University of Oulu

X. Wu, E. Boutellaa, M. B. López, X. Feng and A. Hadid, "On the usefulness of color for kinship verification from face images," 2016 IEEE International Workshop on Information Forensics and Security (WIFS), Abu Dhabi, 2016, pp. 1-6. doi: 10.1109/WIFS.2016.7823901

On the usefulness of color for kinship verification from face images

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Author: Wu, Xiaoting1; Boutellaa, Elhocine2; Bordallo López, Miguel3;
Organizations: 1Northwestern Polytechnical University, School of Electronics and Information, Xi’an, China
2Division Architecture des Systemes et Multimedia, Centre de Developpement des Technologies Avancees CDTA, Algeria
3Center for Machine Vision and Signal Analysis, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.8 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019090526775
Language: English
Published: Institute of Electrical and Electronics Engineers, 2016
Publish Date: 2019-09-05
Description:

Abstract

Automatic kinship verification from faces aims to determine whether two persons have a biological kin relation or not by comparing their facial attributes. This is a challenging research problem that has recently received lots of attention from the research community. However, most of the proposed methods have mainly focused on analyzing only the luminance (i.e. gray-scale) of the face images, hence discarding the chrominance (i.e. color) information which can be a useful additional cue for verifying kin relationships. This paper investigates for the first time the usefulness of color information in the verification of kinship relationships from facial images. For this purpose, we extract joint color-texture features to encode both the luminance and the chrominance information in the color images. The kinship verification performance using joint color-texture analysis is then compared against counterpart approaches using only gray-scale information. Extensive experiments using different color spaces and texture features are conducted on two benchmark databases. Our results indicate that classifying color images consistently shows superior performance in three different color spaces.

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ISBN: 978-1-5090-1138-4
ISBN Print: 978-1-5090-1139-1
Pages: 1 - 6
DOI: 10.1109/WIFS.2016.7823901
OADOI: https://oadoi.org/10.1109/WIFS.2016.7823901
Host publication: IEEE International Workshop on Information Forensics and Security
Conference: 2016 IEEE International Workshop on Information Forensics and Security (WIFS)
Type of Publication: A4 Article in conference proceedings
Field of Science: 113 Computer and information sciences
213 Electronic, automation and communications engineering, electronics
Subjects:
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