We propose a face detection algorithm for color images in the presence of varying lighting conditions as well as complex backgrounds. Our method detects skin regions over the entire image, and then generates face candidates based on the spatial arrangement of these skin patches. The algorithm constructs eye, mouth, and boundary maps for verifying each face candidate. Experimental results demonstrate successful detection over a wide variety of facial variations in color, position, scale, rotation, pose, and expression from several photo collections. Model-based approaches are widely used in tracking faces and often assume that the initial locations of faces are known.
Skin color provides an important cue for face detection.
However, the color-based approaches face difficulties in robust detection of skin colors in the presence of complex background and variations in lighting conditions. We propose a face detection algorithm which is able to handle a wide variety of variations in color images. Major modules of the algorithm are briefly described below. Face detection algorithm. The appearance of the skin-tone color can change due to different lighting conditions.