石器データベースと RGB-D

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.

No abstract

Point-cloud-based technique plays a very significant role in 3D model restoration. In the archaeological application of stone tools, the scale drawing, which is hand-drawn from measured stone tools, is traditionally used. In the scale drawing creation, a base drawing which consists outline and ridge lines is initially drawn from geometric features of shape. After that other lines are extracted from knowledge of making stone tools and are added to the base drawing. It requires special knowledge to extract feature lines from stone tools so that scale drawing is time-consuming. Therefore, if the base drawing is automatically extracted, the working hours are reduced. To overcome this issue, this paper proposes a feature line extraction method using the Mahalanobis distance metric. First, the points on outline are extracted from a point cloud. Then, the surface variation is calculated with a various number of neighbors and thus the potential feature points are detected by the analysis of its surface variation. After that, the potential feature points are thinned towards the highest variation points by using Laplacian smoothing. Then, the thinned feature points are shrunk to the potential feature points. Finally, a feature line is extracted by connecting the nearest thinned feature points locating in the Mahalanobis distance field. To verify our method, the extracted feature lines are compared to the ground truth of base drawing drawn by archaeological illustrators. Our method is applied to stone tools, and we confirm the effectiveness of our method.

Researchers assume that the bodies of several Tara statues may have been molded from the same template. Therefore, researchers are eager to study the shape similarities between the Tara statues. Motivated by the archaeologist's requirements, this study presents an efficient approach to evaluate shape similarities between point clouds of two different Tara statues right-arm models. The evaluation approach consists of two main stages. The first is the reconstruction of individual body parts without decoration using a B-spline surface approximation technique. In previous reconstruction process, the surrounding surface selection parameter was manually specified. If the manually applied parameter is inadequate, it reduces the accuracy of the surface approximation and hole-filling, resulting in reduced accuracy of the evaluation result. Therefore, in this study, the surrounding surface selection parameter is automatically determined based on the Golden-section-search algorithm. The second stage evaluates the shape similarities between two different point clouds. The evaluation method considers a simple point-to-surface distance metric method with overlapping-surface detection and when compared with generic point-to-point distance metric method, the evaluation results proved that the proposed methodology was reliable and effective for this application. The approximation accuracy affects the evaluation result when the reconstruction method fills the gap by adding new points through the approximated surface. Therefore, in this study, the shape similarities were investigated between the two arm models with holes, immediately after separating the decoration parts.

No abstract

In 3D CAD systems, it is not always possible to convert trimmed surfaces to the intended shapes upon data exchange between different CAD systems because the definition of trimmed surfaces is not unified among the CAD systems. If a shape can not import to a CAD system, the shape should be modified to suit to the system. But many problems to improve the shape arise. To solve the problems, it is effective to generate a new surface

Developable surfaces are important for representing and understanding geometric features of 3D models. Some methods are required that surface pattern of a relic should be easily observed in archaeology area. This paper introduces a system to visualize the development of relic's surface pattern based on points, which does not require reconstruction of a mesh model and relies only on the information of points to develop the relic's surface. After a point cloud of a relic is segmented to separate sections, points of each section are projected to a developable surface, then the points of relic's surface are unfolded into an image plane. In our method, the number of segmentations can be controlled by an archaeologist in an interactive interface. The more segmentations a point cloud is divided into, the higher precision the image plane is shown in adjacent area. To observe the surface pattern easily, a developed plane can be interactively rotated on the prime meridian, which is extracted from a relic's surface. This approach can help archaeologists move a specific area of interest to the center of the relics.