| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 534744 | Pattern Recognition Letters | 2009 | 7 Pages |
Abstract
In this article, a novel algorithm – CamShift guided particle filter (CAMSGPF) – is proposed for tracking object in video sequence. CamShift is incorporated into the probabilistic framework of particle filter as an optimization scheme for proposal distribution. Meanwhile, in the context of particle filter, the scale adaptation of CamShift is improved and the computation complexity is reduced. It is demonstrated through several real tracking tasks that the new method performs better than baseline trackers in both tracking robustness and computational efficiency.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Zhaowen Wang, Xiaokang Yang, Yi Xu, Songyu Yu,