loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

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

Affiliations: 1 Universitat Oberta de Catalunya, Spain ; 2 Universitat Autònoma de Barcelona, Spain ; 3 University of Barcelona, Spain

Keyword(s): Face Classification, Incremental Learning, Boosting.

Abstract: Usually face classification applications suffer from two important problems: the number of training samples from each class is reduced, and the final system usually must be extended to incorporate new people to recognize. In this paper we introduce a face recognition method that extends a previous boosting-based classifier adding new classes and avoiding the need of retraining the system each time a new person joins the system. The classifier is trained using the multitask learning principle and multiple verification tasks are trained together sharing the same feature space. The new classes are added taking advantage of the previous learned structure, being the addition of new classes not computationally demanding. Our experiments with two different data sets show that the performance does not decrease drastically even when the number of classes of the base problem is multiplied by a factor of 8.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 52.15.223.239

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Masip, D.; Lapedriza, À. and Vitrià, J. (2008). MULTITASK LEARNING - An Application to Incremental Face Recognition. In Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: OPRMLT; ISBN 978-989-8111-21-0; ISSN 2184-4321, SciTePress, pages 585-590. DOI: 10.5220/0001079205850590

@conference{oprmlt08,
author={David Masip. and Àgata Lapedriza. and Jordi Vitrià.},
title={MULTITASK LEARNING - An Application to Incremental Face Recognition},
booktitle={Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: OPRMLT},
year={2008},
pages={585-590},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0001079205850590},
isbn={978-989-8111-21-0},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISIGRAPP 2008) - Volume 1: OPRMLT
TI - MULTITASK LEARNING - An Application to Incremental Face Recognition
SN - 978-989-8111-21-0
IS - 2184-4321
AU - Masip, D.
AU - Lapedriza, À.
AU - Vitrià, J.
PY - 2008
SP - 585
EP - 590
DO - 10.5220/0001079205850590
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic