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

Boutros, Fadi and Damer, Naser and Terhörst, Philipp and Kirchbuchner, Florian and Kuijper, Arjan (2019):
Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images.
22nd International Conference on Information Fusion (FUSION), Ottawa, Canada, 02.-05. July, 2019, [Conference or Workshop Item]

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.

Item Type: Conference or Workshop Item
Erschienen: 2019
Creators: Boutros, Fadi and Damer, Naser and Terhörst, Philipp and Kirchbuchner, Florian and Kuijper, Arjan
Title: Exploring the Channels of Multiple Color Spaces for Age and Gender Estimation from Face Images
Language: English
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.

Uncontrolled Keywords: Biometric fusion Biometrics Face recognition
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
20 Department of Computer Science > Mathematical and Applied Visual Computing
Event Title: 22nd International Conference on Information Fusion (FUSION)
Event Location: Ottawa, Canada
Event Dates: 02.-05. July, 2019
Date Deposited: 17 Apr 2020 10:05
Official URL: https://www.fusion2019.org/program.html
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