Color-Based Face Detection Using Skin Locus Model and Hierarchical Filtering

This paper introduces a new architecture for face detection in color images. Based on skin locus and successive detectors, the method allows high efficiency under drastically varying illumination conditions. While most color-based approaches work only if the camera was calibrated and detect faces if the features (eyes, mouth, eyebrows...) are visible and detectable, our system detects faces even when these features are not well defined. The detection is based on a robust modeling of skin color, called skin locus, which is used to extract the skin-like regions. After orientation normalization and based on verifying a set of criteria (face symmetry, presence of some facial features, variance of pixel intensities and connected component arrangement), only facial regions are selected. We show that our system can detect faces and deal with different conditions (size, orientation, illumination, and complex background).