A Bayesian framework for video affective representation

  title={A Bayesian framework for video affective representation},
  author={Mohammad Soleymani and Joep J. M. Kierkels and Guillaume Chanel and Thierry Pun},
  journal={2009 3rd International Conference on Affective Computing and Intelligent Interaction and Workshops},
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… CONTINUE READING
Highly Cited
This paper has 64 citations. REVIEW CITATIONS

From This Paper

Figures, tables, results, and topics from this paper.

Key Quantitative Results

  • The f1 classification measure of 54.9% that was obtained on three emotional classes with a naïve Bayes classifier was improved to 63.4% after utilizing all the priors.

Explore Further: Topics Discussed in This Paper


Publications citing this paper.
Showing 1-10 of 43 extracted citations

Affect-based adaptive presentation of home videos

ACM Multimedia • 2011
View 4 Excerpts
Highly Influenced

Deep independent audio-visual affect analysis

2017 IEEE Global Conference on Signal and Information Processing (GlobalSIP) • 2017
View 1 Excerpt

65 Citations

Citations per Year
Semantic Scholar estimates that this publication has 65 citations based on the available data.

See our FAQ for additional information.


Publications referenced by this paper.
Showing 1-9 of 9 references

, " Evidence for A 3 - Factor Theory of Emotions

A. Mehrabian
J . of Research in Personality • 2006

Affective understanding in film

IEEE Transactions on Circuits and Systems for Video Technology • 2006

Sparse Bayesian Learning and the Relevance Vector Machine

George House, Guildhall StreetCambridge

On the use of computable features for film classification

Y. Sheikh, M. Shah
IEEE Trans . on Circuits and Systems for Video Technology

Similar Papers

Loading similar papers…