Multi-Camera Calibration, Object Tracking and Query Generation
| Citation: |
Porikli, F.M.; Divakaran, A., "Multi-Camera Calibration, Object Tracking and Query Generation", IEEE International Conference on Multimedia and Expo (ICME), Vol. 1, pp. 653-656, July 2003 (IEEE Xplore) |
| MERL Report: | TR2003-100 |
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. Objectbased 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?
