Title

Human Tracking In Multiple Cameras

Keywords

Camera handoff; Multi-perspective video; Sensor fusion; Surveillance; Tracking in multiple cameras

Abstract

Multiple cameras are needed to cover large environments for monitoring activity. To track people successfully in multiple perspective imagery, one needs to establish correspondence between objects captured in multiple cameras. We present a system for tracking people in multiple uncalibrated cameras. The system is able to discover spatial relationships between the camera fields of view and use this information to correspond between different perspective views of the same person. We employ the novel approach of finding the limits of field of view (FOV) of a camera as visible in the other cameras. Using this information, when a person is seen in one camera, we are able to predict all the other cameras in which this person will be visible. Moreover, we apply the FOV constraint to disambiguate between possible candidates of correspondence. We present results on sequences of up to three cameras with multiple people. The proposed approach is very fast compared to camera calibration based approaches.

Publication Date

1-1-2001

Publication Title

Proceedings of the IEEE International Conference on Computer Vision

Volume

1

Number of Pages

331-336

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/ICCV.2001.937537

Socpus ID

0034857777 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0034857777

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