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Authors: Soeren Klemm ; Yasmina Andreu ; Pedro Henriquez and Bogdan J. Matuszewski

Affiliation: University of Central Lancashire, United Kingdom

Keyword(s): Face Recognition, SIFT, SURF, ORB, Feature Matching, Face Occlusions.

Abstract: Key-point based techniques have demonstrated a good performance for recognition of various objects in numerous computer vision applications. This paper investigates the use of some of the most popular key-point descriptors for face recognition. The emphasis is put on the experimental performance evaluation of the key-point based face recognition methods against some of the most popular and best performing techniques, utilising both global (Eigenfaces) and local (LBP, Gabor filters) information extracted from the whole face image. Most of the results reported in literature so far, on the use of the key-points descriptors for the face recognition, concluded that the methods based on processing of the full face image have somewhat better performances than methods using exclusively key-points. The results reported in this paper suggest that the performance of the key-point based methods could be at least comparable to the leading “whole face” methods and are often better suited to handle face recognition in practical applications, as they do not require face image co-registration, and perform well even with significantly occluded faces. (More)

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Paper citation in several formats:
Klemm, S.; Andreu, Y.; Henriquez, P. and Matuszewski, B. (2015). Robust Face Recognition using Key-point Descriptors. In Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP; ISBN 978-989-758-090-1; ISSN 2184-4321, SciTePress, pages 447-454. DOI: 10.5220/0005314404470454

@conference{visapp15,
author={Soeren Klemm. and Yasmina Andreu. and Pedro Henriquez. and Bogdan J. Matuszewski.},
title={Robust Face Recognition using Key-point Descriptors},
booktitle={Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP},
year={2015},
pages={447-454},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005314404470454},
isbn={978-989-758-090-1},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 10th International Conference on Computer Vision Theory and Applications (VISIGRAPP 2015) - Volume 3: VISAPP
TI - Robust Face Recognition using Key-point Descriptors
SN - 978-989-758-090-1
IS - 2184-4321
AU - Klemm, S.
AU - Andreu, Y.
AU - Henriquez, P.
AU - Matuszewski, B.
PY - 2015
SP - 447
EP - 454
DO - 10.5220/0005314404470454
PB - SciTePress

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