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Multi-and Single View Multiperson Tracking for Smart Room Environments

  • Keni Bernardin
  • Tobias Gehrig
  • Rainer Stiefelhagen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4122)

Abstract

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.

Keywords

Color Histogram Visual Tracker Microphone Array Person Model Mismatch Error 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Keni Bernardin
    • 1
  • Tobias Gehrig
    • 1
  • Rainer Stiefelhagen
    • 1
  1. 1.Interactive Systems Lab, Institut für Theoretische Informatik, Universität Karlsruhe, 76131 KarlsruheGermany

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