NDLI: Concurrent Single-Label Image Classification and Annotation via Efficient Multi-Layer Group Sparse Coding

Content Provider	IEEE Xplore Digital Library
Author	Shenghua Gao Liang-Tien Chia Tsang, I.W.-H. Zhixiang Ren
Copyright Year	1999
Abstract	We present a multi-layer group sparse coding framework for concurrent single-label image classification and annotation. By leveraging the dependency between image class label and tags, we introduce a multi-layer group sparse structure of the reconstruction coefficients. Such structure fully encodes the mutual dependency between the class label, which describes image content as a whole, and tags, which describe the components of the image content. Therefore we propose a multi-layer group based tag propagation method, which combines the class label and subgroups of instances with similar tag distribution to annotate test images. To make our model more suitable for nonlinear separable features, we also extend our multi-layer group sparse coding in the Reproducing Kernel Hilbert Space (RKHS), which further improves performances of image classification and annotation. Moreover, we also integrate our multi-layer group sparse coding with kNN strategy, which greatly improves the computational efficiency. Experimental results on the LabelMe, UIUC-Sports and NUS-WIDE-Object databases show that our method outperforms the baseline methods, and achieves excellent performances in both image classification and annotation tasks.
Sponsorship	IEEE Signal Processing Society IEEE Circuits and Systems Society IEEE Communications Society IEEE Computer Society
Starting Page	762
Ending Page	771
Page Count	10
File Size	1693145
File Format	PDF
ISSN	15209210
Volume Number	16
Issue Number	3
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image coding Training Image reconstruction Kernel Encoding Computational modeling Semantics sparse coding Image annotation image classification kernel trick
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Science Applications Media Technology

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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