Abstract
Predicting the emotional response of movie audiences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience's perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and induced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and behavioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction.
| Original language | English |
|---|---|
| Title of host publication | The 7th International Conference on Affective Computing and Intelligent Interaction (ACII 2017) |
| Subtitle of host publication | San Antonio, Texas October 23-26, 2017 |
| Editors | Hayley Hung, Emily Mower Provost, Mohammad Soleymani |
| Place of Publication | Piscataway NJ USA |
| Publisher | IEEE, Institute of Electrical and Electronics Engineers |
| Pages | 28-35 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781538605639 |
| ISBN (Print) | 9781538605646 |
| DOIs | |
| Publication status | Published - 2017 |
| Externally published | Yes |
| Event | International Conference on Affective Computing and Intelligent Interaction 2017 - San Antonio, United States of America Duration: 23 Oct 2017 → 26 Oct 2017 Conference number: 7th http://acii2017.org/Home |
Conference
| Conference | International Conference on Affective Computing and Intelligent Interaction 2017 |
|---|---|
| Abbreviated title | ACII 2017 |
| Country | United States of America |
| City | San Antonio |
| Period | 23/10/17 → 26/10/17 |
| Internet address |
Cite this
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Recognizing induced emotions of movie audiences : are induced and perceived emotions the same? / Tian, Leimin; Muszynski, Michal; Lai, Catherine; Moore, Johanna D.; Kostoulas, Theodoras; Lombardo, Patrizia; Pun, Thierry; Chanel, Guillaume.
The 7th International Conference on Affective Computing and Intelligent Interaction (ACII 2017): San Antonio, Texas October 23-26, 2017. ed. / Hayley Hung; Emily Mower Provost; Mohammad Soleymani. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 28-35.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research
TY - GEN
T1 - Recognizing induced emotions of movie audiences
T2 - are induced and perceived emotions the same?
AU - Tian, Leimin
AU - Muszynski, Michal
AU - Lai, Catherine
AU - Moore, Johanna D.
AU - Kostoulas, Theodoras
AU - Lombardo, Patrizia
AU - Pun, Thierry
AU - Chanel, Guillaume
PY - 2017
Y1 - 2017
N2 - Predicting the emotional response of movie audiences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience's perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and induced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and behavioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction.
AB - Predicting the emotional response of movie audiences to affective movie content is a challenging task in affective computing. Previous work has focused on using audiovisual movie content to predict movie induced emotions. However, the relationship between the audience's perceptions of the affective movie content (perceived emotions) and the emotions evoked in the audience (induced emotions) remains unexplored. In this work, we address the relationship between perceived and induced emotions in movies, and identify features and modelling approaches effective for predicting movie induced emotions. First, we extend the LIRIS-ACCEDE database by annotating perceived emotions in a crowd-sourced manner, and find that perceived and induced emotions are not always consistent. Second, we show that dialogue events and aesthetic highlights are effective predictors of movie induced emotions. In addition to movie based features, we also study physiological and behavioural measurements of audiences. Our experiments show that induced emotion recognition can benefit from including temporal context and from including multimodal information. Our study bridges the gap between affective content analysis and induced emotion prediction.
UR - http://www.scopus.com/inward/record.url?scp=85041192587&partnerID=8YFLogxK
U2 - 10.1109/ACII.2017.8273575
DO - 10.1109/ACII.2017.8273575
M3 - Conference Paper
SN - 9781538605646
SP - 28
EP - 35
BT - The 7th International Conference on Affective Computing and Intelligent Interaction (ACII 2017)
A2 - Hung, Hayley
A2 - Mower Provost, Emily
A2 - Soleymani, Mohammad
PB - IEEE, Institute of Electrical and Electronics Engineers
CY - Piscataway NJ USA
ER -