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  2018, Vol. 31 Issue (1): 12-22    DOI: 10.16451/j.cnki.issn1003-6059.201801002
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Binary Representation Learning and Its Applications
LU Jiwen1, DUAN Yueqi1, CHEN Zhixiang1, ZHOU Jie1
1.Department of Automation, Tsinghua University, Beijing 100084

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Abstract  

With the rapid development of internet and other information technologies, the amount of visual data grows explosively. It is an essential research topic for efficient visual data mining in the big data era. In this paper, the technology of binary representation learning and its applications are reviewed. Binary representation shows efficiency in storage, transmission and matching, and it is successfully applied to several visual analysis tasks. The applications on visual search and recognition are summarized, and the future trend of binary representation learning is pointed out. From the aspect of methodology, the image-based hashing and the video-based hashing are illustrated, respectively. From the aspect of applications, the successful applications of binary representation learning on varying tasks are discussed including facial analysis, image categorization, image matching and visual tracking. Finally, the future trend of binary representation learning is introduced.

Key wordsBinary Representation      Feature Learning      Visual Recognition      Visual Search     
Received: 26 September 2017     
About author:: LU Jiwen, Ph.D., associate professor. His research interests include computer vision, pattern recognition and machine learning.DUAN Yueqi, Ph.D. candidate. His research interests include computer vision.CHEN Zhixiang, Ph.D., assistant profe-ssor. His research interests include computer vision.ZHOU JieCorresponding author, Ph.D., professor. His research interests include computer vision, pattern recognition and image processing.
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LU Jiwen
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LU Jiwen,DUAN Yueqi,CHEN Zhixiang等. Binary Representation Learning and Its Applications[J]. , 2018, 31(1): 12-22.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201801002      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2018/V31/I1/12
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