Age and gender classification from ear images

Dogucan Yaman, Fevziye Irem Eyiokur, Nurdan Sezgin, Hazim Kemal Ekenel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

24 Citations (Scopus)

Abstract

In this paper, we present a detailed analysis on extracting soft biometric traits, age and gender, from ear images. Although there have been a few previous work on gender classification using ear images, to the best of our knowledge, this study is the first work on age classification from ear images. In the study, we have utilized both geometric features and appearancebased features for ear representation. The utilized geometric features are based on eight anthropometric landmarks and consist of 14 distance measurements and two area calculations. The appearance-based methods employ deep convolutional neural networks for representation and classification. The well-known convolutional neural network models, namely, AlexNet, VGG-16, GoogLeNet, and SqueezeNet have been adopted for the study. They have been fine-tuned on a large-scale ear dataset that has been built from the profile and close-to-profile face images in the Multi-PIE face dataset. This way, we have performed a domain adaptation. The updated models have been fine-tuned once more time on the small-scale target ear dataset, which contains only around 270 ear images for training. According to the experimental results, appearance-based methods have been found to be superior to the methods based on geometric features. We have achieved 94% accuracy for gender classification, whereas 52% accuracy has been obtained for age classification. These results indicate that ear images provide useful cues for age and gender classification, however, further work is required for age estimation.

Original languageEnglish
Title of host publicationIWBF 2018 - Proceedings
Subtitle of host publication2018 6th International Workshop on Biometrics and Forensics
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-7
Number of pages7
ISBN (Electronic)9781538613665
DOIs
Publication statusPublished - 29 Jun 2018
Event6th International Workshop on Biometrics and Forensics, IWBF 2018 - Sassari, Italy
Duration: 7 Jun 20188 Jun 2018

Publication series

NameIWBF 2018 - Proceedings: 2018 6th International Workshop on Biometrics and Forensics

Conference

Conference6th International Workshop on Biometrics and Forensics, IWBF 2018
Country/TerritoryItaly
CitySassari
Period7/06/188/06/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE-CONFERENCE. All rights reserved.

Funding

This work was supported by Istanbul Technical University Research Fund, ITU BAP, Project No. MGA-2017-40893.

FundersFunder number
ITU BAP
Istanbul Technical University Research Fund

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