Age-invariant person identification by segmentation verification of face image

Yuta Somada, Wataru Oyama, Tetsushi Wakabayashi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Face recognition has been a major research theme over the last two decades. There are several problems to be solved to improve the performance of face recognition. Such major problems involve appearance variation due to pose, illumination, expression, and aging. In particular, aging includes internal and external factors that cause facial appearance variation and, consequently, it is the most difficult problem to handle. In this paper, we propose a face recognition method that is robust against facial appearance variation due to aging. The proposed method employs segmentation verification of frontal face images that consists of the following three steps. (1) Face image segmentation generates three regional subimages from the input face image. (2) A matching score is calculated using gradient features from a pair consisting of the input image and a registered image for each of the three generated subimages and original (whole face) image. We obtain four matching scores. (3) The verifying classifier evaluates the matching score vector formed of the matching scores calculated for each of the four images and predicts the a posteriori probability that two matching images belong to the same person. The results of an experimental evaluation with the FGNET and MORPH face aging datasets clarify the effectiveness of the proposed method for age invariant face recognition

Original languageEnglish
Title of host publicationProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages364-369
Number of pages6
ISBN (Electronic)9781538633540
DOIs
Publication statusPublished - Dec 13 2018
Externally publishedYes
Event4th Asian Conference on Pattern Recognition, ACPR 2017 - Nanjing, China
Duration: Nov 26 2017Nov 29 2017

Publication series

NameProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017

Other

Other4th Asian Conference on Pattern Recognition, ACPR 2017
CountryChina
CityNanjing
Period11/26/1711/29/17

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All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Vision and Pattern Recognition
  • Signal Processing

Cite this

Somada, Y., Oyama, W., & Wakabayashi, T. (2018). Age-invariant person identification by segmentation verification of face image. In Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017 (pp. 364-369). [8575850] (Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ACPR.2017.157