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A Supporting Tool for IT System Security Specification Evaluation Based on ISO/IEC 15408 and ISO/IEC 18045 Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Label Distribution Learning Based Age-Invariant Face Recognition

Authors : Hai Huang, Senlin Cheng, Zhong Hong, Liutong Xu

Published in: Trends and Applications in Knowledge Discovery and Data Mining

Publisher: Springer International Publishing

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Abstract

Face recognition is an important application of computer vision. Al-though the accuracy of face recognition is high, face recognition and retrieval across age is still challenging. Faces across age can be very different caused by the aging process over time. The problem is that the images are not too similar, but with the same label. To reduce the intraclass discrepancy, in this paper we pro-pose a new method called Label Distribution learning for the end-to-end neural network to learn more discriminative features. Extensive experiments conducted on the three public domain face aging datasets (MORPH Album 2, CACD-VS and LFW) have shown the effectiveness of the proposed approach.

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Metadata
Title
Label Distribution Learning Based Age-Invariant Face Recognition
Authors
Hai Huang
Senlin Cheng
Zhong Hong
Liutong Xu
Copyright Year
2019
Book
Trends and Applications in Knowledge Discovery and Data Mining

Print ISBN: 978-3-030-26141-2

Electronic ISBN: 978-3-030-26142-9

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-26142-9_19

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