Multi- and Single View Multiperson Tracking for Smart Room Environments

摘要

Simultaneous tracking of multiple persons in real world environments is an active research field and several approaches have been proposed, based on a variety of features and algorithms. In this work, we present 2 multimodal systems for tracking multiple users in a smart room environment. One is a multi-view tracker based on color histogram tracking and special person region detectors. The other is a wide angle overhead view person tracker relying on foreground segmentation and model-based tracking. Both systems are completed by a joint probabilistic data association filter-based source localization framework using input from several microphone arrays.We also very briefly present two intuitive metrics to allow for objective comparison of tracker characteristics, focusing on their precision in estimating object locations, their accuracy in recognizing object configurations and their ability to consistently label objects over time. The trackers are extensively tested and compared, for each modality separately, and for the combined modalities, on the CLEAR 2006 Evaluation Database.