Referenced Items are not available for this document.
In this paper, a framework for spatiotemporal vehicle tracking using unsupervised learning-based segmentation and object tracking is presented. An adaptive background learning and subtraction method is proposed and applied to two real-traffic video sequences to obtain more accurate spatiotemporal information on the vehicle objects. As demonstrated in the experiments, almost all vehicle objects are successfully identified through this framework.
Published in:
Robotics & Automation Magazine, IEEE
(Volume:12
,
Issue:
1
)
Date of Publication: March 2005
- Page(s):
- 50 - 58
- ISSN :
- 1070-9932
- INSPEC Accession Number:
- 8372282
- Digital Object Identifier :
- 10.1109/MRA.2005.1411419
- Product Type:
- Journals & Magazines
- Date of Current Version :
- 04 April 2005
- Issue Date :
- March 2005
- Sponsored by :
- IEEE Robotics and Automation Society
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