Building descriptive and discriminative visual codebook for large-scale image applications

doi:10.1007/s11042-010-0636-6

CORC > 计算技术研究所 > 中国科学院计算技术研究所 > 中国科学院计算技术研究所期刊论文 > 英文

	Building descriptive and discriminative visual codebook for large-scale image applications
	Tian, Qi 1; Zhang, Shiliang 6; Zhou, Wengang 3; Ji, Rongrong 4; Ni, Bingbing 5; Sebe, Nicu 2
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	2011
卷号	51 期号:2 页码:441-477
关键词	Visual vocabulary Large-scale image retrieval Image search re-ranking Feature space quantization
ISSN号	1380-7501
DOI	10.1007/s11042-010-0636-6
英文摘要	Inspired by the success of textual words in large-scale textual information processing, researchers are trying to extract visual words from images which function similar as textual words. Visual words are commonly generated by clustering a large amount of image local features and the cluster centers are taken as visual words. This approach is simple and scalable, but results in noisy visual words. Lots of works are reported trying to improve the descriptive and discriminative ability of visual words. This paper gives a comprehensive survey on visual vocabulary and details several state-of-the-art algorithms. A comprehensive review and summarization of the related works on visual vocabulary is first presented. Then, we introduce our recent algorithms on descriptive and discriminative visual word generation, i.e., latent visual context analysis for descriptive visual word identification [74], descriptive visual words and visual phrases generation [68], contextual visual vocabulary which combines both semantic contexts and spatial contexts [69], and visual vocabulary hierarchy optimization [18]. Additionally, we introduce two interesting post processing strategies to further improve the performance of visual vocabulary, i.e., spatial coding [73] is proposed to efficiently remove the mismatched visual words between images for more reasonable image similarity computation; user preference based visual word weighting [44] is developed to make the image similarity computed based on visual words more consistent with users' preferences or habits.
资助项目	NSF[IIS 1052851] ; Akiira Media Systems, Inc. ; FIRB SPATTERN project ; FP7 IP GLOCAL European project
WOS研究方向	Computer Science ; Engineering
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000286472300003
内容类型	期刊论文
源URL	[http://119.78.100.204/handle/2XEOYT63/12539]
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Tian, Qi
作者单位	1.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 2.Univ Trent, Dept Informat Engn & Comp Sci, I-38100 Trento, Italy 3.Univ Sci & Technol China, EEIS Dept, Hefei 230027, Peoples R China 4.Harbin Inst Technol, Harbin 150001, Heilongjiang, Peoples R China 5.Natl Univ Singapore, Singapore 117576, Singapore 6.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Tian, Qi,Zhang, Shiliang,Zhou, Wengang,et al. Building descriptive and discriminative visual codebook for large-scale image applications[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2011,51(2):441-477.
APA	Tian, Qi,Zhang, Shiliang,Zhou, Wengang,Ji, Rongrong,Ni, Bingbing,&Sebe, Nicu.(2011).Building descriptive and discriminative visual codebook for large-scale image applications.MULTIMEDIA TOOLS AND APPLICATIONS,51(2),441-477.
MLA	Tian, Qi,et al."Building descriptive and discriminative visual codebook for large-scale image applications".MULTIMEDIA TOOLS AND APPLICATIONS 51.2(2011):441-477.