The invention provides a face detection method based on multiple classifiers, comprising the following steps: selecting positive sample images and negative sample images, and clustering the positive sample images through a K-Means clustering algorithm to get clustered positive sample sets; training the clustered positive sample sets and the negative sample images through a main classifier and sub classifiers by use of a Cascade algorithm to get a trained main classifier and trained sub classifiers; and inputting an image, detecting the input image according to the trained main classifier and the trained sub classifiers, and outputting a detection result. Compared with the prior art, a face can be detected from a complex image, and the detection accuracy is high.