3D Surface Reconstruction of Stone Tools by Using Four-Directional Measurement Machine

Konno

et al. 2015

Self Cite

For point cloud data obtained from 3D scanning devices, excessively large storage and long postprocessing time are required. Due to this, it is very important to simplify the point cloud to reduce calculation cost. In this paper, we propose a new point cloud simplification method that can maintain the characteristics of surface shape for unstructured point clouds. In our method, a segmentation range based on mean curvature of point cloud can be controlled. The simplification process is completed by maintaining the position of the representative point and removing the represented points using the range. Our method can simplify results with highly simplified rate with preserving the form feature. Applying the proposed method to 3D stone tool models, the method is evaluated precisely and effectively.

Section: Experimental Results and Limitationmentioning

confidence: 99%

Section: Search Of Joining Materialsmentioning

confidence: 99%

Feature-Preserving Simplification of Point Cloud by Using Clustering Approach Based on Mean Curvature

Yang

Konno

et al. 2015

Self Cite

“…This section presents the experimental results. We applied our algorithm to point data of stone tools obtained by the four-directional 3D laser scanners, whose scanning precision is 0.2 mm [8]. The experiment was performed in an Intel Core i5-650 3.2 GHz machine, with 3 GB of RAM and an NVIDIA GeForce GTX 570 graphics card.…”

Section: Experimental Results and Applicationmentioning

confidence: 99%

Feature Extraction and Modification for Illustrating 3D Stone Tools from Unorganized Point Clouds

Altantsetseg

Muraki

et al. 2013

Self Cite

This paper presents a method for extracting and modifying features for illustrating stone tools. Features are detected from unorganized point clouds obtained by a 3D laser scanner. The curvature of each point in the point clouds is estimated by local surface fitting algorithm and used for detecting potential feature points. Feature lines are extracted by directionally growing algorithm. Our directionally feature line growing method is simple to detect feature lines from unorganized point data. The main idea of our method is to extract feature lines using principal curvatures and principal directions of the potential feature points along the axis directions and to merge all extracted lines. In the illustration of stone tools, to maintain form and manufacturing information, it requires to modify the detected features by specific knowledge on illustrating stone tools. Using the power of data parallel computation on the GPU, our method can be accelerated multiple times. Finally, our experimental results are compared to the actual illustrations drawn by archaeological illustrators.

“…Our main contributions are: (1) We propose a simple algorithm to fill complex holes with islands, (2) Our proposed method is robust for filling holes by minimizing filling areas and (3) the method can generate a continuous surface by minimizing filling area.…”

Section: Introductionmentioning

confidence: 99%

Minimum Surface Area Based Complex Hole Filling Algorithm of 3D Mesh

Altantsetseg

Konno

2015

Self Cite

Filling holes of 3D models is an important and complicated process. In this paper, we introduce a new and robust method for filling complex holes in triangular mesh models. In order to fill separate holes, the boundary edges of a hole are smoothly arranged and then locally uniform new points are added to the hole. The new points are selected by minimizing a hole filling area. The Delaunay triangulation method in a local area is applied for creating new meshes. By considering vertices of islands in a hole, new points can be added to the hole, which allows filling of a complex hole with islands.