Visual codebook construction for class-specific recognition

Jun Gao; Nong Sang; Changxin GaoQiling TangJun Sang

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Visual codebook construction for class-specific recognition

机译：Visual codebook construction for class-specific recognition

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摘要

Creating a visual codebook is an important problem in object recognition. Using a compact visual codebook can boost computational efficiency and reduce memory cost. A simple and effective method is proposed for visual feature codebook construction. On the basis of a feedforward hierarchical model, a robust local descriptor is proposed and an a priori statistical scheme is applied to the class-specific feature-learning stage. The experiments show that the proposed approach achieves reliable performance with shorter codebook length, and incremental learning can be easily enabled.

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来源
《Optical Engineering》 |2009年第7期|077201-1-077201-5|共5页
作者
Jun Gao; Nong Sang; Changxin GaoQiling TangJun Sang;
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作者单位

Huazhong University of Science and Technology, Institute for Pattern Recognition and Artificial Intelligence, 1037 Luo-Yu Road, Wuhan, Hubei 430074, China;

Chongqing University, School of Software Engineering, Chongqing, 400044, China;

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收录信息美国《科学引文索引》(SCI);美国《工程索引》(EI);
原文格式 PDF
正文语种英语
中图分类计量学;
关键词
object recognition; local descriptor codebook; a priori learning; feature selection;

Visual codebook construction for class-specific recognition

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