DOI QR코드

DOI QR Code

A Study on the Photo-realistic 3D City Modeling Using the Omnidirectional Image and Digital Maps

전 방향 이미지와 디지털 맵을 활용한 3차원 실사 도시모델 생성 기법 연구

  • Kim, Hyungki (Department of Mechanical Engineering, KAIST) ;
  • Kang, Yuna (1st R&D Institute, Agency for Defense Development) ;
  • Han, Soonhung (Department of Ocean System Engineering, KAIST)
  • 김형기 (카이스트 기계공학과) ;
  • 강윤아 (국방과학연구소 제 1기술연구본부 3부) ;
  • 한순흥 (카이스트 해양시스템공학과)
  • Received : 2014.03.04
  • Accepted : 2014.05.09
  • Published : 2014.09.01

Abstract

3D city model, which consisted of the 3D building models and their geospatial position and orientation, is becoming a valuable resource in virtual reality, navigation systems, civil engineering, etc. The purpose of this research is to propose the new framework to generate the 3D city model that satisfies visual and physical requirements in ground oriented simulation system. At the same time, the framework should meet the demand of the automatic creation and cost-effectiveness, which facilitates the usability of the proposed approach. To do that, I suggest the framework that leverages the mobile mapping system which automatically gathers high resolution images and supplement sensor information like position and direction of the image. And to resolve the problem from the sensor noise and a large number of the occlusions, the fusion of digital map data will be used. This paper describes the overall framework with major process and the recommended or demanded techniques for each processing step.

Keywords

References

  1. Google Earth, http://www.google.com/earth/.
  2. Terra Vista, http://www.presagis.com/products_services/products/modeling-simulation/content_creation/terra_vista/.
  3. Yao, J. et al., 2006, A GIS Based Virtual Urban Simulation Environment, Proceedings of the 6th International Conference on Computational Science - Volume Part III, pp.60-68.
  4. Hagedom, B. and Dollner, J., 2007, High-level Web Service for 3D Building Information Visualization and Analysis, Proceedings of the 15th Annual ACM International Symposium on Advances in Geographic Information Systems, pp.1-8.
  5. Shih, N.J. et al., 2011, 3D Scans of As-built Street Scenes for Virtual Environments, Proceedings of the 2011 Symposium on Simulation for Architecture and Urban Design, pp.46-51.
  6. Visintini, D. et al., 2007, The VRML Model of Victoria Square in Gorizia (Italy) from Laser Scanning and Photogrammetric 3D Surveys, Proceedings of the Twelfth International Conference on 3D Web Technology, pp.165-168.
  7. Xiao, J. et al., 2009, Image-based Street-side City Modeling, Trans. Graph., 28, pp.1-12.
  8. Li, X. et al., 2008, Modeling and Recognition of Landmark Image Collections Using Iconic Scene Graphs, Proceedings of the 10th European Conference on Computer Vision, pp.427-440.
  9. Debevec, P.E. et al., 1996, Modeling and Rendering Architecture from Photographs: A Hybrid Geometry- and Image-based Approach, Proceedings of the 23rd Annual Conference on Computer Graphics and Interactive Techniques, pp.11-20.
  10. Zheng, X. et al., Building Modeling from a Single Image Applied in Urban Reconstruction, Proceedings of the 10th International Conference on Virtual Reality Continuum and Its Applications in Industry, pp.225-234.
  11. Barinova, O. et al., 2008, Fast Automatic Single- View 3-d Reconstruction of Urban Scenes, Proceedings of the 10th European Conference on Computer Vision: Part II, pp.100-113.
  12. Naver Street View, map.naver.com
  13. Google Street View, https://www.google.com/maps
  14. Taneja, A. et al., 2012, Registration of Spherical Panoramic Images with Cadastral 3D Models, 3D Imaging, Modeling, Processing, Visualization and Transmission (3DIMPVT), 2012 Second International Conference on, pp.479-486.
  15. Taneja, A. et al., 2012, Registration of Spherical Panoramic Images with Cadastral 3D Models, 2012 Second International Conference on 3DIMPVT, pp.479-486.
  16. Cipolla, R., Robertson, D. and Tordoff, B., 2004, Image-based Localization, Proc. Int. Conf. on Virtual Systems and Multimedia (VSMM 2004), pp.22-29.
  17. David, P., 2011, Orientation Descriptors for Localization in Urban Environments, International Conference on IROS, pp.494-501.
  18. Cham, T.J. et al., 2010, Estimating Camera Pose from a Single Urban Ground-View Omnidirectional Image and a 2D Building Outline Map, 2010 IEEE Conference on CVPR, pp.366-373.
  19. Wan, G. and Li, S., 2011, Automatic Facades Segmentation using Detected Lines and Vanishing Points, International Congress on Image and Signal Processing (CISP), 3, pp.1214-1217.
  20. Haala, N. and Brenner, C., 1999, Extraction of Buildings and Trees in Urban Environments, ISPRS Journal of Photogrammetry and Remote Sensing, 54, pp.130-137. https://doi.org/10.1016/S0924-2716(99)00010-6
  21. Schindler, K. and Bauer, J., 2003, A Modelbased Method for Building Reconstruction, In Proc. of the International Conference on Computer Vision Workshop on Higher-Level Knowledge in 3D Modeling and Motion (HLK'03), pp.74-82.
  22. Vworld, http://map.vworld.kr