Spectral Hashing With Semantically Consistent Graph for Image Indexing

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 图像与视频分析团队

	Spectral Hashing With Semantically Consistent Graph for Image Indexing
	Li, Peng 1; Wang, Meng 2; Cheng, Jian1 ; Xu, Changsheng1 ; Lu, Hanqing1
刊名	IEEE TRANSACTIONS ON MULTIMEDIA
	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
内容类型	期刊论文
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.