Paper Info
Title
Human 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.
Year
DOI
Venue
2001
10.1109/ICCV.2001.937537
Computer Vision, 2001. ICCV 2001. Proceedings. Eighth IEEE International Conference
Keywords
Field
DocType
calibration,computer vision,tracking,camera calibration,field of view,human tracking,multiple cameras,multiple perspective imagery,spatial relationships
Field of view,Computer vision,Computer graphics (images),Viewfinder,Computer science,Sensor fusion,Camera resectioning,Artificial intelligence,Application software,Calibration
Conference
Volume
ISBN
Citations 
1
0-7695-1143-0
51
PageRank 
References 
Authors
4.57
5
4
Name
Order
Citations
PageRank
Sohaib Khan162434.83
Omar Javed22365108.90
Z. Rasheed323514.48
Mubarak Shah416522943.74