A multi-sensor validation approach for human activity monitoring

In this paper, we present a sensor validation approach for human activity monitoring. The sensor validation indicator is used for controlling the tracking process by a reactive strategy. The validation is represented by a confidence associated to each current tracked object and for each sensor and integrates static and dynamic contextual information. This confidence value is estimated by a Bayesian Network, which combines a set of heterogeneous information. The validation indicator takes into account the notion of geometrical visibility and the size of the detected object. We have tested this sensor validation approach in an indoor environment by using two complementary sensors for human activity monitoring. The first sensor is an industrial stereo camera (Triclops) and the second is a laser scanner (Sick LMS).