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An Effective Detection Algorithm of Shot Boundaries in Animations

애니메이션의 효과적인 장면경계 검출 알고리즘

  • 장석우 (안양대학교 디지털미디어학과) ;
  • 정명희 (안양대학교 디지털미디어학과)
  • Received : 2011.05.31
  • Accepted : 2011.08.11
  • Published : 2011.08.31

Abstract

A cell animation is represented by one background cell, and there is much difference of images when its shot is changed. Also, it does not have a lot of colors since people themselves draw it. In order to effectively detect shot transitions of cell animations while fully considering their intrinsic characteristics, in this paper, we propose a animation shot boundary detection algorithm that utilizes color and block-based histograms step by step. The suggested algorithm first converts RGB color space into HSI color one, and coarsely decides if adjacent frames contains a shot transition by performing color difference operation between two images. If they are considered to have a shot transition candidate, we calculate color histograms for 9 sub-regions of the adjacent images and apply weights to them. Finally, we determine whether there is a real shot transition by analyzing the weighted sum of histogram values. In experiments, we show that our method is superior to others.

셀 애니메이션은 배경이 하나의 셀로 표현되고, 장면이 변화될 경우에는 배경이 변경되기 때문에 장면전환시 비교적 큰 변화가 일어난다. 그리고 실제로 카메라를 이용하여 촬영한 영상과는 달리 사람이 직접 그리다 보니 사용된 색상의 종류 또한 그렇게 많지 않다. 본 논문에서는 애니메이션의 이러한 특성을 최대한 반영하고 보다 효과적으로 셀 애니메이션의 장면전환을 검출하기 위해서 색상과 블록 단위의 히스토그램을 단계적으로 활용하는 새로운 애니메이션의 장면전환 검출 기법을 제안한다. 제안된 알고리즘은 연속적으로 입력되는 애니메이션 영상을 받아들인 후 먼저 칼라공간을 HSI 공간으로 변형하고, 두 영상 사이의 색상 값의 차연산을 수행하여 인접한 영상이 장면전환 후보인지를 1차적으로 판단한다. 만일, 인접한 영상이 장면전환 후보군으로 판단되면 부 영역별로 색상 히스토그램을 작성하고, 여기에 가중치를 적용하여 장면전환이 발생했는지의 유무를 최종적으로 판단한다. 본 논문의 실험에서는 제안된 애니메이션의 장면전환 검출 방법이 기존의 장면전환 검출 방법에 비해 보다 우수하다는 것을 보인다.

Keywords

References

  1. S.-H. Lee, S.-O. Yang, and Y.-T. Paik, "Multimedia," Jungil Books, March 2005.
  2. S.-W. Jang, G.-Y. Kim, and H. I. Choi, "Shot Transition Detection by Compensating for Global and Local Motions," In Proceedings of the International Conference on Fuzzy Systems and Knowledge Discovery, pp. 1061-1066, 2005.
  3. A.F. Smeaton, P. Over, A.R. Doherty, "Video Shot Boundary Detection: Seven Years of TRECVid Activity," Computer Vision and Image Understanding, Vol. 114, No. 4, pp. 411-418, 2011.
  4. M.-S. Lee, Y.-M. Yang, and S.-W. Lee, "Auto- matic Video Parsing Using Shot Boundary Detection and Camera Operation Analysis," Pattern Recognition, Vol. 34, No. 3, pp. 711-719, March 2001. https://doi.org/10.1016/S0031-3203(00)00007-8
  5. C. C. Lo and S. J. Wang, "A Histogram-based Moment-Preserving Clustering Algorithm for Video Segmentation," Pattern Recognition Letters, Vol. 24, No. 14, pp. 2209-2218, October 2003. https://doi.org/10.1016/S0167-8655(03)00048-5
  6. H. J. Zhang, A. Kankanhalli, and S. W. Smoliar, "Automatic Partitioning of Full-motion Video," Multimedia Systems, Vol. 1, No. 1, pp. 10-28, 1993. https://doi.org/10.1007/BF01210504
  7. T. Y. Liu, K. T. Lo, X. D. Zhang, and J. Feng, "A New Cut Detection Algorithm with Constant False-Alarm Ratio for Video Segmentation," Journal of Visual Communication and Image Representation, Vol. 15, No. 2, pp. 132-144, 2004. https://doi.org/10.1016/j.jvcir.2003.10.001
  8. C. A. Dhawale and S. Jain, "Motion Compensated Video Shot Detection Using Multiple Feature Experts," ICGST International Journal on Graphics, Vision, and Image Processing, Vol. 8, No. 5, pp. 1-11, 2009.
  9. Y.-U. Han, S.-I. Jung, S.-J. Kim, S.-Y. Lee, and S.-H. Kim, "Improving Histogram Scene Change Detection Method Using Motion Vector," In Proceedings of the Fall Conference of the Korea Institute of Information Scientists and Engineers, Vol. 26, No. 2, pp. 410-412, 1999.
  10. F. Perez and C Koch, "Toward Color Image Segmentation in Analog VLSI: Algorithm and Hardware," International Journal of Computer Vision, Vol. 12, No. 1, pp. 17-42, 1994. https://doi.org/10.1007/BF01420983
  11. K. S. Tana and N. A. M. Isa, "Color Image Segmentation Using Histogram Thresholding-Fuzzy C-Means Hybrid Approach," Pattern Recognition, Vol. 44, No. 1, pp. 1-15, 2011. https://doi.org/10.1016/j.patcog.2010.07.013