Abstract: In this paper, a primitive-based 3D building roof modeling method, by integrating LiDAR data and aerial imagery, is proposed. The novelty of the proposed modeling method is to represent building roofs by geometric primitives and to construct a cost function by using constraints from both LiDAR data and aerial imagery simultaneously, so that the accuracy potential of the different sensors can be tightly integrated for the building model generation by an integrated primitive’s parameter optimization procedure. To verify the proposed modeling method, both simulated data and real data with simple buildings provided by ISPRS (International Society for Photogrammetry and Remote Sensing), were used in this study. The experimental results were evaluated by the ISPRS, which demonstrate the proposed modeling method can integrate LiDAR data and aerial imagery to generate 3D building models with high accuracy in both the horizontal and vertical directions. The experimental results also show that by adding a component, such as a dormer, to the primitive, a variant of the simple primitive is constructed, and the proposed method can generate a building model with some details.
Keywords: building modeling; LiDAR; point cloud; aerial imagery; data fusion; optimization; primitive; model-based
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Zhang, W.; Wang, H.; Chen, Y.; Yan, K.; Chen, M. 3D Building Roof Modeling by Optimizing Primitive’s Parameters Using Constraints from LiDAR Data and Aerial Imagery. Remote Sens. 2014, 6, 8107-8133.
Zhang W, Wang H, Chen Y, Yan K, Chen M. 3D Building Roof Modeling by Optimizing Primitive’s Parameters Using Constraints from LiDAR Data and Aerial Imagery. Remote Sensing. 2014; 6(9):8107-8133.
Zhang, Wuming; Wang, Hongtao; Chen, Yiming; Yan, Kai; Chen, Mei. 2014. "3D Building Roof Modeling by Optimizing Primitive’s Parameters Using Constraints from LiDAR Data and Aerial Imagery." Remote Sens. 6, no. 9: 8107-8133.