University of Oulu

Y. Zhou and S. Zaferiou, "Deformable Models of Ears in-the-Wild for Alignment and Recognition," 2017 12th IEEE International Conference on Automatic Face & Gesture Recognition (FG 2017), Washington, DC, 2017, pp. 626-633. doi: 10.1109/FG.2017.79

Deformable models of ears in-the-wild for alignment and recognition

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Author: Zhou, Yuxiang1; Zaferiou, Stefanos1,2
Organizations: 1Department of Computing, Imperial College London, U.K.
2Centre for Machine Vision and Signal Analysis, University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 5.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2019100330980
Language: English
Published: Institute of Electrical and Electronics Engineers, 2017
Publish Date: 2019-10-03
Description:

Abstract

Ears have been discovered to have biometric importance for identifying people and/or verifying their identity. This is largely because of their complex inner shape structure, which is not only unique but also long-lasting regardless of ageing. In this paper, we make two important contributions relevant to analysis of ear in imagery captured in unconstrained conditions. That is, we present (a) the first, to the best of our knowledge, annotated database with ear landmarks and use it in order to build statistical deformable ear models in-the-wild and (b) a database of 2058 labelled unconstrained ear images with 231 subjects and use it for ear recognition/verification. We perform extensive comparisons for ear alignment using many state-of-the-art techniques and extensive experiments. Finally, we conducted extensive experiments for ear recognition using both handcrafted, as well as learned features (i.e., using deep learning). All annotated data and code will be publicly available.

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ISBN: 978-1-5090-4023-0
ISBN Print: 978-1-5090-4024-7
Pages: 626 - 633
DOI: 10.1109/FG.2017.79
OADOI: https://oadoi.org/10.1109/FG.2017.79
Host publication: IEEE International Conference on Automatic Face and Gesture Recognition and Workshops
Conference: IEEE International Conference on Automatic Face and Gesture Recognition
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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