Multilabel Image Annotation Based on Double-Layer PLSA Model
Joint Authors
Yuan, Y.-B.
Zhang, Jing
Li, Da
Hu, Weiwei
Chen, Zhihua
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-9, 9 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-06-04
Country of Publication
Egypt
No. of Pages
9
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
Due to the semantic gap between visual features and semantic concepts, automatic image annotation has become a difficult issue in computer vision recently.
We propose a new image multilabel annotation method based on double-layer probabilistic latent semantic analysis (PLSA) in this paper.
The new double-layer PLSA model is constructed to bridge the low-level visual features and high-level semantic concepts of images for effective image understanding.
The low-level features of images are represented as visual words by Bag-of-Words model; latent semantic topics are obtained by the first layer PLSA from two aspects of visual and texture, respectively.
Furthermore, we adopt the second layer PLSA to fuse the visual and texture latent semantic topics and achieve a top-layer latent semantic topic.
By the double-layer PLSA, the relationships between visual features and semantic concepts of images are established, and we can predict the labels of new images by their low-level features.
Experimental results demonstrate that our automatic image annotation model based on double-layer PLSA can achieve promising performance for labeling and outperform previous methods on standard Corel dataset.
American Psychological Association (APA)
Zhang, Jing& Li, Da& Hu, Weiwei& Chen, Zhihua& Yuan, Y.-B.. 2014. Multilabel Image Annotation Based on Double-Layer PLSA Model. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049834
Modern Language Association (MLA)
Zhang, Jing…[et al.]. Multilabel Image Annotation Based on Double-Layer PLSA Model. The Scientific World Journal No. 2014 (2014), pp.1-9.
https://search.emarefa.net/detail/BIM-1049834
American Medical Association (AMA)
Zhang, Jing& Li, Da& Hu, Weiwei& Chen, Zhihua& Yuan, Y.-B.. Multilabel Image Annotation Based on Double-Layer PLSA Model. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-9.
https://search.emarefa.net/detail/BIM-1049834
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1049834