1. A face detector training method implemented by a computer having a processor, the method comprising: performing, by the processor, a training process by: collecting face and non-face images as a training image sample set; extracting a flexible block based local binary pattern (FBLBP) feature of the face and non-face images to form an FBLBP feature set; and using the FBLBP feature and a GentleBoost algorithm to perform training, to obtain a first classifier, wherein the first classifier comprises several optimal second classifiers, and wherein each optimal second classifier is obtained by training using the GentleBoost algorithm; repeating, by the processor, the training process to obtain multiple layers of first classifiers; and cascading, by the processor, the multiple layers of first classifiers to form a face detector.