Multi-stage fusion for face localization

We present a new method dedicated to the localization of faces in color images. It combines a connexionist model (auto-associative network), an ellipse model based on Generalized Hough Transform, a skin color model and an eyes detector that results in two features. A linear combination of the 3 first models is performed to eliminate most of non face regions. A connexionist combination of the four detectors response is performed on the remaining candidates. Given an input image, we compute a kind of probability map on it with a sliding window. The face position is then determined as the location of the absolute maximum over this map. Improvement of baseline detectors localization rates is clearly shown and results are very encouraging.