An edge-based face detection algorithm robust against illumination, focus, and scale variations

Abstract

A face detection algorithm very robust against illumination, focus and scale variations in input images has been developed based on the edge-based image representation. The multiple-clue face detection algorithm developed in our previous work has been employed in conjunction with a new decision criterion called “density rule,” where only high density clusters of detected face candidates are retained as faces. As a result, the occurrence of false negatives has been greatly reduced. The robustness of the algorithm against circumstance variations has been demonstrated.