A fast approach for detecting human faces in a complex background

Human face detection is an important capability with a wide range of applications, such as human face recognition, surveillance systems, human-computer interfacing, video-conferencing, etc. In most such applications, the existence of human faces and their corresponding locations must be found. In other words, a reliable and fast method for detecting and locating face regions is of practical importance. In this paper, possible face region candidates in an image with a complex background are identified by means of the valley features on the eyes. These valley features are considered to belong to the eyes of a human face if they satisfy the local properties of the eyes. A pair of these features is matched if their Gabor features are similar; a face region is then formed. Each of the face region candidates is then further verified by matching it to a human face template, and by measuring its symmetry. Experiments show that this approach is fast and reliable