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Authors: Àgata Lapedriza 1 ; David Masip 2 and Jordi Vitrià 3

Affiliations: 1 Computer Vision Center, Universitat Autònoma de Barcelona, Spain ; 2 Computer Vision Center,Universitat Oberta de Catalunya, Spain ; 3 Computer Vision Center, Universitat de Barcelona, Spain

ISBN: 978-989-8111-21-0

Keyword(s): Face Classification, Feature Extraction, Feature Selection.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Feature Extraction ; Features Extraction ; Image and Video Analysis ; Informatics in Control, Automation and Robotics ; Signal Processing, Sensors, Systems Modeling and Control

Abstract: In this paper we propose a feature selection method that uses the mutual information (MI) measure on a Principal Component Analysis (PCA) based decomposition. PCA finds a linear projection of the data in a non-supervised way, which preserves the larger variance components of the data under the reconstruction error criterion. Previous works suggest that using the MI among the PCA projected data and the class labels applied to feature selection can add the missing discriminability criterion to the optimal reconstruction feature set. Our proposal goes one step further, defining a global framework to add independent selection criteria in order to filter misleading PCA components while the optimal variables for classification are preserved. We apply this approach to a face recognition problem using the AR Face data set. Notice that, in this problem, PCA projection vectors strongly related to illumination changes and occlusions are usually preserved given their high variance. Our additional selection tasks are able to discard this type of features while the relevant features to perform the subject recognition classification are kept. The experiments performed show an improved feature selection process using our combined criterion. (More)

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Paper citation in several formats:
Lapedriza À.; Masip D.; Vitrià J. and (2008). SUBJECT RECOGNITION USING A NEW APPROACH FOR FEATURE SELECTION.In Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008) ISBN 978-989-8111-21-0, pages 61-66. DOI: 10.5220/0001079100610066

@conference{visapp08,
author={Àgata Lapedriza and David Masip and Jordi Vitrià},
title={SUBJECT RECOGNITION USING A NEW APPROACH FOR FEATURE SELECTION},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)},
year={2008},
pages={61-66},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001079100610066},
isbn={978-989-8111-21-0},
}

TY - CONF

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications - Volume 1: VISAPP, (VISIGRAPP 2008)
TI - SUBJECT RECOGNITION USING A NEW APPROACH FOR FEATURE SELECTION
SN - 978-989-8111-21-0
AU - Lapedriza, À.
AU - Masip, D.
AU - Vitrià, J.
PY - 2008
SP - 61
EP - 66
DO - 10.5220/0001079100610066

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