Spontaneous subtle expression detection and recognition based on facial strain

Sze-Teng Liong, John See, Raphael C. W. Phan, Yee Hui Oh, Anh Cat Le Ngo, Kok Sheik Wong, Su Wei Tan

Research output: Contribution to journalArticlepeer-review

35 Citations (Scopus)

Abstract

Optical strain is an extension of optical flow that is capable of quantifying subtle changes on faces and representing the minute facial motion intensities at the pixel level. This is computationally essential for the relatively new field of spontaneous micro-expression, where subtle expressions can be technically challenging to pinpoint. In this paper, we present a novel method for detecting and recognizing micro-expressions by utilizing facial optical strain magnitudes to construct optical strain features and optical strain weighted features. The two sets of features are then concatenated to form the resultant feature histogram. Experiments were performed on the CASME II and SMIC databases. We demonstrate on both databases, the usefulness of optical strain information and more importantly, that our best approaches are able to outperform the original baseline results for both detection and recognition tasks. A comparison of the proposed method with other existing spatio-temporal feature extraction approaches is also presented.

Original languageEnglish
Pages (from-to)170-182
Number of pages13
JournalSignal Processing: Image Communication
Volume47
Early online date14 Jun 2016
DOIs
Publication statusPublished - Sep 2016

Keywords

  • Detection
  • Facial strain
  • Micro-expressions
  • Recognition
  • Subtle expressions

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Electrical and Electronic Engineering

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