Deep face recognition under eyeglass and scale variation using extended siamese network

Fan Qiu, Sei Ichiro Kamata, Lizhuang Ma

研究成果

1 被引用数 (Scopus)

抄録

Face recognition has attracted much attention from researchers for past decades. Recently, with the development of deep learning, a deep neural network is adopted by face recognition system and better performance is obtained. Many works on metric learning have been done in the deep neural network. Meanwhile, there are several variation problems existing in face recognition, such as profile face image, low-resolution face image, different age of face image, face image wearing eyeglass, etc. In this paper, targeting at different kinds of variation problems, we proposed a novel network structure, called Extended Siamese Network. Another contribution is that a new loss function is proposed, to further take inter-class information into account based on the center loss function. The experiments show that recognition accuracy is improved in comparison with the other state-of-Art methods.

本文言語English
ホスト出版物のタイトルProceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017
出版社Institute of Electrical and Electronics Engineers Inc.
ページ471-476
ページ数6
ISBN(電子版)9781538633540
DOI
出版ステータスPublished - 2018 12 13
イベント4th Asian Conference on Pattern Recognition, ACPR 2017 - Nanjing, China
継続期間: 2017 11 262017 11 29

出版物シリーズ

名前Proceedings - 4th Asian Conference on Pattern Recognition, ACPR 2017

Other

Other4th Asian Conference on Pattern Recognition, ACPR 2017
国/地域China
CityNanjing
Period17/11/2617/11/29

ASJC Scopus subject areas

  • 人工知能
  • コンピュータ ビジョンおよびパターン認識
  • 信号処理

フィンガープリント

「Deep face recognition under eyeglass and scale variation using extended siamese network」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル