NDLI: LGE-KSVD: Flexible Dictionary Learning for Optimized Sparse Representation Classification

Content Provider	IEEE Xplore Digital Library
Author	Ptucha, R. Savakis, A.
Copyright Year	2013
Description	Author affiliation: Rochester Inst. of Technol., Rochester, NY, USA (Ptucha, R.; Savakis, A.)
Abstract	Sparse representations have successfully been exploited for the development of highly accurate classifiers. Unfortunately, these classifiers are computationally intensive and subject to the adverse effects of coefficient contamination, where for example variations in pose may affect identity and expression recognition. We propose a technique, called LGE-KSVD, that addresses both problems and attains state-of-the-art results for face and gesture classification problems. Specifically, LGE-KSVD utilizes variants of Linear extension of Graph Embedding to optimize K-SVD, an iterative technique for small yet overcomplete dictionary learning. The dimensionality reduction matrix, sparse representation dictionary, sparse coefficients, and sparsity-based linear classifier are jointly learned through LGE-KSVD. The atom optimization process is redefined to have variable support using graph embedding techniques to produce a more flexible and elegant dictionary learning algorithm. Results are obtained for a wide variety of facial and activity recognition problems to demonstrate the robustness of the proposed method.
Starting Page	854
Ending Page	861
File Size	760354
Page Count	8
File Format	PDF
ISBN	9780769549903
ISSN	21607516
DOI	10.1109/CVPRW.2013.126
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-06-23
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Manifolds Dictionaries dimensionality reduction sparse representations dictionary learning Sparse matrices Face Image reconstruction Contamination
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
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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