Collaborative Gesture Analysis in Multi-Camera Networks

An architecture for opportunistic discovery of gesture elements for analysis of human gestures in a multi-camera sensor network is presented in this paper. The proposed approach is motivated by the diversity of gestures expressed in passive monitoring applications, and 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. By reducing the uncertainty through different levels of collaboration, the proposed opportunistic approach offers the potential to address gesture recognition problems more efficiently and accurately. Details of the description-layered and processing-layered architecture for collaborative gesture analysis and some illustrating examples are presented.