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Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images

 
: Boutros, Fadi; Damer, Naser; Terhörst, Philipp; Kirchbuchner, Florian; Kuijper, Arjan

International Society of Information Fusion -ISIF-; Institute of Electrical and Electronics Engineers -IEEE-:
22th International Conference on Information Fusion, FUSION 2019 : 2-5 July 2019, Ottawa, Canada
Piscataway, NJ: IEEE, 2019
ISBN: 978-0-9964527-8-6
ISBN: 978-1-7281-1840-6
8 S.
International Conference on Information Fusion (FUSION) <22, 2019, Ottawa>
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
CRISP; Lead Topic: Smart City; Lead Topic: Visual Computing as a Service; Research Line: Computer vision (CV); biometric fusion; biometrics; face recognition

Abstract
Soft biometrics identify certain traits of individuals based on their sampled biometric characteristics. The automatic identification of traits like age and gender provides valuable information in applications ranging from forensics to service personalization. Color images are stored within a color space containing different channels. Each channel represents a different portion of the information contained in the image, including these of soft biometric patterns. The analysis of the age and gender information in the different channels and different color spaces was not previously studied. This work discusses the soft biometric performances using these channels and analyzes the sample error overlap between all possible channels to successfully prove that different information is considered in the decision making from each channel. We also present a multi-channel selection protocols and fusion solution of the selected channels. Beside the analyzes of color spaces and their channels, our proposed multi-channel fusion solution extends beyond state-of-the-art performance in age estimation on the widely used Adience dataset.

: http://publica.fraunhofer.de/dokumente/N-578727.html