Robust diameter-based thickness estimation of 3D objects

Abstract

International audienceWe propose a robust thickness estimation approach for 3D objects based on the Shape Diameter Function (SDF). Our method first applies a modified strategy to estimate the local diameter with increased accuracy. We then compute a scale-dependent robust thickness estimate from a point cloud, constructed using this local diameter estimation and a variant of a robust distance function. The robustness of our method is benchmarked against several operations such as remeshing, geometric noise and artifacts common in triangle soups. The experimental results show a more stable local thickness estimation than the original SDF, and consistent segmentation results on defect-laden inputs

From 3D models to 3D prints: an overview of the processing pipeline

“…thin walls or other tiny features). In a slightly more general setting, [RNDA13] describes an approach to estimate the thickness of triangulated models.…”

Applicability of watermarking for intellectual property rights protection in a 3D printing scenario

“…A recent work introduced the concept of landmarks [3] as secret points of the 3D shape located on a sphere centered at the CoG. In the embedding stage, the neighborhood around the landmarks is imperceptibly modified.…”

“…Recently, a pose-invariant feature for 3D watermarking systems has been proposed based on thickness estimation [3]. The local surface property is associated to each mesh vertex and its application to 3D watermarking schemes presents promising results against some distortions as pose, noise addition, simplification or remeshing.…”

“…Blind techniques require features to be preserved, for example prongs [5], which are based on the assumption that the model is a connected manifold where geodesic distances can be computed between each vertex of the model, the center of gravity for radial watermarking using constrained watermarking [9,22], or secret landmarks [3]. All these features could potentially be stored as side information, however this could decrease the security of the approach.…”

Improving FEM crash simulation accuracy through local thickness estimation based on CAD data

“…One broadly accepted definition of the local thickness of a three dimensional object with respect to any given point p on the object's surface is based on its Medial Axis Transform (MAT) [9]. Since each such point p has a unique corresponding point m on the medial axis, local thickness at p can be defined as the radius of the sphere centered at m and tangent to p. Since the MAT is a computationally very expensive process Gal et al [6] propose the Local Diameter Shape Function for any point p on the surface of the object, which is based on tracing a large number of rays in a cone around the direction opposite to the surface's normal at p and finding the distance to the next surface intersection point along each ray.…”