Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 379-382, 2016
https://doi.org/10.5194/isprs-archives-XLI-B2-379-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
08 Jun 2016
INTEGRATION OF IMAGES AND LIDAR POINT CLOUDS FOR BUILDING FAÇADE TEXTURING
L. C. Chen1, L. L. Chan2, and W. C. Chang2 1Center for Space and Remote Sensing Research, National Central University, Taiwan
2Dept. of Civil Engineering, National Central University, Taiwan
Keywords: Façade Texture, GLCM, Image, Lidar, Occlusion, Photorealistic Building Model Abstract. This paper proposes a model-based method for texture mapping using close-range images and Lidar point clouds. Lidar point clouds are used to aid occlusion detection. For occluded areas, we compensate the occlusion by different view-angle images. Considering the authenticity of façade with repeated patterns under different illumination conditions, a selection of optimum pattern is suggested. In the selection, both geometric shape and texture are analyzed. The grey level co-occurrence matrix analysis is applied for the selection of the optimal façades texture to generate of photorealistic building models. Experimental results show that the proposed method provides high fidelity textures in the generation of photorealistic building models. It is demonstrated that the proposed method is also practical in the selection of the optimal texture.
Conference paper (PDF, 1030 KB)


Citation: Chen, L. C., Chan, L. L., and Chang, W. C.: INTEGRATION OF IMAGES AND LIDAR POINT CLOUDS FOR BUILDING FAÇADE TEXTURING, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B2, 379-382, https://doi.org/10.5194/isprs-archives-XLI-B2-379-2016, 2016.

BibTeX EndNote Reference Manager XML