A system for face detection and tracking in unconstrained environments

We describe a trainable system for face detection and tracking. The structure of the system is based on multiple cues that discard non face areas as soon as possible: we combine motion, skin, and face detection. The latter is the core of our system and consists of a hierarchy of small SVM classifiers built on the output of an automatic feature selection procedure. Our feature selection is entirely data-driven and allows us to obtain powerful descriptions from a relatively small set of data. Finally, a Kalman tracking on the face region optimizes detection results over time. We present an experimental analysis of the face detection module and results obtained with the whole system on the specific task of counting people entering the scene.