Learning latent semantic model with visual consistency for image analysis
Cheng, Jian1; Li, Peng1; Rui, Ting2; Lu, Hanqing1
发表期刊MULTIMEDIA TOOLS AND APPLICATIONS
2015-02-01
卷号74期号:4页码:1341-1356
文章类型Article
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.
关键词Plsa Latent Semantic Model Image Clustering
WOS标题词Science & Technology ; Technology
关键词[WOS]NONLINEAR DIMENSIONALITY REDUCTION ; REPRESENTATION
收录类别SCI
语种英语
WOS研究方向Computer Science ; Engineering
WOS类目Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods ; Engineering, Electrical & Electronic
WOS记录号WOS:000349356300010
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/8057
专题紫东太初大模型研究中心_图像与视频分析
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
第一作者单位模式识别国家重点实验室
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.
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