A trainable system for face detection in unconstrained environments

This paper describes a monitoring system that implements real-time face detection. 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 a feature selection procedure. Following face detection, a Kalman tracking on the face region allows us to optimize 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.