Notice of Retraction: Human emotional states modeling by Hidden Markov Model

Teik Toe Teoh, Siu Yeung Cho

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

5 Citations (Scopus)

Abstract

This paper presents an attempt of using Hidden Markov Model to model the high level emotions (such as, encouraging, interest, unsure, disagreeing and discouraging) through low level facial expressions (such as, happy, sad, surprise and neutral). The rationale behind using HMM is that the HMM models human brain as human emotion is quite complex, naturally a human instinct contain hidden layer as well (like sub conscious mind). In addition, Markov state chain property is good to model human emotion as our emotion is also through our mind state that it is always dependent on our previous state of our emotion and current event will end up our current emotion state. Our proposed work is to develop an emotion indexer acting as a higher level analysis to interpret more advanced emotional states out of the basic emotions.

Original languageEnglish
Title of host publicationProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
PublisherIEEE Computer Society
Pages908-912
Number of pages5
ISBN (Print)9781424499533
DOIs
Publication statusPublished - 2011
Externally publishedYes
Event2011 7th International Conference on Natural Computation, ICNC 2011 - Shanghai, China
Duration: 26 Jul 201128 Jul 2011

Publication series

NameProceedings - 2011 7th International Conference on Natural Computation, ICNC 2011
Volume2

Conference

Conference2011 7th International Conference on Natural Computation, ICNC 2011
Country/TerritoryChina
CityShanghai
Period26/07/1128/07/11

Keywords

  • Emotion
  • Facial Expressions
  • Hidden Markov Model

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Neuroscience (all)

Fingerprint

Dive into the research topics of 'Notice of Retraction: Human emotional states modeling by Hidden Markov Model'. Together they form a unique fingerprint.

Cite this