Dynamic Head Location and Pose from Video

In this paper we present a visual particle filter for jointly tracking the position of a person and her head orientation. The resulting information may be used to support automatic analysis of interactive people behaviour, by supporting proxemics analysis and providing dynamic information on focus of attention. An orientation-sensitive visual likelihood is proposed which models the appearance of the target on a key-view basis, and uses body part color histograms as descriptors. The resulting system is able to provide reliable, real time estimates of people position and orientation, with a scalable number of sensors. It is then possible to adaptively allocate computational resources and sensors to increase people monitoring coverage or tracking accuracy. The integration of multi-view sensing, the joint estimation of location and orientation, the use of generative image models, and of simple visual matching measures, make the system robust to low image resolution and sensors failure.