Ecole d'ingénieur et centre de recherche en Sciences du numérique

Improving identification by pruning: a case study on face recognition and body soft biometric

Velardo, Carmelo; Dugelay, Jean-Luc

Research report RR-12-262

We investigate body soft biometrics capabilities to perform pruning of a hard biometrics database improving both retrieval speed and accuracy. Our pre-classification scheme based on anthropometricmeasures is elaborated on a large scale medical dataset to guarantee statistical meaning of the results, and tested in conjunction with a face recognition algorithm. Our assumptions are verified building and testing our system on a chimera dataset. We clearly identify the trade off among pruning, accuracy, and mensuration error of an anthropomeasure based system. Our results show that even in the worst case of ±10% error magnitude in the anthropometric measures, our pruning scheme improves the accuracy performances guaranteeing a speedup of 2×factor.

Document Bibtex

Titre:Improving identification by pruning: a case study on face recognition and body soft biometric
Mots Clés:Soft biometrics, pruning, anthropometric measurements, face recognition
Type:Rapport
Langue:English
Ville:
Date:
Département:Sécurité numérique
Eurecom ref:3593
Copyright: © EURECOM. Personal use of this material is permitted. The definitive version of this paper was published in Research report RR-12-262 and is available at :
Bibtex: @techreport{EURECOM+3593, year = {2012}, title = {{I}mproving identification by pruning: a case study on face recognition and body soft biometric}, author = {{V}elardo, {C}armelo and {D}ugelay, {J}ean-{L}uc}, number = {EURECOM+3593}, month = {01}, institution = {Eurecom}, url = {http://www.eurecom.fr/publication/3593},, }
Voir aussi: