|
Published Articles >> Table of Contents >> Abstract
November/December 2003 (Vol. 23, No. 6)
pp. 52-61
Constructing 3D City Models by Merging Aerial and Ground Views
Christian Fruh, University of California, Berkeley
Avideh Zakhor, University of California, Berkeley
Full Article Text:
   
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/MCG.2003.1242382
Send link to a friend
| Abstract |
|
This article presents a fast approach to automated generation of textured 3D city models with both high details at ground level, and complete coverage for bird's-eye view. A close-range facade model is acquired at the ground level by driving a vehicle equipped with laser scanners and a digital camera under normal traffic conditions on public roads; a far-range digital surface model (DSM), containing complementary roof and terrain shape, is created from airborne laser scans, then triangulated, and finally texture-mapped with aerial imagery. The facade models are first registered with respect to the DSM using Monte Carlo localization, and then merged with the DSM by removing redundant parts and filling gaps.
|
 References
|
[1] Z. Kim, A. Huertas, and R. Nevatia, "Automatic Description of Buildings with Complex Rooftops from Multiple Images," Proc. Computer Vision and Pattern Recognition, IEEE CS Press, vol. 2, 2001, pp. II-272-279.
[2] C. Brenner, N. Haala, and D. Fritsch:, "Towards Fully Automated 3D City Model Generation," Proc. Workshop Automatic Extraction of Man-Made Objects from Aerial and Space Images III, Int'l Soc. Photogrammetry and Remote Sensing, 2001.
[3] A. Dick et al., "Combining Single View Recognition and Multiple View Stereo for Architectural Scenes," Proc. IEEE Int'l Conf. Computer Vision, IEEE CS Press, vol. 1, 2001, pp. 268-274.
[4] V. Sequeira and J.G.M. Goncalves, "3D Reality Modeling: Photo-Realistic 3D Models of Real World Scenes," Proc. 1st Int'l Symp. 3D Data Processing Visualization and Transmission, IEEE CS Press, 2002, pp. 776-783.
[5] I. Stamos and P.K. Allen, "Geometry and Texture Recovery of Scenes of Large Scale," Computer Vision and Image Understanding (CVIU), vol. 88, no. 2, Nov. 2002, pp. 94-118.
[6] C. Früh and A. Zakhor, "Fast 3D Model Generation in Urban Environments," Proc. IEEE Conf. Multisensor Fusion and Integration for Intelligent Systems, IEEE CS Press, 2001, pp. 165-170.
[7] C. Früh and A. Zakhor, "3D Model Generation of Cities Using Aerial Photographs and Ground Level Laser Scans," Proc. Computer Vision and Pattern Recognition, IEEE CS Press, vol. 2.2, 2001, p. II-31-8.
[8] H. Zhao and R. Shibasaki, "Reconstructing a Textured CAD Model of an Urban Environment Using Vehicle-Borne Laser Range Scanners and Line Cameras," Machine Vision and Applications, vol. 14, no. 1, 2003, pp. 35-41
[9] C. Früh and A. Zakhor, "Data Processing Algorithms for Generating Textured 3D Building Façade Meshes From Laser Scans and Camera Images," Proc. 3D Processing, Visualization and Transmission, IEEE CS Press, 2002, pp. 834-847.
[10] M.A. Fischler and R.C. Bolles, “Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography,” Graphics and Image Processing, vol. 24, no. 6, pp. 381–395, June 1981.
[11] M. Garland and P.S. Heckbert, "Surface Simplification Using Quadric Error Metrics," Proc. Siggraph 97, ACM Press, New York, 1997, pp. 209-216.
[12] S. Thrun et al., "Robust Monte Carlo Localization for Mobile Robots," Artificial Intelligence, vol. 101, 2000, pp. 99-141; .
[13] G. Turk and M. Levoy, “Zippered Polygon Meshes from Range Images,” Proc. SIGGRAPH '94, pp. 311-318, 1994.
|
 Additional Information
|
Index Terms- localization, scan matching, airborne laser scans, 3D city model, urban simulation
Citation:
Christian Fruh, Avideh Zakhor,
"Constructing 3D City Models by Merging Aerial and Ground Views,"
IEEE Computer Graphics and Applications,
vol. 23,
no. 6,
pp. 52-61,
Nov/Dec,
2003
|
|
RSS Feed