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Image annotation using high order statistics in non-Euclidean spaces

文献类型：期刊论文

作者Zhu, Songhao1; Hu, Juanjuan1; Wang, Baoyun1; Shen, Shuhan2
刊名JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION
出版日期2013-11-01
卷号24期号:8页码:1342-1348
关键词Dissimilarity diffusion distribution High-order statistics Maximum a posteriori Gaussian Mixture Model Non-Euclidean space Image annotation Corel database Experimentation
英文摘要Automatic image annotation is a promising way to achieve more effective image retrieval and image analysis by using keywords associated to the image content. Due to the semantic gap between low-level visual features and high-level semantic concepts of an image, however, the performances of many existing algorithms are not so satisfactory. In this paper, a novel image classification scheme, named high order statistics based maximum a posterior (HOS-MAP), is proposed to deal with the issue of image annotation. To bridge the gap between human judgment and machine intelligence, the proposed scheme first constructs a dissimilarity representation for each image in a non-Euclidean space; then, the information of dissimilarity diffusion distribution for each image is achieved with respect to the high-order statistics of a triplet of nearest neighbor images; finally, a maximum a posteriori algorithm with the information of Gaussian Mixture Model and dissimilarity diffusion distribution is adopted to estimate the relevance between each annotation and an input un-annotated image. Experimental results on a general-purpose image database demonstrate the effectiveness and efficiency of the proposed automatic image annotation scheme. (C) 2013 Elsevier Inc. All rights reserved.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Information Systems ; Computer Science, Software Engineering
研究领域[WOS]Computer Science
关键词[WOS]RECOGNITION
收录类别SCI
语种英语
WOS记录号WOS:000328590700011
源URL[http://ir.ia.ac.cn/handle/173211/2989]  
专题自动化研究所_模式识别国家重点实验室_机器人视觉团队
作者单位1.Nanjing Univ Posts & Telecommun, Sch Automat, Nanjing 210046, Jiangsu, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 110093, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Songhao,Hu, Juanjuan,Wang, Baoyun,et al. Image annotation using high order statistics in non-Euclidean spaces[J]. JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,2013,24(8):1342-1348.
APA Zhu, Songhao,Hu, Juanjuan,Wang, Baoyun,&Shen, Shuhan.(2013).Image annotation using high order statistics in non-Euclidean spaces.JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION,24(8),1342-1348.
MLA Zhu, Songhao,et al."Image annotation using high order statistics in non-Euclidean spaces".JOURNAL OF VISUAL COMMUNICATION AND IMAGE REPRESENTATION 24.8(2013):1342-1348.

入库方式： OAI收割

来源：自动化研究所

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