Performance evaluation of face attribute estimation method using DendroNet

Hiroya Kawai, Koichi Ito, Takafumi Aoki

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

Abstract

There are many studies on face recognition, which identifies a person using distinctive features extracted from a face image. One of the problems in face recognition is that the accuracy of face recognition decreases due to environmental changes such as head pose, emotion, illumination, etc. Addressing this problem, soft biometrics, which uses attributes such as age and gender for person authentication, is expected to improve the accuracy of face recognition. This paper proposes a face attribute estimation method using the Convolutional Neural Network (CNN). The CNN architecture of the proposed method, called DendroNet, is automatically designed according to the relationships among attributes. Though experiments using the CelebA dataset, we demonstrate that the proposed method exhibits better performance than conventional methods.

Original languageEnglish
Title of host publication2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages184-185
Number of pages2
ISBN (Electronic)9781728135755
DOIs
Publication statusPublished - 2019 Oct
Event8th IEEE Global Conference on Consumer Electronics, GCCE 2019 - Osaka, Japan
Duration: 2019 Oct 152019 Oct 18

Publication series

Name2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019

Conference

Conference8th IEEE Global Conference on Consumer Electronics, GCCE 2019
CountryJapan
CityOsaka
Period19/10/1519/10/18

Keywords

  • Attribute
  • Biometrics
  • CNN
  • Face recognition
  • Soft biometrics

ASJC Scopus subject areas

  • Instrumentation
  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Electrical and Electronic Engineering

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  • Cite this

    Kawai, H., Ito, K., & Aoki, T. (2019). Performance evaluation of face attribute estimation method using DendroNet. In 2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019 (pp. 184-185). [9015613] (2019 IEEE 8th Global Conference on Consumer Electronics, GCCE 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/GCCE46687.2019.9015613