the augmented HAAR feature in the training sample is calculated, and the non symmetric GentleBoost algorithm is used to generate a set of weak classifiers. Finally, the weight and threshold of the strong classifier are adjusted by the linear non symmetric classifier. This method not only improves the distinguishing ability of the feature, but also realizes the reasonable division of the non balanced positive and negative sample space.Experimental results show that the proposed method has a faster detection speed and the higher detection accuracy compared with the classical methods.