Layered and Collaborative Gesture Analysis in Multi-Camera Networks

A layered and collaborative architecture for gesture recognition in a multi-camera network is presented in this paper. The proposed approach is motivated by the diversity of gestures expressed in passive monitoring applications. It is based on the concept of opportunistic fusion of simple features within a single camera and active collaboration between multiple cameras in the decision making process. The decision process is pursued through mutual, assisted, and self correspondences, using features available at different cameras. The dynamics employed by the opportunistic fusion of different features within a single camera as well as those from multiple cameras offer the potential to address gesture recognition problems more efficiently and accurately across a variety of different applications.