Identifying universal facial emotion markers for automatic 3D facial expression recognition

Amal Azazi, Syaheerah Lebai Lutfi, Ibrahim Venkat

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

3 Citations (Scopus)

Abstract

Facial expressions convey human emotions as a simple and effective non-verbal communication method. Motivated by this special characteristic, facial expression recognition rapidly gains attention in social computing fields, especially in Human Computer Interaction (HCI). Identifying the optimal set of facial emotion markers is an important technique that not only reduces the feature vector dimensionality, but also impacts the recognition accuracy. In this paper, we propose a new emotion marker identification algorithm for automatic and person-independent 3D facial expression recognition system. First, we mapped the 3D face images into the 2D plane via conformal geometry to reduce the dimensionality. Then, the identification algorithm is designed to seek the best discriminative markers and the classifier parameters simultaneously by integrating three techniques viz., Differential Evolution (DE), Support Vector Machine (SVM) and Speed Up Robust Feature (SURF). The proposed system yielded an average recognition rate of 79% and outperformed the previous studies using the Bosphorus database.

Original languageEnglish
Title of host publication2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2014
Subtitle of host publicationProceedings
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages6
ISBN (Electronic)9781479943913
DOIs
Publication statusPublished - 1 Jan 2014
Externally publishedYes
Event2014 International Conference on Computer and Information Sciences, ICCOINS 2014 - Kuala Lumpur, Malaysia
Duration: 3 Jun 20145 Jun 2014

Conference

Conference2014 International Conference on Computer and Information Sciences, ICCOINS 2014
CountryMalaysia
CityKuala Lumpur
Period3/06/145/06/14

Keywords

  • 3D facial expression recognition
  • DE
  • Emotion marker identification
  • HCI
  • SURF
  • SVM

Fingerprint Dive into the research topics of 'Identifying universal facial emotion markers for automatic 3D facial expression recognition'. Together they form a unique fingerprint.

Cite this