Browse > Article

Statistical Model for Emotional Video Shot Characterization  

박현재 (가톨릭대학교 컴퓨터정보공학부 지능형 멀티미디어 시스템 연구실)
강행봉 (가톨릭대학교 컴퓨터정보공학부 지능형 멀티미디어 시스템 연구실)
Publication Information
The Journal of Korean Institute of Communications and Information Sciences / v.28, no.12C, 2003 , pp. 1200-1208 More about this Journal
Abstract
Affective computing plays an important role in intelligent Human Computer Interactions(HCI). To detect emotional events, it is desirable to construct a computing model for extracting emotion related features from video. In this paper, we propose a statistical model based on the probabilistic distribution of low level features in video shots. The proposed method extracts low level features from video shots and then from a GMM(Gaussian Mixture Model) for them to detect emotional shots. As low level features, we use color, camera motion and sequence of shot lengths. The features can be modeled as a GMM by using EM(Expectation Maximization) algorithm and the relations between time and emotions are estimated by MLE(Maximum Likelihood Estimation). Finally, the two statistical models are combined together using Bayesian framework to detect emotional events in video.
Keywords
Video shot modeling; Low level feature; Emotion detection;
Citations & Related Records
연도 인용수 순위
  • Reference
1 A. Hanjalic, 'Video and Image Retrieval beyond the Cognitive Level: The Needs and Possibilities,' Proc. SPIE Storage and Retrieval for Media Databases, San Jose, pp. 130-140, 200
2 Richard O. Duda, Peter E. Hart, David G. Stork, Pattern classification 2nd Ed., Wiley-interscience
3 Nuno Vasconcelos and Andrew Lippman, 'Statistical Models of Video for Content Analysis and Characterization', IEEE Trans. Image Processing, vol. 9, PP. 3-19, Jan. 2000   DOI   ScienceOn
4 U. Sarkar, S. Ramakrishnan and D. Sarkar, 'Segmenting full-length VBR video into shots for modeling with markov-modulated gamma-based framework', SPIE ITCom 2007, 19-24, Aug. 2001
5 C. Taskiran, C. Bouman, and E. DelP, 'Discovering video structure suing the pseudo-semantic trace', Proc. SPIE Storage and Retrieval for Media Databases 2001, Jan. 2001, PP.571-578
6 A. Hanjalic and L. Xu, 'User-oriented Affective Video Content Analysis', Proc. IEEE Workshop on CBAIBL '01, Kauai, HI, pp50-57, Dec 2001   DOI
7 S. Moncrief, C. Dorai and S. Venkatesh, 'Affect Computing in Film through Sound Energy Dynamics', Proc. ACM MM'01, pp525-527, 2001
8 R. Picard, Affective Computing, MIT Press, 1997
9 Sangkeun Lee, Hayes M.H., III, 'Real-time camera motion classification for content based indexing and retrieval using templates', Proc. 1CASSP '02 , Volume: 4 , 2002 , PP.3664 -3667
10 E. Goldstein, Sensation and perception, Brooks/Cole, 1999
11 C. Dorai and S. Venkatesh eds., Media Computing: Computational Media Aesthetics, Kluwer Academic Publishers, 2002