The emotion prediction model based on audience behavior

Eun Chung Ryoo, Seung Bo Park, Jae Kyeong Kim

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

1 Citation (Scopus)

Abstract

Emotion-based behavior includes information about the audience's emotions and feelings. To analysis audience's behavior allows us to predict emotional state of the audience, and enable to easily understand the feeling of being each other's feelings, knowledge, and information. To recognize the real human emotions, the emotions are recognized through a variety of biological signals rather than only a specific signal. Thus, research is needed to analyze biological signals using a variety of techniques and sensors. Therefore, in this study, we would construct the emotion prediction model in two ways using emotion-specific behaviors, and compare its performance. The proposed model consists of three steps. 1) Collect audience images by camera as five emotional stimuli, 2) Extract characteristics of emotional behavior using difference image technique, and 3) construct emotion prediction model in two ways and compare its performance. It is expected that the proposed model constructed in this study will be able to identify the characteristics of the audience behavior and suggest more effective ways of interacting with the audience.

Original languageEnglish
Title of host publication2013 International Conference on Information Science and Applications, ICISA 2013
DOIs
Publication statusPublished - 2013
Event2013 4th International Conference on Information Science and Applications, ICISA 2013 - Pattaya, Thailand
Duration: 24 Jun 201326 Jun 2013

Publication series

Name2013 International Conference on Information Science and Applications, ICISA 2013

Conference

Conference2013 4th International Conference on Information Science and Applications, ICISA 2013
Country/TerritoryThailand
CityPattaya
Period24/06/1326/06/13

Keywords

  • audience behavior
  • audience's response
  • emotion prediction;

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