The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLIII-B1-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 375–382, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-375-2022
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLIII-B1-2022, 375–382, 2022
https://doi.org/10.5194/isprs-archives-XLIII-B1-2022-375-2022
 
30 May 2022
30 May 2022

AUTOMATIC METHOD FOR GENERATING 3D BUILDING MODELS WITH TEXTURE FROM UAV IMAGES

H. G. Kim1, W. Yoon1, S. Rhee1, and T. Kim2 H. G. Kim et al.
  • 13DLabs Co. Ltd., 1609-ho, 56 Songdogwahak-ro, Yeonsu-gu, Incheon, South Korea
  • 2Dept. of Geoinformatic Engineering, Inha University, 100 Inharo, Namgu, Incheon, South Korea

Keywords: 3D Building Model, UAV Images, Point Cloud, Statistical Technique

Abstract. In this paper, we propose a method for automatically generating 3D building models from UAV image based point cloud data and for mapping building texture from UAV images. The proposed method generates dense point clouds from UAV images and isolates points from building areas through a statistical analysis. It then generates solid models as 3D building models by point cloud analysis per building area. Texture for 3D building solid models are created by mapping model face to UAV images. In order to verify the proposed method, various UAV image sets and point clouds were tested. As results, the possibility of generating cluster-type solid building models based on UAV images was confirmed. It is expected that this method can contribute to the active usage of UAV images in 3D spatial information generation. In the future, we plan to conduct research on improving the accuracy of curved building shapes and texturing accuracy.