Generating Descriptive Visual Words and Visual Phrases for Large-Scale Image Applications

doi:10.1109/TIP.2011.2128333

	Generating Descriptive Visual Words and Visual Phrases for Large-Scale Image Applications
	Zhang, Shiliang 1; Tian, Qi 2; Hua, Gang 3; Huang, Qingming 4; Gao, Wen 1
	2011-09-01
发表期刊	IEEE TRANSACTIONS ON IMAGE PROCESSING
ISSN	1057-7149
卷号	20 期号:9 页码:2664-2677
摘要	Bag-of-visual Words (BoWs) representation has been applied for various problems in the fields of multimedia and computer vision. The basic idea is to represent images as visual documents composed of repeatable and distinctive visual elements, which are comparable to the text words. Notwithstanding its great success and wide adoption, visual vocabulary created from single-image local descriptors is often shown to be not as effective as desired. In this paper, descriptive visual words (DVWs) and descriptive visual phrases (DVPs) are proposed as the visual correspondences to text words and phrases, where visual phrases refer to the frequently co-occurring visual word pairs. Since images are the carriers of visual objects and scenes, a descriptive visual element set can be composed by the visual words and their combinations which are effective in representing certain visual objects or scenes. Based on this idea, a general framework is proposed for generating DVWs and DVPs for image applications. In a large-scale image database containing 1506 object and scene categories, the visual words and visual word pairs descriptive to certain objects or scenes are identified and collected as the DVWs and DVPs. Experiments show that the DVWs and DVPs are informative and descriptive and, thus, are more comparable with the text words than the classic visual words. We apply the identified DVWs and DVPs in several applications including large-scale near-duplicated image retrieval, image search re-ranking, and object recognition. The combination of DVW and DVP performs better than the state of the art in large-scale near-duplicated image retrieval in terms of accuracy, efficiency and memory consumption. The proposed image search re-ranking algorithm: DWPRank outperforms the state-of-the-art algorithm by 12.4% in mean average precision and about 11 times faster in efficiency.
关键词	Image retrieval image search re-ranking object recognition visual phrase visual word
DOI	10.1109/TIP.2011.2128333
收录类别	SCI
语种	英语
资助项目	Microsoft Research Asia (MSRA) ; National Science Foundation[IIS 1052581] ; National Natural Science Foundation of China[61025011] ; National Natural Science Foundation of China[60833006] ; National Basic Research Program of China (973 Program)[2009CB320906] ; Beijing Natural Science Foundation[4092042] ; Google Faculty Research Award ; FXPAL Faculty Research Award
WOS研究方向	Computer Science ; Engineering
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS记录号	WOS:000294132800022
出版者	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
引用统计	被引频次：52[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://119.78.100.204/handle/2XEOYT63/12648
专题	中国科学院计算技术研究所期刊论文_英文
通讯作者	Zhang, Shiliang
作者单位	1.Chinese Acad Sci, Inst Comp Technol, Key Lab Intelligent Informat Proc, Beijing 100190, Peoples R China 2.Univ Texas San Antonio, Dept Comp Sci, San Antonio, TX 78249 USA 3.IBM Corp, TJ Watson Res Ctr, Armonk, NY 10532 USA 4.Chinese Acad Sci, Grad Univ, Beijing 100080, Peoples R China
推荐引用方式 GB/T 7714	Zhang, Shiliang,Tian, Qi,Hua, Gang,et al. Generating Descriptive Visual Words and Visual Phrases for Large-Scale Image Applications[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2011,20(9):2664-2677.
APA	Zhang, Shiliang,Tian, Qi,Hua, Gang,Huang, Qingming,&Gao, Wen.(2011).Generating Descriptive Visual Words and Visual Phrases for Large-Scale Image Applications.IEEE TRANSACTIONS ON IMAGE PROCESSING,20(9),2664-2677.
MLA	Zhang, Shiliang,et al."Generating Descriptive Visual Words and Visual Phrases for Large-Scale Image Applications".IEEE TRANSACTIONS ON IMAGE PROCESSING 20.9(2011):2664-2677.