NDLI: Open-set semi-supervised audio-visual speaker recognition using co-training LDA and Sparse Representation Classifiers

Content Provider	IEEE Xplore Digital Library
Author	Xuran Zhao Evans, N. Dugelay, J.-L.
Copyright Year	2013
Description	Author affiliation: Dept. of Multimedia Commun., EURECOM, Biot, France (Xuran Zhao; Evans, N.; Dugelay, J.-L.)
Abstract	Semi-supervised learning is attracting growing interest within the biometrics community. Almost all prior work focuses on closed-set scenarios, in which samples labelled automatically are assumed to belong to an enrolled class. This is often not the case in realistic applications and thus open-set alternatives are needed. This paper proposes a new approach to open-set, semi-supervised learning based on co-training, Linear Discriminant Analysis (LDA) subspaces and Sparse Representation Classifiers (SRCs). Experiments on the standard MOBIO dataset show how the new approach can utilize automatically labelled data to augment a smaller, manually labelled dataset and thus improve the performance of an open-set audio-visual person recognition system.
Starting Page	2999
Ending Page	3003
File Size	298375
Page Count	5
File Format	PDF
ISBN	9781479903566
ISSN	15206149
DOI	10.1109/ICASSP.2013.6638208
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-05-26
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Feature extraction Biometrics (access control) Face Principal component analysis Semisupervised learning Standards co-training Semi-supervised learning open-set identification multimodal biometrics
Content Type	Text
Resource Type	Article

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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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