TY - GEN
T1 - The first audio/visual emotion challenge and workshop – an introduction
AU - Schuller, Björn
AU - Valstar, Michel
AU - Cowie, Roddy
AU - Pantic, Maja
N1 - Publisher Copyright:
© Springer-Verlag Berlin Heidelberg 2011.
PY - 2011
Y1 - 2011
N2 - The Audio/Visual Emotion Challenge and Workshop (http://sspnet. eu/avec2011) is the first competition event aimed at comparison of automatic audio, visual, and audiovisual emotion analysis. The goal of the challenge is to provide a common benchmark test set for individual multimodal information processing and to bring together the audio and video emotion recognition communities, to compare the relative merits of the two approaches to emotion recognition under well-defined and strictly comparable conditions, and establish to what extent fusion of the approaches is possible and beneficial. A second motivation is the need to advance emotion recognition systems to be able to deal with naturalistic behavior in large volumes of un-segmented, non-prototypical and non-preselected data as this is exactly the type of data that real systems have to face in the real world. Three emotion detection sub-challenges were addressed: emotion detection from audio, from video, or from audiovisual information. As benchmarking database the SEMAINE database of naturalistic dialogues was used. Emotion needed to be recognized in terms of positive/negative valence, and high and low activation (arousal), expectancy, and power.
AB - The Audio/Visual Emotion Challenge and Workshop (http://sspnet. eu/avec2011) is the first competition event aimed at comparison of automatic audio, visual, and audiovisual emotion analysis. The goal of the challenge is to provide a common benchmark test set for individual multimodal information processing and to bring together the audio and video emotion recognition communities, to compare the relative merits of the two approaches to emotion recognition under well-defined and strictly comparable conditions, and establish to what extent fusion of the approaches is possible and beneficial. A second motivation is the need to advance emotion recognition systems to be able to deal with naturalistic behavior in large volumes of un-segmented, non-prototypical and non-preselected data as this is exactly the type of data that real systems have to face in the real world. Three emotion detection sub-challenges were addressed: emotion detection from audio, from video, or from audiovisual information. As benchmarking database the SEMAINE database of naturalistic dialogues was used. Emotion needed to be recognized in terms of positive/negative valence, and high and low activation (arousal), expectancy, and power.
UR - http://www.scopus.com/inward/record.url?scp=84964937579&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-24571-8_42
DO - 10.1007/978-3-642-24571-8_42
M3 - Conference contribution
AN - SCOPUS:84964937579
SN - 9783642245701
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 322
BT - Affective Computing and Intelligent Interaction - 4th International Conference, ACII 2011, Proceedings
A2 - D’Mello, Sidney
A2 - Graesser, Arthur
A2 - Schuller, Bjorn
A2 - Martin, Jean-Claude
PB - Springer Verlag
T2 - 4th International Conference on Affective Computing and Intelligent Interaction, ACII 2011
Y2 - 9 October 2011 through 12 October 2011
ER -