Title
Trajectory Association Across Non-Overlapping Moving Cameras In Planar Scenes
Abstract
The ability to associate objects across multiple views allows co-operative use of an ensemble cameras for scene understanding. In this paper, we present a principled solution to object association where both the scene and the object motion are modeled. By making the motion model of each object with respect to time explicit, we are able to solve the trajectory association problem in a unified framework for overlapping or non-overlapping cameras. We recover the assignment of associations while simultaneously computing the maximum likelihood estimates of the inter-camera homographies and the trajectory parameters using the Expectation Maximization algorithm. Quantitative results on simulations are reported along with several results on real data. ©2007 IEEE.
Publication Date
10-11-2007
Publication Title
Proceedings of the IEEE Computer Society Conference on Computer Vision and Pattern Recognition
Number of Pages
-
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1109/CVPR.2007.383182
Copyright Status
Unknown
Socpus ID
34948816668 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/34948816668
STARS Citation
Sheikh, Yaser; Xin, Li; and Shah, Mubarak, "Trajectory Association Across Non-Overlapping Moving Cameras In Planar Scenes" (2007). Scopus Export 2000s. 6666.
https://stars.library.ucf.edu/scopus2000/6666