A local experts organization model with application to face emotion recognition

Jia Jun Wong, Siu Yeung Cho

Research output: Journal PublicationArticlepeer-review

24 Citations (Scopus)

Abstract

This paper presents a novel approach for recognizing human facial emotion in order to further detect human suspicious behaviors. Instead of relying on relative poor representation of facial features in a flat vector form, the approach utilizes a format of tree structures with Gabor feature representations to present a facial emotional state. The novel local experts organization (LEO) model is proposed for the processing of this tree structure representation. The motivation for the LEO model is to deal with the inconsistent length of features in case there are some features failed to be detected. The proposed LEO model is inspired by the natural hierarchical model presented in natural organization, where workers (local experts) reports to their supervisor (fusion classifier), whom in turn reports to upper management (global fusion classifier). Moreover, an Asian emotion database is created. The database contains high-resolution images of 153 Asian subjects in six basic pseudo-emotions (excluding neutral expression) in three different poses for evaluating our proposed system. Empirical studies were conducted to benchmark our approach with other well-known classifiers applying to the system, and the results showed that our approach is the most robust, and less affected by noise from feature locators for the face emotion recognition system.

Original languageEnglish
Pages (from-to)804-819
Number of pages16
JournalExpert Systems with Applications
Volume36
Issue number1
DOIs
Publication statusPublished - Jan 2009
Externally publishedYes

Keywords

  • Emotion recognition
  • Face emotion tree structure
  • Local experts organization model
  • Polynomial classifier
  • Support vector machines

ASJC Scopus subject areas

  • General Engineering
  • Computer Science Applications
  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'A local experts organization model with application to face emotion recognition'. Together they form a unique fingerprint.

Cite this