Principal axis-based correspondence between multiple cameras for people tracking
- 21 February 2006
- journal article
- research article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in Ieee Transactions On Pattern Analysis and Machine Intelligence
- Vol. 28 (4), 663-671
- https://doi.org/10.1109/tpami.2006.80
Abstract
Visual surveillance using multiple cameras has attracted increasing interest in recent years. Correspondence between multiple cameras is one of the most important and basic problems which visual surveillance using multiple cameras brings. In this paper, we propose a simple and robust method, based on principal axes of people, to match people across multiple cameras. The correspondence likelihood reflecting the similarity of pairs of principal axes of people is constructed according to the relationship between "ground-points" of people detected in each camera view and the intersections of principal axes detected in different camera views and transformed to the same view. Our method has the following desirable properties; 1) camera calibration is not needed; 2) accurate motion detection and segmentation are less critical due to the robustness of the principal axis-based feature to noise; 3) based on the fused data derived from correspondence results, positions of people in each camera view can be accurately located even when the people are partially occluded in all views. The experimental results on several real video sequences from outdoor environments have demonstrated the effectiveness, efficiency, and robustness of our method.Keywords
This publication has 23 references indexed in Scilit:
- A Survey on Visual Surveillance of Object Motion and BehaviorsIEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews), 2004
- Consistent labeling of tracked objects in multiple cameras with overlapping fields of viewIeee Transactions On Pattern Analysis and Machine Intelligence, 2003
- Tracking from multiple view points: Self-calibration of space and timePublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Multiple camera tracking of interacting and occluded human motionProceedings of the IEEE, 2001
- Urban surveillance systems: from the laboratory to the commercial worldProceedings of the IEEE, 2001
- Algorithms for cooperative multisensor surveillanceProceedings of the IEEE, 2001
- Tracking Groups of PeopleComputer Vision and Image Understanding, 2000
- W/sup 4/: real-time surveillance of people and their activitiesIeee Transactions On Pattern Analysis and Machine Intelligence, 2000
- Tracking human motion in structured environments using a distributed-camera systemIeee Transactions On Pattern Analysis and Machine Intelligence, 1999
- The background primal sketch: An approach for tracking moving objectsMachine Vision and Applications, 1992