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모바일 카메라를 이용한 경량 3D 모델링

Light 3D Modeling with mobile equipment

  • 주승환 (한국기술교육대학교 컴퓨터공학부) ;
  • 서희석 (한국기술교육대학교 컴퓨터공학부) ;
  • 한성휴 (한국기술교육대학교 문리HRD학부)
  • 투고 : 2016.10.08
  • 심사 : 2016.11.22
  • 발행 : 2016.12.30

초록

Recently, 3D related technology has become a hot topic for IT. 3D technologies such as 3DTV, Kinect and 3D printers are becoming more and more popular. According to the flow of the times, the goal of this study is that the general public is exposed to 3D technology easily. we have developed a web-based application program that enables 3D modeling of facial front and side photographs using a mobile phone. In order to realize 3D modeling, two photographs (front and side) are photographed with a mobile camera, and ASM (Active Shape Model) and skin binarization technique are used to extract facial height such as nose from facial and side photographs. Three-dimensional coordinates are generated using the face extracted from the front photograph and the face height obtained from the side photograph. Using the 3-D coordinates generated for the standard face model modeled with the standard face as a control point, the face becomes the face of the subject when the RBF (Radial Basis Function) interpolation method is used. Also, in order to cover the face with the modified face model, the control point found in the front photograph is mapped to the texture map coordinate to generate the texture image. Finally, the deformed face model is covered with a texture image, and the 3D modeled image is displayed to the user.

키워드

참고문헌

  1. Su, T. Lv, Z., Gao, S., Li, X. and Lv, H., "3d seabed: 3d modeling and visualization platform for the seabed," In Multimedia and Expo Workshops (ICMEW) 2014 IEEE International Conference on IEEE, 2014, pp. 1-6.
  2. Compton, Brett G., and Jennifer A. Lewis., "3D-printing of lightweight cellular composites," Advanced Materials Vol. 26, No. 34, 2014, pp. 5930-5935. https://doi.org/10.1002/adma.201401804
  3. Van Ginneken, B., Frangi, A. F., Staal, J. J., ter Haar Romeny, B. M. and Viergever, M. A., "Active shape model segmentation with optimal features," IEEE transactions on medical imaging, Vol. 21, No.8, 2002, pp. 924-933. https://doi.org/10.1109/TMI.2002.803121
  4. Phung S. L., Bouzerdoum A., and Chai D., "A novel skin color model in YCbCr color space and its application to human face detection," Image Processing, Proceedings International Conference on IEEE, Vol. 1, 2002, pp. I-289-I-292.
  5. Mostafa, L. and Abdelazeem, S., "Face detection based on skin color using neural networks," GVIP 05 Conference, 2005, pp. 19-21.
  6. Park, I. K., Zhang, H., Vezhnevets, V. and Choh, H. K., "Image-based photorealistic 3-D face modeling," Automatic Face and Gesture Recognition, Proceedings Sixth IEEE International Conference on IEEE, 2004. pp. 49-54.
  7. Zhang, M., Ma, L., Zeng, X. and Wang, Y., "Imaged-based 3D face modeling," Computer Graphics, Imaging and Visualization, Proceedings International Conference on IEEE, 2004, pp. 165-168.
  8. Bjarne Stroustrup, "The C++ Programming Language SE," Addison-Wesley, 2000.
  9. Wright, G. B., "Radial Basis Function Interpolation: Numerical and Analytic Developments," Ph. D. Thesis, 2003.