People location and orientation tracking in multiple views

This paper presents a multi-view approach to the tracking of people location and orientation. To achieve efficient and accurate likelihood evaluation, a novel likelihood computation method is proposed. Mixtures of Gaussian (MoG) are used to represent the color models of subjects. The scaled unscented transformation is used to project the MoG color models onto the image plane to predict the color distribution for a motion sample. The efficacy of the proposed approach is demonstrated by experiment results obtained using real videos.