Title
Appearance Modeling For Tracking In Multiple Non-Overlapping Cameras
Abstract
When viewed from a system of multiple cameras with non-overlapping fields of view, the appearance of an object in one camera view is usually very different from its appearance in another camera view due to the differences in illumination, pose and camera parameters. In order to handle the change in observed colors of an object as it moves from one camera to another, we show that all brightness transfer functions from a given camera to another camera lie in a low dimensional subspace and demonstrate that this subspace can be used to compute appearance similarity. In the proposed approach, the system learns the subspace of inter-camera brightness transfer functions in a training phase during which object correspondences are assumed to be known. Once the training is complete, correspondences are assigned using the maximum a posteriori (MAP) estimation framework using both location and appearance cues. We evaluate the proposed method under several real world scenarios obtaining encouraging results.
Publication Date
1-1-2005
Publication Title
Proceedings - 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition, CVPR 2005
Volume
II
Number of Pages
26-33
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CVPR.2005.71
Copyright Status
Unknown
Socpus ID
24644519063 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/24644519063
STARS Citation
Javed, Omar; Shafique, Khurram; and Shah, Mubarak, "Appearance Modeling For Tracking In Multiple Non-Overlapping Cameras" (2005). Scopus Export 2000s. 4482.
https://stars.library.ucf.edu/scopus2000/4482