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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Qicong Wang Wenxiao Jiang Chenhui Yang Yunqi Lei |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Computer Science, Xiamen University, 361005, China (Qicong Wang; Wenxiao Jiang; Chenhui Yang; Yunqi Lei) |
| Abstract | This paper proposes a fast target tracking method in which particle filter is improved using Gaussian kernel and evolutionary strategy. We use Gaussian kernel function to replace the Dirac kernel function, which can decrease the degeneracy problem of the traditional particle filter partly. To further improve the performance of particle filter, we introduce evolutionary strategy into the process of Gaussian kernel particle filtering. It uses only mutation operation, which has less computation than genetic algorithm. And it can prevent the impoverishment problem and steer the particles towards local mode of posterior probability effectively. The proposed method can track fast target robustly using fewer particles than the standard particle filter and Gaussian kernel particle filter. |
| Starting Page | 288 |
| Ending Page | 293 |
| File Size | 1685681 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424463343 |
| e-ISBN | 9781424463374 |
| DOI | 10.1109/IWACI.2010.5585219 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-08-25 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Target tracking Monte Carlo methods Evolutionary computation Particle filters Kernel |
| Content Type | Text |
| Resource Type | Article |
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