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A Study on 3D Visualization for Color Analysis of Multimedia Data

멀티미디어 데이터의 색상분포 분석을 통한 3차원 시각화 연구

  • 서상현 (성결대학교 미디어소프트웨어학부)
  • Received : 2018.07.28
  • Accepted : 2018.08.28
  • Published : 2018.08.31

Abstract

The development of multimedia devices with built-in cameras such as smart devices and various studies using video-related multimedia data such as images and video obtained from the devices have been actively conducted. These studies deal with image data. An image can be defined as a set of color information obtained from a digital sensor called a pixel. Images contain various cognitive information such as color, lighting, objects and so on. In order to extract or process such information, it is necessary to clearly understand the composition of colors. In this paper, we introduce 3-dimensional information visualization method which can effectively express the results of image processing together with color distribution. This study visualizes the characteristics of image related multimedia data as well as the characteristics of various analytical data derived from it, so that researchers can transmit the image information more clearly and effectively.

스마트기기와 같은 카메라를 내장한 멀티미디어 기기의 발달과 함께 그 기기로부터 얻어지는 영상관련 멀티미디어 데이터(이미지, 동영상)를 활용한 다양한 연구들이 활발히 진행되고 있다. 이러한 연구들은 이미지 데이터를 다루고 있으며 이미지들은 화소라고 하는 디지털 센서로부터 얻어지는 색상정보들의 집합으로 정의될 수 있다. 이미지에는 색, 조명, 객체 등 다양한 인지 정보가 들어있으며 이러한 정보들을 추출하거나 가공하기위해서는 색의 구성을 명확히 이해할 필요가 있다. 본 논문에서는 영상의 정보와 함께 영상처리 연구들의 결과물을 효과적으로 표현할 수 있는 3차원 정보시각화 방법을 소개한다. 본 연구는 영상관련 멀티미디어 데이터의 특징은 물론 그로부터 나오는 다양한 분석 데이터들의 특징정보를 직관적으로 이해할 수 있도록 시각화하여 연구자들에게 영상 정보를 보다 명확하고 효과적으로 전달할 수 있도록 하였다.

Keywords

References

  1. Ware, C., Information Visualization, Third Edition: Perception for Design (Interactive Technologies), 3rd Edition, Morgan Kaufman, 2012.
  2. Moreland, K., "A survey of visualization pipelines", IEEE Transactions on Visualization and Computer Graphics, Vol. 19. No.3, pp.367-378, 2013. https://doi.org/10.1109/TVCG.2012.133
  3. Liu, S., Cui,W., Wu, Y., and Liu, M., "A survey on information visualization: recent advances and challenges," The Visual Computer, Vol. 20, No.12, pp.1373-1393, 2014
  4. C. Lee and S Seo, "3D interactive visualization using image color distribution," International Journal of Engineering & Technology, Vol.7, No.2.33, pp.397-400, June. 2018.
  5. Wee, M. C., "An improved diversity visualization system for multivariate data". Journal of Visualziation, Vol.20, No.1, pp.163-179, 2017. https://doi.org/10.1007/s12650-016-0380-8
  6. Spence and Robert, Information Visualization, ACM press Books, 2001.
  7. Chen, T., Lu, A., &Hu, S.-M., "Visual storylines: semantic visualization of movie sequence," Computer&Graphics, Vol. 36, No.4, pp.241-249, 2012. https://doi.org/10.1016/j.cag.2012.02.010
  8. S. Kim, "Methods to Maximize 3D Space Usage in Information Visualization," Journal of Digital Design, Vol. 16, No. 3, pp. 11-20, 2016.
  9. A.J. Pretorius, M.-A. Bray, A.E. Carpenter and R.A. Ruddle, "Visualizationof parameter space for image analysis," IEEE Transactions on Visualization and Computer Graphics, Vol.17, No.12, pp.2402-2411, 2011. https://doi.org/10.1109/TVCG.2011.253
  10. R.C. Gonzalez and R.E. Woods, Digital Image Processing, Prentice Hall, 2002.
  11. I. Lee, C.H. Lee and J. Park, "Automatic Color Palette Extraction for Paintings Using Color Grouping and Clustering," Journal of KIISE : Computer Systems and Theory, Vol. 35, No. 7.8, pp. 340-353.2008.
  12. J. Park, D. Kang and K. Yoon, "An Artistic Texture Transfer Method considering Colors Patterns," Journal of KIISE : Computing Practices and Letters, Vol. 20, No. 4, pp. 224-228, 2014.
  13. B.J. Meier, A.M. Spalter and D.B. Karelitz, "Interactive color palette tools", IEEE Computer Graphics and Applications, Vol. 24, No. 3, pp. 64-72, 2004.
  14. Huiwen Chang, Ohad Fried, Yiming Liu, Stephen DiVerdi, and Adam Finkelstein, "Palette-based photo recoloring," ACM Transaction on Graphics, Vol.34, No.4, Article No. 139, July .2015.
  15. E. Reinhard, M. Adhikhmin, B. Gooch and P. Shirley, "Color transfer between images," IEEE Computer Graphics and Applications, Vol. 21, No. 5, pp. 34-41, July-Aug. 2001. https://doi.org/10.1109/38.946629
  16. T. Lee, D. Kang, K. Cho, S. Park and K. Yoon, "Developing application depend on emotion extraction from paintings,", Journal of DCS, Vol.8, No.6, pp.1033-1040, October, 2017.

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