Please use this identifier to cite or link to this item:
Title: Fused intra-bimodal face verification approach based on Scale-Invariant Feature Transform and a vocabulary tree
Authors: Travieso, Carlos M. 
Del Pozo-Banos, Marcos
Alonso, Jesus B. 
UNESCO Clasification: 3307 Tecnología electrónica
Keywords: Bimodal interaction, Information fusion, Visible and thermal face verification, Face detection, SIFT parameters, Vocabulary tree
Issue Date: 2014
Publisher: 0167-8655
Journal: Pattern Recognition Letters 
Abstract: This work studies the intra-bimodal face-based biometric fusion approach composed of the thermal and spatial domains. The distinctive feature of this work is the use of a single camera with two sensors which returns a unique image with thermal and visual images at a time, as opposed to the-state-of-the-art, for example the multibiometric modalities and hyperspectral images. The proposed system represents a practical bimodal approach for real applications. It is composed by a verification architecture based on the Scale-Invariant Feature Transform algorithm (SIFT) with a vocabulary tree, providing a scheme that scales efficiently to a large number of features. The image database consists of front-view thermal and visual image as a single image, which contain facial temperature distributions of 41 different individuals in 2-dimensional format and 18 images per subject, acquired on three different-day sessions. Results showed that visible images gives better accuracy than thermal information, and with independency of range, head images give the most discriminative information. Besides, fusion approaches reached better accuracy, up to 99.45% for score fusion and 100% for decision fusion. This shows the independency of information between visual and thermal images and the robustness of bimodal interaction.
ISSN: 0167-8655
DOI: 10.1016/j.patrec.2013.08.016
Source: Pattern Recognition Letters[ISSN 0167-8655],v. 36, p. 254-260
Appears in Collections:Artículos
Show full item record


checked on May 19, 2024


checked on Feb 25, 2024

Page view(s)

checked on Mar 9, 2024

Google ScholarTM




Export metadata

Items in accedaCRIS are protected by copyright, with all rights reserved, unless otherwise indicated.