ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume V-2-2020
03 Aug 2020
 | 03 Aug 2020


K. Kawakami, K. Hasegawa, L. Li, H. Nagata, M. Adachi, H. Yamaguchi, F. I. Thufail, S. Riyanto, Brahmantara, and S. Tanaka

Keywords: 3D Scanned Point Clouds, Transparent Visualization, 3D Edges, Opacity-based Edge Highlighting

Abstract. The recent development of 3D scanning technologies has made it possible to quickly and accurately record various 3D objects in the real world. The 3D scanned data take the form of large-scale point clouds, which describe complex 3D structures of the target objects and the surrounding scenes. The complexity becomes significant in cases that a scanned object has internal 3D structures, and the acquired point cloud is created by merging the scanning results of both the interior and surface shapes. To observe the whole 3D structure of such complex point-based objects, the point-based transparent visualization, which we recently proposed, is useful because we can observe the internal 3D structures as well as the surface shapes based on high-quality see-through 3D images. However, transparent visualization sometimes shows us too much information so that the generated images become confusing. To address this problem, in this paper, we propose to combine “edge highlighting” with transparent visualization. This combination makes the created see-through images quite understandable because we can highlight the 3D edges of visualized shapes as high-curvature areas. In addition, to make the combination more effective, we propose a new edge highlighting method applicable to 3D scanned point clouds. We call the method “opacity-based edge highlighting,” which appropriately utilizes the effect of transparency to make the 3D edge regions look clearer. The proposed method works well for both sharp (high-curvature) and soft (low-curvature) 3D edges. We show several experiments that demonstrate our method’s effectiveness by using real 3D scanned point clouds.