Human centric facial expression recognition

K. Clawson, L. S. Delicato, C. Bowerman

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

1 Citation (Scopus)

Abstract

Facial expression recognition (FER) is an area of active research, both in computer science and in behavioural science. Across these domains there is evidence to suggest that humans and machines find it easier to recognise certain emotions, for example happiness, in comparison to others. Recent behavioural studies have explored human perceptions of emotion further, by evaluating the relative contribution of features in the face when evaluating human sensitivity to emotion. It has been identified that certain facial regions have more salient features for certain expressions of emotion, especially when emotions are subtle in nature. For example, it is easier to detect fearful expressions when the eyes are expressive. Using this observation as a starting point for analysis, we similarly examine the effectiveness with which knowledge of facial feature saliency may be integrated into current approaches to automated FER. Specifically, we compare and evaluate the accuracy of 'full-face' versus upper and lower facial area convolutional neural network (CNN) modelling for emotion recognition in static images, and propose a human centric CNN hierarchy which uses regional image inputs to leverage current understanding of how humans recognise emotions across the face. Evaluations using the CK+ dataset demonstrate that our hierarchy can enhance classification accuracy in comparison to individual CNN architectures, achieving overall true positive classification in 93.3% of cases.

Original languageEnglish
Title of host publicationProceedings of the 32nd International BCS Human Computer Interaction Conference (HCI 2018)
PublisherBCS Learning and Development Ltd.
Pages1-12
Number of pages13
DOIs
Publication statusPublished - Jul 2018
Event32nd International BCS Human Computer Interaction Conference 2018 - Belfast, United Kingdom
Duration: 4 Jul 20186 Jul 2018

Conference

Conference32nd International BCS Human Computer Interaction Conference 2018
Abbreviated titleHCI 2018
CountryUnited Kingdom
CityBelfast
Period4/07/186/07/18

Keywords

  • Convolutional Neural Network
  • Deep Learning
  • Emotion Recognition
  • Facial Expression Recognition

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Human-Computer Interaction
  • Artificial Intelligence

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