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CLC number: TP391.41

On-line Access: 2013-07-05

Received: 2012-12-29

Revision Accepted: 2013-05-08

Crosschecked: 2013-06-06

Cited: 9

Clicked: 6028

Citations:  Bibtex RefMan EndNote GB/T7714

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Journal of Zhejiang University SCIENCE C 2013 Vol.14 No.7 P.495-504

http://doi.org/10.1631/jzus.CIDE1303


A review of object representation based on local features


Author(s):  Jian Cao, Dian-hui Mao, Qiang Cai, Hai-sheng Li, Jun-ping Du

Affiliation(s):  College of Computer and Information Engineering, Beijing Technology and Business University, Beijing 100048, China; more

Corresponding email(s):   caojian@th.btbu.edu.cn, caojian9527@sina.com

Key Words:  Object presentation, Local feature, Image understanding, Object recognition, Visual words


Jian Cao, Dian-hui Mao, Qiang Cai, Hai-sheng Li, Jun-ping Du. A review of object representation based on local features[J]. Journal of Zhejiang University Science C, 2013, 14(7): 495-504.

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A1 - Jian Cao
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DOI - 10.1631/jzus.CIDE1303


Abstract: 
Object representation based on local features is a topical subject in the domain of image understanding and computer vision. We discuss the defects of global features in present methods and the advantages of local features in object recognition, and briefly explore state-of-the-art recognition methods using local features, especially the main approaches of local feature extraction and object representation. To clearly explain these methods, the problem of local feature extraction is divided into feature region detection, feature region description, and feature space optimization. The main components and merits of these steps are presented. Technologies for object presentation are classified into three types: vector space, sliding window, and structure relationship models. Future development trends are discussed briefly.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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