A Bayesian framework for video affective representation
- 1 September 2009
- conference paper
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
Abstract
Emotions that are elicited in response to a video scene contain valuable information for multimedia tagging and indexing. The novelty of this paper is to introduce a Bayesian classification framework for affective video tagging that allows taking contextual information into account. A set of 21 full length movies was first segmented and informative content-based features were extracted from each shot and scene. Shots were then emotionally annotated, providing ground truth affect. The arousal of shots was computed using a linear regression on the content-based features. Bayesian classification based on the shots arousal and content-based features allowed tagging these scenes into three affective classes, namely calm, positive excited and negative excited. To improve classification accuracy, two contextual priors have been proposed: the movie genre prior, and the temporal dimension prior consisting of the probability of transition between emotions in consecutive scenes. The f1 classification measure of 54.9% that was obtained on three emotional classes with a nai¿ve Bayes classifier was improved to 63.4% after utilizing all the priors.Keywords
This publication has 15 references indexed in Scilit:
- Hierarchical movie affective content analysis based on arousal and valence featuresPublished by Association for Computing Machinery (ACM) ,2008
- Valence-arousal evaluation using physiological signals in an emotion recall paradigmPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2007
- Information-theoretic temporal segmentation of video and applications: multiscale keyframes selection and shot boundaries detectionMultimedia Tools and Applications, 2006
- Extracting moods from pictures and sounds: towards truly personalized TVIEEE Signal Processing Magazine, 2006
- Affect-based indexing and retrieval of filmsPublished by Association for Computing Machinery (ACM) ,2005
- Affective video content representation and modelingIEEE Transactions on Multimedia, 2005
- 10.1162/15324430152748236Applied Physics Letters, 2000
- Effects of color on emotions.Journal of Experimental Psychology: General, 1994
- Looking at pictures: Affective, facial, visceral, and behavioral reactionsPsychophysiology, 1993
- Evidence for a three-factor theory of emotionsJournal of Research in Personality, 1977