Search

We present a novel method for dynamic estimation of pose of multiple people using multiple video cameras. Tracking is performed using a model-based approach and a set of cues which exploit both shape and colour information. For shape we propose a fast line-search method to incorporate multi-view constraints without the computational overhead of a voxel representation. The tracking algorithm is a new hierarchical stochastic sampling scheme. Results are presented using natural movements of up to two people sharing the same capture volume. Tracking is shown to be robust over a range of natural movements, including considerable occlusion. Processing times for tracking two people are at least as short as those for tracking one person using other stochastic schemes. The high performance and efficiency are attributed to the hierarchical search method and the accuracy of the cues in identifying suitable poses.