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Orthogonal Cross Cylinder Using Segmentation Based Environment Modeling

  • Seung Taek Ryoo
  • Kyung Hyun Yoon
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2330)

Abstract

Orthogonal Cross Cylinder (OCC) mapping and segmentation based modeling methods have been implemented for constructing the image-based navigation system in this paper. The OCC mapping method eliminates the singularity effect caused in the environment maps and shows an almost even amount of area for the environment occupied by a single texel. A full-view image from a fixed point-of-view can be obtained with OCC mapping although it becomes difficult to express another image when the point-of-view has been changed. The OCC map is segmented according to the objects that form the environment and the depth value is set by the characteristics of the classified objects for the segmentation-based modeling. This method can easily be implemented on an environment map and makes the environment modeling easier through extracting the depth value by the image segmentation.

Keywords

Image Segmentation Solid Angle Environment Modeling Depth Image Base Modeling Method 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Bregler, C., Cohen, M. F., Debevec, P., McMillan L., Sillion, F. X., Szeliski, R.: Image-based Modeling, Rendering, and Lighting. Siggraph 2000 Course 35, (2000)Google Scholar
  2. 2.
    Blinn J., Newell M.: Texture and reflection in computer generated images. Communications of the ACM, (1976) 19:456–547CrossRefGoogle Scholar
  3. 3.
    Blythe, D., Grantham, B., McReynolds, T., Nelson, S. R.: Advanced Graphics Programming Techniques Using OpenGL. Siggraph’ 99 Course 29, (1999)Google Scholar
  4. 4.
    Greene, N.: Environment Mapping and Other Applications of World Projections. Computer Graphics and Applications, (1986) 6(11):21–29CrossRefGoogle Scholar
  5. 5.
    McMillan, L., Bishop, G.: Plenoptic modeling: An image-based rendering system. Siggraph’ 95, (1995) 39–46Google Scholar
  6. 6.
    Heidrich, W., Seidel, H.-P.: View independent Environment Maps. Eurographics/ACM Siggraph Workshop on Graphics Hardware’ 98, (1998) 39–46Google Scholar
  7. 7.
    Imielinska, C., Laino-Pepper, L.: Technical Challenges of 3D Visualization of Large Color Data Sets. The Second Visible Human Project Conference Proceedings, (1998)Google Scholar
  8. 8.
    Mortensen, E. N., Reese, L. J., Barrett, W. A.: Intelligent Selection Tools. IEEE Conference on Computer Vision and Pattern Recognition’ 00, (2000) 776–777Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Seung Taek Ryoo
    • 1
  • Kyung Hyun Yoon
    • 1
  1. 1.Department of Image Engineering Graduate School of Advanced Imaging Science, Multimedia and FilmChungAng UniversitySeoulKorea

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