Wonder Ears: Identification of Identical Twins from Ear Images

Hossein Nejati, Li Zhang, Terence Sim, Elisa Martinez Marroquin, Guo Dong Zhou

Research output: A Conference proceeding or a Chapter in BookConference contribution

35 Citations (Scopus)

Abstract

While identical twins identification is a well known challenge in face recognition, it seems that no work has explored automatic ear recognition for identical twin identification. Ear image recognition has been studied for years, but Iannarelli (1989) appears to be the only work mentioning the twin identification (performed manually). We here explore the possibility of automatic twin identification from their ear images based on a psychological model for face recognition in humans, known as Exception Report Model (ERM). We test our approach on 39 pairs of identical twins (78 subjects), with several levels of resolution, occlusion, noise, left vs. right ear, and feature optimization which verifies the robustness of the introduced features.
Original languageEnglish
Title of host publicationInternational Conference on Parttern Recognition (ICPR)
EditorsJan-olof eklundh, Yuichi Ohta, Steven Tanimoto
Place of PublicationJapan
PublisherIEEE, Institute of Electrical and Electronics Engineers
Pages1201-1204
Number of pages4
ISBN (Electronic)9784990644109
ISBN (Print)9781467322164
Publication statusPublished - 11 Nov 2012
Event21st International Conference on Pattern Recognition (ICPR 2012) - Tsukuba, Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012

Conference

Conference21st International Conference on Pattern Recognition (ICPR 2012)
Abbreviated titleICPR 2012
CountryJapan
CityTsukuba
Period11/11/1215/11/12

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    Nejati, H., Zhang, L., Sim, T., Martinez Marroquin, E., & Zhou, G. D. (2012). Wonder Ears: Identification of Identical Twins from Ear Images. In J. eklundh, Y. Ohta, & S. Tanimoto (Eds.), International Conference on Parttern Recognition (ICPR) (pp. 1201-1204). IEEE, Institute of Electrical and Electronics Engineers. https://ieeexplore.ieee.org/document/6460353