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Joint geometric and photometric visual tracking based on lie group
Li CX(李晨曦); Shi ZL(史泽林); Liu YP(刘云鹏); Liu TC(刘天赐)
Department光电信息技术研究室
Conference Name3rd International Conference on Geometric Science of Information, GSI 2017
Conference DateNovember 7-9, 2017
Conference PlaceParis, France
Source PublicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Publication PlaceBerlin
2017
Pages291-298
Indexed ByEI ; CPCI(ISTP)
EI Accession number20174604409904
WOS IDWOS:000440482500034
Contribution Rank1
ISSN0302-9743
ISBN978-3-319-68444-4
KeywordVisual Tracking Illumination Variations Lie Algebra Efficient Second-order Minimization Lie Group
Abstract

This paper presents a novel efficient and robust direct visual tracking method under illumination variations. In our approach, non-Euclidean Lie group characteristics of both geometric and photometric transformations are exploited. These transformations form Lie groups and are parameterized by their corresponding Lie algebras. By applying the efficient second-order minimization trick, we derive an efficient second-order optimization technique for jointly solving the geometric and photometric parameters. Our approach has a high convergence rate and low iterations. Moreover, our approach is almost not affected by linear illumination variations. The superiority of our proposed method over the existing direct methods, in terms of efficiency and robustness is demonstrated through experiments on synthetic and real data.

Language英语
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/21235
Collection光电信息技术研究室
Corresponding AuthorLi CX(李晨曦)
Affiliation1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, 110016, China
2.University of Chinese Academy of Sciences, Beijing, 100049, China
3.Key Laboratory of Opto-electronic Information Processing, Chinese Academy of Sciences, Shenyang, Liaoning, 110016, China
4.The Key Lab of Image Understanding and Computer Vision, Shenyang, Liaoning Province, 110016, China
Recommended Citation
GB/T 7714
Li CX,Shi ZL,Liu YP,et al. Joint geometric and photometric visual tracking based on lie group[C]. Berlin:Springer Verlag,2017:291-298.
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