Learning latent semantic model with visual consistency for image analysis

CORC > 自动化研究所 > 中国科学院自动化研究所 > 模式识别国家重点实验室 > 图像与视频分析团队

	Learning latent semantic model with visual consistency for image analysis
	Cheng, Jian1 ; Li, Peng 1; Rui, Ting 2; Lu, Hanqing1
刊名	MULTIMEDIA TOOLS AND APPLICATIONS
	2015-02-01
卷号	74 期号:4 页码:1341-1356
关键词	PLSA Latent semantic model Image clustering
英文摘要	Latent semantic models (e.g. PLSA and LDA) have been successfully used in document analysis. In recent years, many of the latent semantic models have also been proved to be promising for visual content analysis tasks, such as image clustering and classification. The topics and words which are two of the key components in latent semantic models have explicit semantic meaning in document analysis. However, these topics and words are difficult to be described or represented in visual content analysis tasks, which usually leads to failure in practice. In this paper, we consider simultaneously the topic consistency and word consistency in semantic space to adapt the traditional PLSA model to the visual content analysis tasks. In our model, the a"" (1)-graph is constructed to model the local neighborhood structure of images in feature space and the word co-occurrence is computed to capture the local word consistency. Then, the local information is incorporated into the model for topic discovering. Finally, the generalized EM algorithm is used to estimate the parameters. Extensive experiments on publicly available databases demonstrate the effectiveness of our approach.
WOS标题词	Science & Technology ; Technology
类目[WOS]	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
研究领域[WOS]	Computer Science ; Engineering
关键词[WOS]	NONLINEAR DIMENSIONALITY REDUCTION ; REPRESENTATION
收录类别	SCI
语种	英语
WOS记录号	WOS:000349356300010
公开日期	2015-09-22
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/8057]
专题	自动化研究所_模式识别国家重点实验室_图像与视频分析团队
作者单位	1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China 2.PLA Univ Sci & Technol, Nanjing 210007, Jiangsu, Peoples R China
推荐引用方式 GB/T 7714	Cheng, Jian,Li, Peng,Rui, Ting,et al. Learning latent semantic model with visual consistency for image analysis[J]. MULTIMEDIA TOOLS AND APPLICATIONS,2015,74(4):1341-1356.
APA	Cheng, Jian,Li, Peng,Rui, Ting,&Lu, Hanqing.(2015).Learning latent semantic model with visual consistency for image analysis.MULTIMEDIA TOOLS AND APPLICATIONS,74(4),1341-1356.
MLA	Cheng, Jian,et al."Learning latent semantic model with visual consistency for image analysis".MULTIMEDIA TOOLS AND APPLICATIONS 74.4(2015):1341-1356.