Multi-camera calibration, object tracking and query generation

  • Authors:
  • F. Porikli;A. Divakaran

  • Affiliations:
  • Mitsubishi Electr. Res. Labs, Cambridge, MA, USA;Mitsubishi Electr. Res. Labs, Cambridge, MA, USA

  • Venue:
  • ICME '03 Proceedings of the 2003 International Conference on Multimedia and Expo - Volume 2
  • Year:
  • 2003

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Abstract

An automatic object tracking and video summarization method for multi-camera systems with a large number of non-overlapping field-of-view cameras is explained. In this framework, video sequences are stored for each object as opposed to storing a sequence for each camera. Object-based representation enables annotation of video segments, and extraction of content semantics for further analysis. We also present a novel solution to the inter-camera color calibration problem. The transitive model function enables effective compensation for lighting changes and radiometric distortions for large-scale systems. After initial calibration, objects are tracked at each camera by background subtraction and mean-shift analysis. The correspondence of objects between different cameras is established by using a Bayesian belief network. This framework empowers the user to get a concise response to queries such as "which locations did an object visit on Monday and what did it do there?".