Which ear regions contribute to identification and to gender classification?
Which ear regions contribute to identification and to gender classification?
Previous studies in biometrics have shown how gender can be determined from images of ears for recognition, but without specificity. In this paper, we use model-based analysis and deep learning methods for gender classification from ear images. We use these methods to determine the differences between female and male ears. We confirm the identification performance and then the gender discrimination before analyzing which ear parts contribute most to performance. To this end, we compare the heatmaps of different genders with identification heatmaps. It appears from the heatmaps that ears encode females and males differently and we show how this can lead to successful gender discrimination and to increase insight into the process of identification of people by their ears. This could lead to gender identification in surveillance imagery, even when the face is concealed and provides a potential focus for future gender research.
gender classification, heatmaps, significant parts
Meng, Di
ec8d62a6-c99c-4fbf-93e3-ff705c6a8279
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
April 2020
Meng, Di
ec8d62a6-c99c-4fbf-93e3-ff705c6a8279
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Nixon, Mark
2b5b9804-5a81-462a-82e6-92ee5fa74e12
Meng, Di, Mahmoodi, Sasan and Nixon, Mark
(2020)
Which ear regions contribute to identification and to gender classification?
In 2020 8th International Workshop on Biometrics and Forensics, IWBF 2020 - Proceedings.
IEEE.
6 pp
.
(doi:10.1109/IWBF49977.2020.9107963).
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Abstract
Previous studies in biometrics have shown how gender can be determined from images of ears for recognition, but without specificity. In this paper, we use model-based analysis and deep learning methods for gender classification from ear images. We use these methods to determine the differences between female and male ears. We confirm the identification performance and then the gender discrimination before analyzing which ear parts contribute most to performance. To this end, we compare the heatmaps of different genders with identification heatmaps. It appears from the heatmaps that ears encode females and males differently and we show how this can lead to successful gender discrimination and to increase insight into the process of identification of people by their ears. This could lead to gender identification in surveillance imagery, even when the face is concealed and provides a potential focus for future gender research.
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Published date: April 2020
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© 2020 IEEE.
Keywords:
gender classification, heatmaps, significant parts
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Local EPrints ID: 439095
URI: http://eprints.soton.ac.uk/id/eprint/439095
PURE UUID: e302fcbb-8d06-4bfe-bc32-ced5ae5c276a
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Date deposited: 03 Apr 2020 16:30
Last modified: 17 Mar 2024 02:33
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Author:
Di Meng
Author:
Sasan Mahmoodi
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