Presentation | 2004/9/3 K-means tracking with variable ellipse model CHUNSHENG HUA, TOSHIKAZU WADA, HAIYUAN WU, |
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Abstract(in English) | We have proposed a K-means clustering based target tracking method, which is robust against background involution comparing with the target template. This paper presents a new method for solving the drawbacks of the previous method, i.e., speed, stability, target appearance change and size change. Our new tracking method consists of a single target point, and a variable ellipse model for representing non-target pixels. The contributions of our new method are : 1) The original K-means clustering is reduced to 2-means clustering, i.e., target and non-target clusters, and the non-target cluster center is adaptively picked up from the pixels on the ellipse circumference. This modification reduces the number of distance computation and improves the stability of the target detection as well. 2) The ellipse parameters are adaptively controlled according to the target detection result. This adaptation improves the robustness against the scale and shape changes of the target. Through the various experiments, we confirmed that our new method improves speed and robustness of the original method. |
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Paper # | PRMU2004-68 |
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Committee | PRMU |
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Conference Date | 2004/9/3(1days) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | K-means tracking with variable ellipse model |
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1st Author's Name | CHUNSHENG HUA |
1st Author's Affiliation | Wakayama University() |
2nd Author's Name | TOSHIKAZU WADA |
2nd Author's Affiliation | Wakayama University |
3rd Author's Name | HAIYUAN WU |
3rd Author's Affiliation | Wakayama University |
Date | 2004/9/3 |
Paper # | PRMU2004-68 |
Volume (vol) | vol.104 |
Number (no) | 290 |
Page | pp.pp.- |
#Pages | 8 |
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