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Learning binary codes with local and inner data structure
He, Shiyuan1; Ye, Guo1; Hu, Mengqiu1; Yang, Yang1; Shen, Fumin1; Shen, Heng Tao1; Li, Xuelong2
作者部门光学影像学习与分析中心
2018-03-22
发表期刊NEUROCOMPUTING
ISSN0925-2312
卷号282页码:32-41
产权排序2
摘要

Recent years have witnessed the promising capacity of hashing techniques in tackling nearest neighbor search because of the high efficiency in storage and retrieval. Data-independent approaches (e.g., Locality Sensitive Hashing) normally construct hash functions using random projections, which neglect intrinsic data properties. To compensate this drawback, learning-based approaches propose to explore local data structure and/or supervised information for boosting hashing performance. However, due to the construction of Laplacian matrix, existing methods usually suffer from the unaffordable training cost. In this paper, we propose a novel supervised hashing scheme, which has the merits of (1) exploring the inherent neighborhoods of samples; (2) significantly saving training cost confronted with massive training data by employing approximate anchor graph; as well as (3) preserving semantic similarity by leveraging pair-wise supervised knowledge. Besides, we integrate discrete constraint to significantly eliminate accumulated errors in learning reliable hash codes and hash functions. We devise an alternative algorithm to efficiently solve the optimization problem. Extensive experiments on various image datasets demonstrate that our proposed method is superior to the state-of-the-arts. (c) 2017 Elsevier B.V. All rights reserved.

关键词Supervised Hashing Anchor Graph Nearest Neighbor Search
DOI10.1016/j.neucom.2017.12.005
收录类别SCI ; EI
语种英语
WOS记录号WOS:000424893200004
EI入藏号20180104597751
引用统计
文献类型期刊论文
条目标识符http://ir.opt.ac.cn/handle/181661/30772
专题光学影像学习与分析中心
作者单位1.Univ Elect Sci & Technol China, Ctr Future Media, Chengdu, Sichuan, Peoples R China;
2.Chinese Acad Sci, Ctr OPTical IMagery Anal & Learning OPTIMAL, State Key Lab Transient Opt & Photon, Xian Inst Opt & Precis Mech, Xian 710119, Shaanxi, Peoples R China
推荐引用方式
GB/T 7714
He, Shiyuan,Ye, Guo,Hu, Mengqiu,et al. Learning binary codes with local and inner data structure[J]. NEUROCOMPUTING,2018,282:32-41.
APA He, Shiyuan.,Ye, Guo.,Hu, Mengqiu.,Yang, Yang.,Shen, Fumin.,...&Li, Xuelong.(2018).Learning binary codes with local and inner data structure.NEUROCOMPUTING,282,32-41.
MLA He, Shiyuan,et al."Learning binary codes with local and inner data structure".NEUROCOMPUTING 282(2018):32-41.
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