基于二階空間直方圖的雙核跟蹤
doi: 10.11999/JEIT141321 cstr: 32379.14.JEIT141321
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1.
(廣西師范大學計算機科學與信息工程學院 桂林 541004) ②(桂林電子科技大學 桂林 541004)
基金項目:
國家自然科學基金(61365009, 61165009),廣西自然科學基金(2014GXNSFAA118368, 2012GXNSFAA053219)和廣西高校科技項目(2013YB027)
Dual-kernel Tracking Approach Based on Second-order Spatiogram
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2.
(Guangxi Experiment Center of Information Science, Guilin University of Electronic Technology, Guilin 541004, China)
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摘要: 針對核跟蹤算法中的背景信息棄用和空間結(jié)構(gòu)丟失問題,該文提出一種基于二階空間直方圖的雙核式目標跟蹤算法。該算法以二階空間直方圖為目標表示模型,以相似度和對比度為目標判斷準則,來建立全新的目標函數(shù);并依據(jù)多變量泰勒展開和目標函數(shù)最大化方法,推導出雙核式目標位移公式;最后使用均值漂移程序遞歸地獲得了目標的最優(yōu)位置。通過對各種條件下運動目標的跟蹤驗證了算法的有效性。
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關鍵詞:
- 模式識別 /
- 雙核跟蹤 /
- 空間直方圖 /
- 延森-香農(nóng)散度
Abstract: In order to avoid the loss of background and spatial information in mean shift tracker, a dual-kernel tracking approach based on the second-order spatiogram is proposed. In the method, the second-order spatiogram is employed to represent a target, the similarity and contrast are considered simultaneously when evaluating the target candidate, and they are adaptively integrated into a novel objective function. By performing multi-variable Taylor series expansion and maximization on the objective function, a dual-kernel target location-shift formula is induced. Finally, the optimal target location is gained recursively by applying the mean shift procedure. Experimental evaluations on several image sequences demonstrate the effectiveness of the proposed algorithm.-
Key words:
- Pattern recognition /
- Dual-kernel tracking /
- Spatiogram /
- Jensen-Shannon divergence
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