Facial expression recognition based on spatial transformer siamese networks

Shujuan Luo, Ximing Zhang, Yuntao Guo, Sijun Bai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

As the development of the computer vision, we could employ the facial expressions recognition technique in the human-computer interaction domain, such as chatting robot, psychological counselling robot and so on. In this paper, we propose a novel method to jointly learn the facial expression features based the combination of Siamese networks and spatial transformer networks. We posit that learning the features from both networks may make them more robust to the image variation especially illumination and viewpoint variation. Particularly, we construct the structure of the Spatial Transformer Siamese Networks(STSN) and learn the features robust to the facial expression image variation. The experimental results show that the proposed method outperforms the-state-of-art method on the MDLTI-PIE dataset.

Original languageEnglish
Title of host publication2018 IEEE 4th International Conference on Computer and Communications, ICCC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1453-1457
Number of pages5
ISBN (Electronic)9781538683392
DOIs
StatePublished - Dec 2018
Event4th IEEE International Conference on Computer and Communications, ICCC 2018 - Chengdu, China
Duration: 7 Dec 201810 Dec 2018

Publication series

Name2018 IEEE 4th International Conference on Computer and Communications, ICCC 2018

Conference

Conference4th IEEE International Conference on Computer and Communications, ICCC 2018
Country/TerritoryChina
CityChengdu
Period7/12/1810/12/18

Keywords

  • Facial expression recognition
  • Siamese networks
  • Spatial transformer networks

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