Journal of the Korea Academia-Industrial cooperation Society (한국산학기술학회논문지)

The Korea Academia-Industrial cooperation Society (한국산학기술학회)
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Detecting Shot Boundaries of Dynamic Images Using Certainty Factors

확신도를 이용한 동영상의 화면변환 감지

  • 장석우 (안양대학교 디지털미디어학과)
  • Received : 2011.11.08
  • Accepted : 2011.12.13
  • Published : 2011.12.31
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Abstract

In this paper, we propose a new method to detect abrupt and gradual shot transitions of video data by using certainty factors. The abrupt transitions denotes cuts and the gradual transitions fade in, fade out, dissolve, horizontal wipes, vertical wipes, Barn Doors, and Iris Rounds. The suggested method first extracts representative features for each shot transition and determines corresponding shot transitions by integrating all the extracted features and inferring adequate transitions. To verify the performance of the proposed shot transition method, experimental results show that the suggested method can detect shot transitions more accurately than existing methods.

본 논문에서는 비디오 데이터에서 확신도 추론을 이용하여 급진적인 화면변환과 점진적인 화면변환을 동시에 검출하는 새로운 방법을 제안한다. 제안된 방법에서 급진적인 화면변환은 컷을 의미하고, 점진적인 화면변환은 페이드 인, 페이드 아웃, 디졸브, 수평 와이프, 수직 와이프, 반도어(Barn Doors), 아이리스 라운드(Iris Round)를 의미한다. 먼저, 각 화면변환을 대표하는 특징을 추출한 후 확신도를 이용하여 특징들을 효과적으로 통합하면서 발생한 화면변환을 추출한다. 실험결과에서는 제안된 방법이 기존의 방법에 비해 여러 가지 종류의 화면변환을 보다 정확하게 추출함을 다양한 비디오 데이터를 이용한 실험을 통해 보여준다.

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References

  1. L.-H. Chen, Y.-C. Lai, and H.-Y. M. Liao, "Movie Scene Segmentation Using Background Information" Pattern Recognition, Vol. 41, No. 3, pp. 1056-1065, 2008. https://doi.org/10.1016/j.patcog.2007.07.024
  2. S. Li and M.-C. Lee, "Effective Detection of Various Wipe Transitions," IEEE Transactions on Circuits and Systems for Video Technology, Vol. 17, No. 6, pp. 663-673, 2007. https://doi.org/10.1109/TCSVT.2007.896621
  3. R. Joyce and B. Liu, "Temporal Segmentation of Video Using Frame and Histogram Space," IEEE Transactions on Multimedia, Vol. 8, No. 1, pp. 130-140, 2006. https://doi.org/10.1109/TMM.2005.861285
  4. R. Zabih, J. Miller, and K. Mai, "A Feature-based Algorithm for Detecting and Classifying Production Effects," Multimedia Systems, Vol. 7, No. 2, pp. 119-128, 1999. https://doi.org/10.1007/s005300050115
  5. C. A. Dhawale1 and S. Jain, "Motion Compensated Video Shot Detection Using Multiple Feature Experts," International Journal of Graphics, Vision, and Image Processing, Vol. 8, No. 5, pp. 1-11, 2009.
  6. P. Campisi, A. Neri, and L. Sorgi, "Wipe Effect Detection for Video Sequences," In Proc. of the IEEE Workshop on Multimedia Signal Processing, pp. 161-164, 2002.
  7. A. F. Smeaton, P. Over, and A. R. Doherty, "Video Shot Boundary Detection: Seven Years of TRECVid Activity,"Computer Vision and Image Understanding, Vol. 114, No. 4, pp. 411-418, 2010. https://doi.org/10.1016/j.cviu.2009.03.011
  8. K. Bunte, M. Biehl, M. F. Jonkman, and N. Petkov, "Learning Effective Color Features for Content Based Image Retrieval in Dermatology," Pattern Recognition, Vol. 44, No. 9, pp. 1892-1902, 2011. https://doi.org/10.1016/j.patcog.2010.10.024
  9. F. Y. Shih, "Image Processing and Pattern Recognition: Fundamentals and Techniques," John Wiley & Sons, 2010.
  10. J. Giarratano, "Expert Systems: Principles and Programming," Third Edition, PWS Publishing Company, 1998.
  11. D. Lelescu, D. Schonfeld, "Statistical Sequential Analysis for Real-Time Video Scene Change Detection on Compressed Multimedia Bitstream," IEEE Transactions on Multimedia, Vol. 5, No. 1, pp. 106-117, 2003. https://doi.org/10.1109/TMM.2003.808819
  12. B. T. Jeon, "A Study on Analyzing Caption Characteristic for Recovering Original Images of Caption Region in TV Scene", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 10, No 4, pp. 177-182, 2010.
  13. Y. K. Jung, "Decision of Gaussian Function Threshold for Image Segmentation", Journal of The Institute of Webcasting, Internet and Telecommunication, Vol 9, No 5, pp. 163-168, 2009.