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Plumber is a specialized shape classification method for detecting tubular features of 3D objects represented by a triangle mesh. The Plumber algorithm segments a surface into connected components that are either body parts or elongated features, that is, handle-like and protrusion-like features, together with their concave counterparts, i.e. narro...
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Context 1
... 1 boundary: the surface around p is considered topologically equivalent to a disc (see Figure 3(a)). ...
Context 2
... 2 boundary components: the surface around p is tubular-shaped (see Figure 3(b)). Their lengths are used to distinguish between conic and cylindrical shapes, and p is classified as a limb-vertex. ...
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Plumber is a specialized shape classification method for detecting tubular features of 3D objects represented by a triangle mesh. The Plumber algorithm segments a surface into connected components that are either body parts or elongated features, that is, handle-like and protrusion-like features, together with their concave counterparts, i.e. narro...
Citations
... Traditional region-based methods are roughly divided into clustering [19−21] and region growing [22,23] . Clustering allots elements into pre-determined classes of representative points according to specific distances. ...
... Region growing starts growing regions with pre-defined seeds, until certain terminating conditions are met. Ref. [22] deduces the connectivity between the protrusion and the body based on the intersection of a small spherical surface and model surface, and uses region growing to separate the handle-like or protruding parts. Ref. [23] obtains the foreground region and background region by improved isophotic region growing, with user-defined foreground and background seeds. ...
In this paper, we propose a fully automatic mesh segmentation method, which divides meshes into sub‐meshes recursively through spectral analysis. A common problem in the spectral analysis of geometric processing is how to choose the specific eigenvectors and the number of these vectors for analysis and processing. This method tackles this problem with only one eigenvector, i.e. Fiedler vector. In addition, using only one eigenvector drastically reduces the cost of computing. Different from the Fiedler vector commonly used in the bipartition of graphs and meshes, this method finds multiple parts in only one iteration, vastly reducing the number of iterations and thus the time of operation, because each iteration produces as many correct boundaries as possible, instead of only one. We have tested this method on many 3D models, the results of which suggest the proposed method performs better than many advanced methods of recent years.
... All of the above-mentioned methods analyze the point cloud at only one single scale. To our knowledge, only the Plumber method [Mortara 2004] uses different radii of analysis. However, the scale is used to intersect the mesh with a sphere in order to determine the local topology of the surface, which cannot be easily extended to unstructured data. ...
3D acquisition techniques like photogrammetry and laser scanning are commonly used in numerous fields such as reverse engineering, archeology, robotics and urban planning. The main objective is to get virtual versions of real objects in order to visualize, analyze and process them easily. Acquisition techniques become more and more powerful and affordable which creates important needs to process efficiently the resulting various and massive 3D data. Data are usually obtained in the form of unstructured 3D point cloud sampling the scanned surface. Traditional signal processing methods cannot be directly applied due to the lack of spatial parametrization. Points are only represented by their 3D coordinates without any particular order. This thesis focuses on the notion of scale of analysis defined by the size of the neighborhood used to locally characterize the point-sampled surface. The analysis at different scales enables to consider various shapes which increases the analysis pertinence and the robustness to acquired data imperfections. We first present some theoretical and practical results on curvature estimation adapted to a multi-scale and multi-resolution representation of point clouds. They are used to develop multi-scale algorithms for the recognition of planar and anisotropic shapes such as cylinders and feature curves. Finally, we propose to compute a global 2D parametrization of the underlying surface directly from the 3D unstructured point cloud.
... Zhou et al. [26] proposed a generalized cylinder decomposition method which allows handling of objects composed of multiple GCs. Mortara et al. in Ref. [59] proposed a method to decompose a mesh into shape features and more specifically in Ref. [60] proposed an algorithm to decompose a mesh into tubular primitives. The special challenge in applying our method to this case, to be solved in future, is how to represent the branch point and how the cross sections come together there. ...
Large-scale deformations of a tubular object, or generalized cylinder, are often defined by a target shape for its center curve, typically using a parametric target curve. This task is non-trivial for free-form deformations or direct manipulation methods because it is hard to manually control the centerline by adjusting control points. Most skeleton-based methods are no better, again due to the small number of manually adjusted control points. In this paper, we propose a method to deform a generalized cylinder based on its skeleton composed of a centerline and orthogonal cross sections. Although we are not the first to use such a skeleton, we propose a novel skeletonization method that tries to minimize the number of intersections between neighboring cross sections by means of a relative curvature condition to detect intersections. The mesh deformation is first defined geometrically by deforming the centerline and mapping the cross sections. Rotation minimizing frames are used during mapping to control twisting. Secondly, given displacements on the cross sections, the deformation is decomposed into finely subdivided regions. We limit distortion at these vertices by minimizing an elastic thin shell bending energy, in linear time. Our method can handle complicated generalized cylinders such as the human colon.
... 2 with the function t measuring tubeness, that is, the likelihood of a given vertex to lie on a tubular feature. The tubeness t is a region-wise measure, computed following the intuition that tubes are identified by shape parts whose intersection with a sphere of proper radius is homeomorphic to a topological disk with holes, rather than a disk [Mortara et al. 2004]. For a given vertex v i , we consider the surface region defined by the points having geodesic distance from v i less than a radius r , and keep track of the topology of the region as r increases. ...
We propose a new method for fabricating digital objects through reusable silicone molds. Molds are generated by casting liquid silicone into custom 3D printed containers called metamolds. Metamolds automatically define the cuts that are needed to extract the cast object from the silicone mold. The shape of metamolds is designed through a novel segmentation technique, which takes into account both geometric and topological constraints involved in the process of mold casting. Our technique is simple, does not require changing the shape or topology of the input objects, and only requires of-the-shelf materials and technologies. We successfully tested our method on a set of challenging examples with complex shapes and rich geometric detail.
... Benchmark with the 3D Normalized Probabilistic Rand Index (3DNPRI) [28]. The obtained results are compared to some methodologies, which are MVBB [29], Plumber [30], Curvature Classification (CC) [9], Topology Driven (TD) [31], Fitting Primitives (FP) [32], Shape Diameter (SD) [33], Heterogeneous Graphs (HG) [14] and Boundary Learning (BL) [34]. Fig. 7 and Table 1 illustrate the comparative results produced by the evaluated algorithms. ...
Decomposing a 3D mesh into significant regions is considered as a fundamental process in computer graphics, since several algorithms use the segmentation results as an initial step, such as skeleton extraction, shape retrieval, shape correspondence, and compression. In this work, we present a new segmentation algorithm using spectral clustering where the affinity matrix is constructed by combining the minimal curvature and dihedral angles to detect both concave and convex properties of each edge. Experimental results show that the proposed method outperforms some of the existing segmentation methods, which highlight the performance of our approach.
... In particular, tubular (or cylindrical) decompositions are widely used for shape approximation and modeling. Methods such as [30,31] aim to recognize the cylindrical components of a shape, though are not applicable to our specific problem since they may leave some portions of the shape with weak cilindricity outside of the decomposition. Similarly, Wu and Lui [32] propose a skeleton-driven tube decomposition, but their method leaves some unassigned voids around the branching nodes of the skeleton. ...
... We motivate the introduction of a novel splitting technique by observing that similar methods for tube decomposition (e.g. [30,31]) may leave portions of the object with weak cilindricity outside of the decomposition and are therefore not suited for our purposes. The decomposition we present guarantees that the union of all tubes coincides with the input shape, thus ensuring that the resulting parameterization is defined within the whole domain. ...
... Unfortunately, the axis computed by some algorithms [31] is entirely contained in the solid, endpoints included. In these cases, we simply elongate each of its extremities by linear extrapolation, locate the intersection with the boundary of T , and create an additional segment for each extremity of T axis . ...
A solid cylindrical parameterization is a volumetric map between a tubular shape and a right cylinder embedded in the polar coordinate reference system. This paper introduces a novel approach to derive smooth (i.e., harmonic) cylindrical parameterizations for solids with arbitrary topology. Differently from previous approaches our mappings are both fully explicit and bi-directional, meaning that the three polar coordinates are encoded for both internal and boundary points, and that for any point within the solid we can efficiently move from the object space to the parameter space and vice-versa. To represent the discrete mapping, we calculate a tetrahedral mesh that conforms with the solid's boundary and accounts for the periodic and singular structure of the parametric domain. To deal with arbitrary topologies, we introduce a novel approach to exhaustively partition the solid into a set of tubular parts based on a curve-skeleton. Such a skeleton can be either computed by an algorithm or provided by the user. Being fully explicit, our mappings can be readily exploited by off-the-shelf algorithms (e.g., for iso-contouring). Furthermore, when the input shape is made of tubular parts, our method produces low-distortion parameterizations whose iso-surfaces fairly follow the geometry in a natural way. We show how to exploit this characteristic to produce high-quality hexahedral and shell meshes.
... New comparable studies on the outcomes of some region type mesh decomposition procedures can be located in [4]. In [50], [51], region type decomposition is generated relied on investigating the junction curves/sweeps of the ball concentrated nearly all vertices. The investigation partitions a shape into related parts that are either body's parts or extended characteristics, like protrusion characteristics. ...
Mesh segmentation plays a major role in modeling, shape compression, simplification, texture mapping, and skeleton extracting. The main goal of the mesh decomposition techniques is to segment the shape into parts in the preprocessing step. Each part acts as a dependent object which can identify the logic characteristics of the shape, in the preprocessing step. The techniques can be based on human perception (meaning components), geometric attributes or mesh components (vertices, edges, faces). This paper presents a comprehensive comparative study of the mesh segmentation techniques in terms of features and limitations. Finally, we figure out the most important challenges and recommendations for the mesh segmentation techniques. Index Terms-Mesh segmentation.
... (Shlafman et al., 2002) take a measure of weighted distance to represent any distance between two surface patches. In order to easily generate segmentation that two mesh models can be compatible, literature (Mortara et al., 2009) proposes a K-means algorithm based on face clustering. As mentioned in Section1., model segmentation efficiency by K-means algorithm heavily depends on randomized initial seed points (i.e., centroid). ...
3D mesh model segmentation is drawing increasing attentions from digital geometry processing field in recent years. The original 3D mesh model need to be divided into separate meaningful parts or surface patches based on certain standards to support reconstruction, compressing, texture mapping, model retrieval and etc. Therefore, segmentation is a key problem for 3D mesh model segmentation. In this paper, we propose a method to segment Collada (a type of mesh model) 3D building models into meaningful parts using cluster analysis. Common clustering methods segment 3D mesh models by K-means, whose performance heavily depends on randomized initial seed points (i.e., centroid) and different randomized centroid can get quite different results. Therefore, we improved the existing method and used K-means++ clustering algorithm to solve this problem. Our experiments show that K-means++ improves both the speed and the accuracy of K-means, and achieve good and meaningful results.
... These methods, directly seek a single segmentation solution without considering or reusing other potential segmentation solutions, usually do not suffice to generate high quality segmentation results for all kinds of models. In contrast, there are other alternative segmentation methods using more complex geometrical information, like shape diameter function [13], tubular analysis [14] and skeleton-based methods [15]. These methods, however, involve complex implementation procedures and expensive computation costs. ...
Tooth segmentation on dental model is an essential step of computer-aided-design systems for orthodontic virtual treatment planning. However, fast and accurate identifying cutting boundary to separate teeth from dental model still remains a challenge, due to various geometrical shapes of teeth, complex tooth arrangements, different dental model qualities, and varying degrees of crowding problems. Most segmentation approaches presented before are not able to achieve a balance between fine segmentation results and simple operating procedures with less time consumption. In this article, we present a novel, effective and efficient framework that achieves tooth segmentation based on a segmentation field, which is solved by a linear system defined by a discrete Laplace-Beltrami operator with Dirichlet boundary conditions. A set of contour lines are sampled from the smooth scalar field, and candidate cutting boundaries can be detected from concave regions with large variations of field data. The sensitivity to concave seams of the segmentation field facilitates effective tooth partition, as well as avoids obtaining appropriate curvature threshold value, which is unreliable in some case. Our tooth segmentation algorithm is robust to dental models with low quality, as well as is effective to dental models with different levels of crowding problems. The experiments, including segmentation tests of varying dental models with different complexity, experiments on dental meshes with different modeling resolutions and surface noises and comparison between our method and the morphologic skeleton segmentation method are conducted, thus demonstrating the effectiveness of our method.
... For perspective projection, a correct approach is to trace rays from each billboard pixel p to the viewpoint; if a ray intersects the billboard's ball, the corresponding screen pixel v gets its color and depth from the ray-sphere intersection point x. This technique is also known under the name of impostors [McK12]. Ball splatting methods can generate shape reconstructions from skeletons of hundreds of thousand of points at interactive rates, as their speed is bounded only by the pixel fill rate of the GPU [JKT13]. ...
... [JKT13]. Impostor technique generates correct results for perspective projections [McK12]. ...
Given a shape, a skeleton is a thin centered structure which jointly describes the topology and the geometry of the shape. Skeletons provide an alternative to classical boundary or volumetric representations, which is especially effective for applications where one needs to reason about, and manipulate, the structure of a shape. These skeleton properties make them powerful tools for many types of shape analysis and processing tasks. For a given shape, several skeleton types can be defined, each having its own properties, advantages, and drawbacks. Similarly, a large number of methods exist to compute a given skeleton type, each having its own requirements, advantages, and limitations. While using skeletons for two-dimensional (2D) shapes is a relatively well covered area, developments in the skeletonization of three-dimensional (3D) shapes make these tasks challenging for both researchers and practitioners. This survey presents an overview of 3D shape skeletonization. We start by presenting the definition and properties of various types of 3D skeletons. We propose a taxonomy of 3D skeletons which allows us to further analyze and compare them with respect to their properties. We next overview methods and techniques used to compute all described 3D skeleton types, and discuss their assumptions, advantages, and limitations. Finally, we describe several applications of 3D skeletons, which illustrate their added value for different shape analysis and processing tasks.
