TY - GEN
T1 - The emotion prediction model based on audience behavior
AU - Ryoo, Eun Chung
AU - Park, Seung Bo
AU - Kim, Jae Kyeong
PY - 2013
Y1 - 2013
N2 - 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.
AB - 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.
KW - audience behavior
KW - audience's response
KW - emotion prediction;
UR - http://www.scopus.com/inward/record.url?scp=84883770630&partnerID=8YFLogxK
U2 - 10.1109/ICISA.2013.6579443
DO - 10.1109/ICISA.2013.6579443
M3 - Conference contribution
AN - SCOPUS:84883770630
SN - 9781479906031
T3 - 2013 International Conference on Information Science and Applications, ICISA 2013
BT - 2013 International Conference on Information Science and Applications, ICISA 2013
T2 - 2013 4th International Conference on Information Science and Applications, ICISA 2013
Y2 - 24 June 2013 through 26 June 2013
ER -