Tracking of individuals in very long video sequences

Authors:
P. Fihl;R. Corlin;S. Park;T. B. Moeslund;M. M. Trivedi
Affiliations:
Laboratory of Computer Vision and Media Technology, Aalborg University, Denmark;Laboratory of Computer Vision and Media Technology, Aalborg University, Denmark;Computer Vision and Robotics Research Laboratory, The University of California, San Diego;Laboratory of Computer Vision and Media Technology, Aalborg University, Denmark;Computer Vision and Robotics Research Laboratory, The University of California, San Diego
Venue:
ISVC'06 Proceedings of the Second international conference on Advances in Visual Computing - Volume Part I
Year:
2006

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Abstract

In this paper we present an approach for automatically detecting and tracking humans in very long video sequences. The detection is based on background subtraction using a multi-mode Codeword method. We enhance this method both in terms of representation and in terms of automatically updating the background allowing for handling gradual and rapid changes. Tracking is conducted by building appearance-based models and matching these over time. Tests show promising detection and tracking results in a ten hour video sequence.