Knowledge Commons of Institute of Automation,CAS
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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Learning latent sema(783KB) | 期刊论文 | 作者接受稿 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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