Modeling continuous visual features for semantic image annotation and retrieval

doi:10.1016/j.patrec.2010.11.015

	Modeling continuous visual features for semantic image annotation and retrieval
	Li, Zhixin 1,2; Shi, Zhiping 1; Liu, Xi 1; Shi, Zhongzhi 1
	2011-02-01
发表期刊	PATTERN RECOGNITION LETTERS
ISSN	0167-8655
卷号	32 期号:3 页码:516-523
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.
关键词	Automatic image annotation Continuous PLSA Latent aspect model Semantic gap Image retrieval
DOI	10.1016/j.patrec.2010.11.015
收录类别	SCI
语种	英语
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
WOS类目	Computer Science, Artificial Intelligence
WOS记录号	WOS:000286560600013
出版者	ELSEVIER SCIENCE BV
引用统计	被引频次：20[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/2XEOYT63/12880
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.