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Modeling continuous visual features for semantic image annotation and retrieval

文献类型：期刊论文

作者Li, Zhixin1,2; Shi, Zhiping1; Liu, Xi1; Shi, Zhongzhi1
刊名PATTERN RECOGNITION LETTERS
出版日期2011-02-01
卷号32期号:3页码:516-523
关键词Automatic image annotation Continuous PLSA Latent aspect model Semantic gap Image retrieval
ISSN号0167-8655
DOI10.1016/j.patrec.2010.11.015
英文摘要Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we firstly extend probabilistic latent semantic analysis (PLSA) to model continuous quantity. In addition, corresponding Expectation-Maximization (EM) algorithm is derived to determine the model parameters. Furthermore, in order to deal with the data of different modalities in terms of their characteristics, we present a semantic annotation model which employs continuous PLSA and standard PLSA to model visual features and textual words respectively. The model learns the correlation between these two modalities by an asymmetric learning approach and then it can predict semantic annotation precisely for unseen images. Finally, we compare our approach with several state-of-the-art approaches on the Core15k and Core130k datasets. The experiment results show that our approach performs more effectively and accurately. (C) 2010 Elsevier B.V. All rights reserved.
资助项目National Basic Research Priorities Programme[2007CB311004] ; National Science and Technology Support Plan[2006BAC08B06] ; National Natural Science Foundation of China[60933004] ; National Natural Science Foundation of China[60903141] ; National Natural Science Foundation of China[60903079] ; National Natural Science Foundation of China[60775035] ; National Natural Science Foundation of China[60970088]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:000286560600013
出版者ELSEVIER SCIENCE BV
源URL[http://119.78.100.204/handle/2XEOYT63/12879]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Li, Zhixin
作者单位1.Chinese Acad Sci, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100190, Peoples R China
2.Guangxi Normal Univ, Coll Comp Sci & Informat Technol, Guilin 541004, Peoples R China
推荐引用方式
GB/T 7714		 Li, Zhixin,Shi, Zhiping,Liu, Xi,et al. Modeling continuous visual features for semantic image annotation and retrieval[J]. PATTERN RECOGNITION LETTERS,2011,32(3):516-523.
APA Li, Zhixin,Shi, Zhiping,Liu, Xi,&Shi, Zhongzhi.(2011).Modeling continuous visual features for semantic image annotation and retrieval.PATTERN RECOGNITION LETTERS,32(3),516-523.
MLA Li, Zhixin,et al."Modeling continuous visual features for semantic image annotation and retrieval".PATTERN RECOGNITION LETTERS 32.3(2011):516-523.

入库方式： OAI收割

来源：计算技术研究所

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