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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Feng Sha Changseok Bae Guang Liu XiMeng Zhao Yuk Ying Chung WeiChang Yeh |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Inf. Technol., Univ. of Sydney, Sydney, NSW, Australia (Feng Sha; Guang Liu; XiMeng Zhao; Yuk Ying Chung) || Dept. of Ind. Eng. & Eng. Manage., Nat. Tsing Hua Univ., Hsinchu, Taiwan (WeiChang Yeh) || SW Content Res. Lab., Electron. & Telecommun. Res. Inst., Daejeon, South Korea (Changseok Bae) |
| Abstract | Object tracking for video and camera image capturing becomes more popular in recent scientific and application domain. Many Scientists in Image Processing try to find an efficient and accurate way to track the objects' moving in real time video applications. Particle Swarm Optimization is one of the most efficient and potential approaches developed to provide linear and non-linear object tracking by identifying special patterns for selected object, and achieving efficient algorithm to calculate random object moving. Compare to classic Kalman Filter, Particle Filter, or other improved PSO, this paper is aim to find a more efficient and precious pathway using categorized particle movement with dynamic inertia weight value in PSO to build a tracking procedure in order to provide better tracking speed and quality result in different types of video records and different visions of object moving. The proposed Categorized PSO based target tracking scheme can achieve better quality when compared to Particle Filter and typical Particle Swarm Optimization methods in our tracking experiments. It has been developed in C++ environment and tested against videos to demonstrate its excellent tracking ability in object retrieval and high accurate in tracking objects movement within other similar object's environment. |
| Starting Page | 2737 |
| Ending Page | 2744 |
| File Size | 1839470 |
| Page Count | 8 |
| File Format | |
| e-ISBN | 9781479974924 |
| DOI | 10.1109/CEC.2015.7257228 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-05-25 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Target tracking Object tracking Particle filters Histograms Particle swarm optimization Search problems Object Tracking PSO Particle Swarm Optimization inertia weight constriction factor Histogram |
| Content Type | Text |
| Resource Type | Article |
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