Automatical face detection in images with complex background

In this paper, we presented a robust coarse-to-fine detection engine. In this engine, the structure based scheme is used to detect all face candidates, while the statistic based scheme to verify the detected candidates. All concave horizontal features (CHFs) are extracted from images under multi-scales and multi-levels to create a list of CHF images at the first stage. At the second stage, the face candidates are detected on the CHF images based on the trigonal relation between the eye pairs and mouths of human faces. The last stage is the face verification, which check out all real faces from the candidates. This robust face detection method is fast, and insensitive to facial poses, facial scales, uneven lighting, and etc. it can challenge any other face detection methods.