基于快速傅里葉變換的局部分塊視覺跟蹤算法

侯志強(qiáng); 張浪; 余旺盛; 許婉君

doi:10.11999/JEIT150183

基于快速傅里葉變換的局部分塊視覺跟蹤算法

doi: 10.11999/JEIT150183

基金項(xiàng)目:

國家自然科學(xué)基金(61175029, 61473309)和陜西省自然科學(xué)基金(2011JM8015)

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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-02-02
- 修回日期: 2015-06-03
- 刊出日期: 2015-10-19

Local Patch Tracking Algorithm Based on Fast Fourier Transform

Funds:

The National Natural Science Foundation of China (61175029, 61473309)

摘要

摘要: 針對(duì)視覺跟蹤中目標(biāo)表觀變化、局部遮擋、背景干擾等問題，該文提出一種基于快速傅里葉變換的局部分塊視覺跟蹤算法。通過建立目標(biāo)分塊核嶺回歸模型并構(gòu)建循環(huán)結(jié)構(gòu)矩陣進(jìn)行分塊窮搜索來提高跟蹤精度，利用快速傅里葉變換將時(shí)域運(yùn)算變換到頻域運(yùn)算提高跟蹤效率。首先，在包含目標(biāo)的初始跟蹤區(qū)域建立目標(biāo)分塊核嶺回歸模型；然后，提出通過構(gòu)造循環(huán)結(jié)構(gòu)矩陣進(jìn)行分塊窮搜索，并構(gòu)建目標(biāo)分塊在相鄰幀位置關(guān)系模型；最后，利用位置關(guān)系模型精確估計(jì)目標(biāo)位置并進(jìn)行分塊模型更新。實(shí)驗(yàn)結(jié)果表明，該文算法不僅對(duì)目標(biāo)表觀變化、局部遮擋以及背景干擾等問題的適應(yīng)能力有所增強(qiáng)，而且跟蹤實(shí)時(shí)性較好。
- 視覺跟蹤 /
- 核嶺回歸模型 /
- 快速傅里葉變換 /
- 分塊窮搜索 /
- 位置關(guān)系模型
Abstract: In order to solve the problems of appearance change, local occlusion and background distraction in the visual tracking, a local patch tracking algorithm based on Fast Fourier Transform(FFT)is proposed. The tracking precision can be improved by establishing objects patch kernel ridge regression model and using patch exhaustive search based on circular structure matrix, and the efficiency can be improved by transforming time domains operation into frequency domains based on FFT. Firstly, patch kernel ridge regression model is constructed according to the initialized tracking area. Secondly, a patch exhaustive search method based on circular structure matrix is proposed, then the position model is constructed in adjoining frame. Finally, the position of the object is estimated accurately using the position model and the local patch model is updated. Experimental results indicate that the proposed algorithm not only can obtain a distinct improvement in coping with appearance change, local occlusion and background distraction, but also have high tracking efficiency.
- Visual tracking /
- Kernel ridge regression model /
- Fast Fourier Transform (FFT) /
- Patch exhaustive search /
- Position model

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參考文獻(xiàn)(16)

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