A robust template tracking algorithm with weighted active drift correction

► We propose a novel algorithm for object template tracking and its drift correction. ► The tracking term and the drift correction term constitute the total energy function. ► The template tracking and weighted active drift correction are achieved synchronously by minimizing the total energy. ► We d...

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Vydáno v:	Pattern recognition letters Ročník 32; číslo 9; s. 1317 - 1327
Hlavní autoři:	Fan, Baojie, Du, Yingkui, Zhu, Linlin, Sun, Jing, Tang, Yandong
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Amsterdam Elsevier B.V 01.07.2011 Elsevier
Témata:	Active drift correction Applied sciences Detection, estimation, filtering, equalization, prediction Exact sciences and technology Image processing Information, signal and communications theory Inverse compositional algorithm Pattern recognition Signal and communications theory Signal processing Signal, noise Telecommunications and information theory Template tracking Template update Inverse compositional algorithm Active drift correction Template tracking Template update Target tracking Image processing Energy function Sequence alignment Updating L2 approximation Algorithm Adaptive method Image matching Algorithm performance Object detection Target detection
ISSN:	0167-8655, 1872-7344
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Abstract	► We propose a novel algorithm for object template tracking and its drift correction. ► The tracking term and the drift correction term constitute the total energy function. ► The template tracking and weighted active drift correction are achieved synchronously by minimizing the total energy. ► We design a new template updating strategy to diminish the accumulative error during the tracking. ► Verified on the PETS2001 datasets, the proposed algorithm can prevent the tracking drift effectively, and save the time of an additional correction tracking, and achieve better performance than the inverse compositional algorithm for drift correction. In this paper, we propose a novel algorithm for object template tracking and its drift correction. It can prevent the tracking drift effectively, and save the time of an additional correction tracking. In our algorithm, the total energy function consists of two terms: the tracking term and the drift correction term. We minimize the total energy function synchronously for template tracking and weighted active drift correction. The minimization of the active drift correction term is achieved by the inverse compositional algorithm with a weighted L2 norm, which is incorporated into traditional affine image alignment (AIA) algorithm. Its weights can be adaptively updated for each template. For diminishing the accumulative error in tracking, we design a new template update strategy that chooses a new template with the lowest matching error. Finally, we will present various experimental results that validate our algorithm. These results also show that our algorithm achieves better performance than the inverse compositional algorithm for drift correction.
AbstractList	► We propose a novel algorithm for object template tracking and its drift correction. ► The tracking term and the drift correction term constitute the total energy function. ► The template tracking and weighted active drift correction are achieved synchronously by minimizing the total energy. ► We design a new template updating strategy to diminish the accumulative error during the tracking. ► Verified on the PETS2001 datasets, the proposed algorithm can prevent the tracking drift effectively, and save the time of an additional correction tracking, and achieve better performance than the inverse compositional algorithm for drift correction. In this paper, we propose a novel algorithm for object template tracking and its drift correction. It can prevent the tracking drift effectively, and save the time of an additional correction tracking. In our algorithm, the total energy function consists of two terms: the tracking term and the drift correction term. We minimize the total energy function synchronously for template tracking and weighted active drift correction. The minimization of the active drift correction term is achieved by the inverse compositional algorithm with a weighted L2 norm, which is incorporated into traditional affine image alignment (AIA) algorithm. Its weights can be adaptively updated for each template. For diminishing the accumulative error in tracking, we design a new template update strategy that chooses a new template with the lowest matching error. Finally, we will present various experimental results that validate our algorithm. These results also show that our algorithm achieves better performance than the inverse compositional algorithm for drift correction.
Author	Zhu, Linlin Sun, Jing Tang, Yandong Fan, Baojie Du, Yingkui
Author_xml	– sequence: 1 givenname: Baojie surname: Fan fullname: Fan, Baojie email: fanbaojie@sia.cn organization: Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China – sequence: 2 givenname: Yingkui surname: Du fullname: Du, Yingkui email: dyk@sia.cn organization: Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China – sequence: 3 givenname: Linlin surname: Zhu fullname: Zhu, Linlin email: zhulinlin@sia.cn organization: Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China – sequence: 4 givenname: Jing surname: Sun fullname: Sun, Jing email: sunjing@sia.cn organization: Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China – sequence: 5 givenname: Yandong surname: Tang fullname: Tang, Yandong email: ytang@sia.cn organization: Shenyang Institute Automation, Chinese Academy of Sciences, Shenyang 110016, China
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Cites_doi	10.1109/TPAMI.2003.1195991 10.1016/j.patrec.2007.03.007 10.1007/BF00130487 10.1109/ICCV.1995.466925 10.21236/ADA366982 10.1016/j.patcog.2004.05.011 10.1023/B:VISI.0000011205.11775.fd 10.1007/3-540-55426-2_27 10.1109/34.841758 10.1016/j.imavis.2005.08.001 10.1016/S0262-8856(01)00076-2 10.1109/ICIP.2008.4711736 10.1109/34.722606 10.1109/TIP.2003.821445 10.1007/978-3-642-10817-4_86 10.1109/34.927467 10.1109/34.990133 10.1109/TPAMI.2003.1233903 10.1109/TIP.2004.836152 10.1023/A:1007939232436 10.1109/TPAMI.2004.16
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Keywords	Inverse compositional algorithm Active drift correction Template tracking Template update Target tracking Image processing Energy function Sequence alignment Updating L2 approximation Algorithm Adaptive method Image matching Algorithm performance Object detection Target detection
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Snippet	► We propose a novel algorithm for object template tracking and its drift correction. ► The tracking term and the drift correction term constitute the total...
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SubjectTerms	Active drift correction Applied sciences Detection, estimation, filtering, equalization, prediction Exact sciences and technology Image processing Information, signal and communications theory Inverse compositional algorithm Pattern recognition Signal and communications theory Signal processing Signal, noise Telecommunications and information theory Template tracking Template update
Title	A robust template tracking algorithm with weighted active drift correction
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