Earticle

초록

영어

Recently, due to the introduction of high-tech equipment in interactive exhibits, it became possible to measure various audiences’ responses in the interactive exhibition. Among them, this paper is to predict user’s emotion using the change of the facial features. In other words, the goal of this research is to build the interactive system with the emotion determination model to predict the audience’s response. At this time, as a technique to learn model to predict the response of the audience, we used an Artificial Neural Network-based model. And, as a model to present the emotion state of the audience, we used a Valence-Arousal model. In addition, this paper performed the experiment to compare the proposed model with the multiple regression-based model to see whether it had better performance or not. As a result, although the data set had much noise, we could confirm that the proposed model had better prediction accuracy.

목차

Abstract
 Introduction
 Related Work
  Valence-Arousal Model
  Artificial Neural Network
 Research Model
  System architecture
  The analysis technique of audience’s response: Artificia lNeural Network-based Model
 Experiment design
  Acquiring the audience’s data for analysis
  Select the fields of dependent and independent variables
  Extract significant variables
  Design the experiment of ANN
  Design the comparison model
 Result
 Conclusion
 References

키워드

저자

• Min Kyu Jung [ The School of Management, Kyunghee University ]
• Hyun Chul Ahn [ School of Management Information Systems, Kookmin University ]
• Jae Kyeong Kim [ The School of Management, Kyunghee University ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국경영정보학회 정기 학술대회 [KMIS Conference]

• 간기

  반년간

• 수록기간

  1990~2025

• 십진분류

  KDC 325 DDC 658