Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-5/W12, 7-12, 2011
http://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XXXVIII-5-W12/7/2011/
doi:10.5194/isprsarchives-XXXVIII-5-W12-7-2011
© Author(s) 2011. This work is distributed
under the Creative Commons Attribution 3.0 License.
 
03 Sep 2012
PRIMITIVE-BASED BUILDING RECONSTRUCTION BY INTEGRATION OF LIDAR DATA AND OPTICAL IMAGERY
W. Zhang1, P. Grussenmeyer2, G. Yan1, and M. Mohamed2 1State Key Laboratory of Remote Sensing Science, School of Geography, Beijing Normal University, 100875 Beijing, China
2The Images Sciences, Computer Sciences and Remote Sensing Laboratory, INSA Strasbourg, France
Keywords: Building Reconstruction, LiDAR, Optical Imagery, Primitive-based, Bundle Adjustment Abstract. Airborne LiDAR data and optical imagery are two datasets used for 3D building reconstruction. In this paper, the complementarities of these two datasets are utilized to perform a primitive-based 3D building reconstruction. The proposed method comprises following steps: (1) recognize primitives from LiDAR point cloud and roughly measure primitives' parameters as initial values, and (2) select primitives' features on the imagery, and (3) optimize primitives' parameters by the constraints of LiDAR point cloud and imagery, and (4) represent 3D building model by these optimized primitives. Compared with other modelbased or CSG-based methods, the proposed method is simpler. It only uses the most straightforward features, i.e. planes of LiDAR point cloud and points of optical imagery. The experimental result shows this primitive-based method can accurately reconstruct 3D building model. And it can tightly integrate LiDAR point cloud and optical imagery, that is to say, all primitives’ parameters are optimized with all constraints in one step.
Conference paper (PDF, 840 KB)


Citation: Zhang, W., Grussenmeyer, P., Yan, G., and Mohamed, M.: PRIMITIVE-BASED BUILDING RECONSTRUCTION BY INTEGRATION OF LIDAR DATA AND OPTICAL IMAGERY, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XXXVIII-5/W12, 7-12, doi:10.5194/isprsarchives-XXXVIII-5-W12-7-2011, 2011.

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