Abstract

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.

Highlights

  • The recent development of 3D scanning, that is, photogrammetry and laser scanning, has enabled us to quickly and accurately record complex 3D objects in the real world

  • To observe the whole 3D structure of such complex point-based objects, the point-based transparent visualization, which we recently proposed and named “stochastic point-based rendering (SPBR)” (Tanaka et al, 2016), is useful

  • In this paper, we propose combining edge highlighting with transparent visualization based on SPBR

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Summary

INTRODUCTION

The recent development of 3D scanning, that is, photogrammetry and laser scanning, has enabled us to quickly and accurately record complex 3D objects in the real world. The complexity becomes significant in cases in which the scanned objects have internal 3D structures and the acquired point clouds describe 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 and named “stochastic point-based rendering (SPBR)” (Tanaka et al, 2016), is useful. Transparent visualization sometimes shows us too much information so that the generated images become confusing To address this problem, in this paper, we propose combining edge highlighting with transparent visualization based on SPBR. We propose a new edge highlighting method applicable to 3D scanned point clouds.

RELATED WORK
BRIEF REVIEW OF SPBR
OPACITY-BASED EDGE HIGHLIGHTING
Eigenvalue-based 3D Feature Values
Method of Opacity-based Edge Highlighting
CASE STUDIES
Comparative visualizations of 3D feature values
CONCLUSIONS

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