디지털융복합연구 (Journal of Digital Convergence)

  • 제12권12호
  • /
  • Pages.521-528
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  • 2014
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  • 2713-6434(pISSN)
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  • 2713-6442(eISSN)
한국디지털정책학회 (The Society of Digital Policy and Management)
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HTML5에서 직선의 기울기를 이용한 2D to 3D 입체 이미지 변환

2D to 3D Anaglyph Image Conversion using Linear Curve in HTML5

  • 투고 : 2014.10.20
  • 심사 : 2014.12.20
  • 발행 : 2014.12.28
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⟨ 이전 논문 다음 논문 ⟩

초록

본 논문에서는 HTML5에서 직선의 기울기를 이용하여 2D 이미지를 3D 입체 이미지로 변환하는 방법을 제안한다. 3D 이미지 변환을 위한 어떠한 정보도 없이 단 하나의 원본 이미지를 좌안과 우안을 위해 RGB 색상을 필터링한다. 사용자는 깊이 값을 설정하기 위해 미리 만들어 놓은 제어 점을 선택한 후 깊이 값을 설정하는 작업을 수행한다. 이렇게 선택된 값들을 반영하여, 이미지 전체와 부분적인 원근감을 갖도록 사용자가 정의한 직선의 기울기를 이용하여 좌안과 우안을 위한 깊이를 부여한 후 Anaglyph 3D 이미지를 자동으로 생성하게 된다. 이 모든 과정이 HTML5를 사용한 웹 환경에서 구현하였기 때문에, 사용자들은 매우 쉽고 편리하게 자신들이 원하는 3D 이미지를 생성할 수 있게 된다.

In this paper, we propose the method of converting 2D image to 3D image using linear curves in HTML5. We use only one image without any other information about depth map for creating 3D images. So we filter the original image to extract RGB colors for left and right eyes. After selecting the ready-made control point of linear curves to set up depth values, users can set up the depth values and modify them. Based on the depth values that the end users select, we reflect them. Anaglyph 3D is automatically made with the whole and partial depth information. As all of this work has been designed and implemented in Web environment using HTML5, it is very easy and convenient and end users can create any 3D image that they want to make.

키워드

참고문헌

  1. R. Phon, R. Rzesutek, and D. Androutsos, Semi-automatic 2D to 3D image conversion using scale-space Random Walks and a graph cuts based depth prior, 2011 18th IEEE International Conference on Image Processing (ICIP), pp.865-868, 2011
  2. J. Konrad, Meng Wang and P. Ishwar, Learning-Based, Automatic 2D-to-3D Image and Video Conversion, IEEE Transactions on Image Processing, Vol.22 pp. 3485-3496, 2013 https://doi.org/10.1109/TIP.2013.2270375
  3. J. Caviedes, J. Villegas, Real time 2D to 3D conversion: Technical and visual quality requirements, 2011 IEEE International Conference on Consumer Electronics (ICCE), pp. 897-898, 2011
  4. H. Emrah Tasli, K. Ugur, Interactive 2D 3D image conversion method for mobile devices, 3DTV Conference: The True Vision - Capture, Transmission and Display of 3D Video (3DTV-CON), pp.1-4, 2011
  5. L. Zhang, C. Vazquez, and S. Knorr, 3D-TV Content Creation: Automatic 2D-to-3D Video Conversion, IEEE Transactions on Broadcasting, Vol. 57, pp. 372-383, 2011 https://doi.org/10.1109/TBC.2011.2122930
  6. Ianir Ideses, Leonid P. Yaroslavsky, and Barak Fishbain, Real-time 2D to 3D video conversion, Journal of Real-Time Image Proc Springer, Vol. 2, pp.3-9, 2007 https://doi.org/10.1007/s11554-007-0038-9
  7. J. Ko, M .Kim, and C. Kim, 2D-To-3D Stereoscopic Conversion: Depth-Map Estimation in a 2D Single-View Image, Proc. of SPIE Vol. 6696, pp.66962A-1-9, 2007
  8. C.C. Cheng, C. T. Li, and L. G. Chen, A Novel 2D-to-3D Conversion System Using Edge Information, IEEE Transactions on Consumer Electronics, Vol. 56, No. 3, pp. 1739-1745, 2010 https://doi.org/10.1109/TCE.2010.5606320
  9. Ge Guo, Nan Zhang, Longshe Huo, and Wen Gao, 2D to 3D conversion based on edge defocus and segmentation, IEEE International Conference on Acoustics, Speech & Signal Processing, pp.2181-2184, 2008
  10. Yu-Lin Chang, Chih-Ying Fang, Li-Fu Ding, Shao-Yi Chen, and Liang-Gee Chen, Depth Map Generation for 2D-to-3D Conversion by Short-Term Motion Assisted Color Segmentation, IEEE International Conference on Multimedia & Expo, pp.1958-1961, 2007
  11. A. Capra, S. Curti, and M. La Cascia, 3D stereoscopic image pairs by depth-map generation, IEEE 3D Data Processing, Visualization and Transmission(3DPVT), pp. 124-131, 2004
  12. http://en.wikipedia.org/wiki/2D_to_3D_conversion
  13. http://en.wikipedia.org/wiki/Anaglyph_3D
  14. http://dxinteractive.com/#!/3d-photos