Spectral Hashing With Semantically Consistent Graph for Image Indexing
文献类型：期刊论文
| 作者 | Li, Peng1; Wang, Meng2 ; Cheng, Jian1; Xu, Changsheng1; Lu, Hanqing1
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| 刊名 | IEEE TRANSACTIONS ON MULTIMEDIA
 |
| 出版日期 | 2013 |
| 卷号 | 15期号:1页码:141-152 |
| 关键词 | Graph Laplacian metric learning similarity search spectral hashing |
| 英文摘要 | The ability of fast similarity search in a large-scale dataset is of great importance to many multimedia applications. Semantic hashing is a promising way to accelerate similarity search, which designs compact binary codes for a large number of images so that semantically similar images are mapped to close codes. Retrieving similar neighbors is then simply accomplished by retrieving images that have codes within a small Hamming distance of the code of the query. Among various hashing approaches, spectral hashing (SH) has shown promising performance by learning the binary codes with a spectral graph partitioning method. However, the Euclidean distance is usually used to construct the graph Laplacian in SH, which may not reflect the inherent distribution of the data. Therefore, in this paper, we propose a method to directly optimize the graph Laplacian. The learned graph, which can better represent similarity between samples, is then applied to SH for effective binary code learning. Meanwhile, our approach, unlike metric learning, can automatically determine the scale factor during the optimization. Extensive experiments are conducted on publicly available datasets and the comparison results demonstrate the effectiveness of our approach. |
| WOS标题词 | Science & Technology ; Technology |
| 类目[WOS] | Computer Science, Information Systems ; Computer Science, Software Engineering ; Telecommunications |
| 研究领域[WOS] | Computer Science ; Telecommunications |
| 关键词[WOS] | APPROXIMATE NEAREST-NEIGHBOR ; VIDEO ANNOTATION ; DIMENSIONALITY ; RETRIEVAL ; ALGORITHM |
| 收录类别 | SCI |
| 语种 | 英语 |
| WOS记录号 | WOS:000312646600012 |
| 源URL | [http://ir.ia.ac.cn/handle/173211/3350]  |
| 专题 | 自动化研究所_模式识别国家重点实验室_图像与视频分析团队 |
| 作者单位 | 1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing 100190, Peoples R China 2.Hefei Univ Technol, Sch Comp & Informat, Hefei 230009, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Peng,Wang, Meng,Cheng, Jian,et al. Spectral Hashing With Semantically Consistent Graph for Image Indexing[J]. IEEE TRANSACTIONS ON MULTIMEDIA,2013,15(1):141-152. |
| APA | Li, Peng,Wang, Meng,Cheng, Jian,Xu, Changsheng,&Lu, Hanqing.(2013).Spectral Hashing With Semantically Consistent Graph for Image Indexing.IEEE TRANSACTIONS ON MULTIMEDIA,15(1),141-152. |
| MLA | Li, Peng,et al."Spectral Hashing With Semantically Consistent Graph for Image Indexing".IEEE TRANSACTIONS ON MULTIMEDIA 15.1(2013):141-152. |
入库方式： OAI收割
来源：自动化研究所
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