The Experts below are selected from a list of 2817 Experts worldwide ranked by ideXlab platform
Hao Zhang - One of the best experts on this subject based on the ideXlab platform.
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Skeleton-Intrinsic Symmetrization of Shapes
Computer Graphics Forum, 2015Co-Authors: Qian Zheng, Hao Zhang, Hui Huang, Kai Xu, Daniel Cohen-or, Baoquan ChenAbstract:Enhancing the self-symmetry of a shape is of fundamental aesthetic virtue. In this paper, we are interested in recovering the aesthetics of intrinsic reflection symmetries, where an asymmetric shape is symmetrized while keeping its general pose and perceived dynamics. The key challenge to intrinsic symmetrization is that the input shape has only approximate reflection symmetries, possibly far from perfect. The main premise of our work is that Curve Skeletons provide a concise and effective shape abstraction for analyzing approximate intrinsic symmetries as well as symmetrization. By measuring intrinsic distances over a Curve Skeleton for symmetry analysis, symmetrizing the Skeleton, and then propagating the symmetrization from Skeleton to shape, our approach to shape symmetrization is Skeleton-intrinsic. Specifically, given an input shape and an extracted Curve Skeleton, we introduce the notion of a backbone as the path in the Skeleton graph about which a self-matching of the input shape is optimal. We define an objective function for the reflective self-matching and develop an algorithm based on genetic programming to solve the global search problem for the backbone. The extracted backbone then guides the symmetrization of the Skeleton, which in turn, guides the symmetrization of the whole shape. We show numerous intrinsic symmetrization results of hand drawn sketches and artist-modeled or reconstructed 3D shapes, as well as several applications of Skeleton-intrinsic symmetrization of shapes.
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l 1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Shihao Wu, Minglun Gong, Guiqing Li, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
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l1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Minglun Gong, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
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Mean Curvature Skeletons
Computer Graphics Forum, 2012Co-Authors: Andrea Tagliasacchi, Ibraheem Alhashim, Matt Olson, Hao ZhangAbstract:Inspired by recent developments in contraction-based Curve Skeleton extraction, we formulate the Skeletonization problem via mean curvature flow (MCF). While the classical application of MCF is surface fairing, we take advantage of its area-minimizing characteristic to drive the curvature flow towards the extreme so as to collapse the input mesh geometry and obtain a skeletal structure. By analyzing the differential characteristics of the flow, we reveal that MCF locally increases shape anisotropy. This justifies the use of curvature motion for Skeleton computation, and leads to the generation of what we call “mean curvature Skeletons”. To obtain a stable and efficient discretization, we regularize the surface mesh by performing local remeshing via edge splits and collapses. Simplifying mesh connectivity throughout the motion leads to more efficient computation and avoids numerical instability arising from degeneracies in the triangulation. In addition, the detection of collapsed geometry is facilitated by working with simplified mesh connectivity and monitoring potential non-manifold edge collapses. With topology simplified throughout the flow, minimal post-processing is required to convert the collapsed geometry to a Curve. Formulating Skeletonization via MCF allows us to incorporate external energy terms easily, resulting in a constrained flow. We define one such energy term using the Voronoi medial Skeleton and obtain a medially centred Curve Skeleton. We call the intermediate results of our Skeletonization motion meso-Skeletons; these consist of a mixture of Curves and surface sheets as appropriate to the local 3D geometry they capture. © 2012 Wiley Periodicals, Inc.
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point cloud Skeletons via laplacian based contraction
Shape Modeling International Conference, 2010Co-Authors: Andrea Tagliasacchi, Matt Olson, Hao Zhang, Zhinxun SuAbstract:We present an algorithm for Curve Skeleton extraction via Laplacian-based contraction. Our algorithm can be applied to surfaces with boundaries, polygon soups, and point clouds. We develop a contraction operation that is designed to work on generalized discrete geometry data, particularly point clouds, via local Delaunay triangulation and topological thinning. Our approach is robust to noise and can handle moderate amounts of missing data, allowing Skeleton-based manipulation of point clouds without explicit surface reconstruction. By avoiding explicit reconstruction, we are able to perform Skeleton-driven topology repair of acquired point clouds in the presence of large amounts of missing data. In such cases, automatic surface reconstruction schemes tend to produce incorrect surface topology. We show that the Curve Skeletons we extract provide an intuitive and easy-to-manipulate structure for effective topology modification, leading to more faithful surface reconstruction.
Daniel Cohenor - One of the best experts on this subject based on the ideXlab platform.
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l1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Minglun Gong, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
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l 1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Shihao Wu, Minglun Gong, Guiqing Li, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
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Curve Skeleton extraction from incomplete point cloud
International Conference on Computer Graphics and Interactive Techniques, 2009Co-Authors: Andrea Tagliasacchi, Hao Zhang, Daniel CohenorAbstract:We present an algorithm for Curve Skeleton extraction from imperfect point clouds where large portions of the data may be missing. Our construction is primarily based on a novel notion of generalized rotational symmetry axis (ROSA) of an oriented point set. Specifically, given a subset S of oriented points, we introduce a variational definition for an oriented point that is most rotationally symmetric with respect to S. Our formulation effectively utilizes normal information to compensate for the missing data and leads to robust Curve Skeleton computation over regions of a shape that are generally cylindrical. We present an iterative algorithm via planar cuts to compute the ROSA of a point cloud. This is complemented by special handling of non-cylindrical joint regions to obtain a centered, topologically clean, and complete 1D Skeleton. We demonstrate that quality Curve Skeletons can be extracted from a variety of shapes captured by incomplete point clouds. Finally, we show how our algorithm assists in shape completion under these challenges by developing a Skeleton-driven point cloud completion scheme.
Alexandru Telea - One of the best experts on this subject based on the ideXlab platform.
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an unified multiscale framework for planar surface and Curve Skeletonization
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2016Co-Authors: Andrei C Jalba, Andre Sobiecki, Alexandru TeleaAbstract:Computing Skeletons of 2D shapes, and medial surface and Curve Skeletons of 3D shapes, is a challenging task. In particular, there is no unified framework that detects all types of Skeletons using a single model, and also produces a multiscale representation which allows to progressively simplify, or regularize, all Skeleton types. In this paper, we present such a framework. We model Skeleton detection and regularization by a conservative mass transport process from a shape’s boundary to its surface Skeleton, next to its Curve Skeleton, and finally to the shape center. The resulting density field can be thresholded to obtain a multiscale representation of progressively simplified surface, or Curve, Skeletons. We detail a numerical implementation of our framework which is demonstrably stable and has high computational efficiency. We demonstrate our framework on several complex 2D and 3D shapes.
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surface and Curve Skeletonization of large 3d models on the gpu
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2013Co-Authors: Andrei C Jalba, Jacek Kustra, Alexandru TeleaAbstract:We present a GPU-based framework for extracting surface and Curve Skeletons of 3D shapes represented as large polygonal meshes. We use an efficient parallel search strategy to compute point-cloud Skeletons and their distance and feature transforms (FTs) with user-defined precision. We regularize Skeletons by a new GPU-based geodesic tracing technique which is orders of magnitude faster and more accurate than comparable techniques. We reconstruct the input surface from Skeleton clouds using a fast and accurate image-based method. We also show how to reconstruct the skeletal manifold structure as a polygon mesh and the Curve Skeleton as a polyline. Compared to recent Skeletonization methods, our approach offers two orders of magnitude speed-up, high-precision, and low-memory footprints. We demonstrate our framework on several complex 3D models.
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probabilistic view based 3d Curve Skeleton computation on the gpu
International Conference on Computer Vision Theory and Applications, 2013Co-Authors: Jacek Kustra, Andrei C Jalba, Alexandru TeleaAbstract:Computing Curve Skeletons of 3D shapes is a challenging task. Recently, a high-potential technique for this task was proposed, based on integrating medial information obtained from several 2D projections of a 3D shape. However effective, this technique is strongly influenced in terms of complexity by the quality of a so-called Skeleton probability volume, which encodes potential 3D Curve-Skeleton locations. In this paper, we extend the above method to deliver a highly accurate and discriminative Curve-Skeleton probability volume. For this, we analyze the error sources of the original technique, and propose improvements in terms of accuracy, culling false positives, and speed. We show that our technique can deliver point-cloud Curve-Skeletons which are close to the desired locations, even in the absence of complex postprocessing. We demonstrate our technique on several 3D models.
Baoquan Chen - One of the best experts on this subject based on the ideXlab platform.
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Skeleton-Intrinsic Symmetrization of Shapes
Computer Graphics Forum, 2015Co-Authors: Qian Zheng, Hao Zhang, Hui Huang, Kai Xu, Daniel Cohen-or, Baoquan ChenAbstract:Enhancing the self-symmetry of a shape is of fundamental aesthetic virtue. In this paper, we are interested in recovering the aesthetics of intrinsic reflection symmetries, where an asymmetric shape is symmetrized while keeping its general pose and perceived dynamics. The key challenge to intrinsic symmetrization is that the input shape has only approximate reflection symmetries, possibly far from perfect. The main premise of our work is that Curve Skeletons provide a concise and effective shape abstraction for analyzing approximate intrinsic symmetries as well as symmetrization. By measuring intrinsic distances over a Curve Skeleton for symmetry analysis, symmetrizing the Skeleton, and then propagating the symmetrization from Skeleton to shape, our approach to shape symmetrization is Skeleton-intrinsic. Specifically, given an input shape and an extracted Curve Skeleton, we introduce the notion of a backbone as the path in the Skeleton graph about which a self-matching of the input shape is optimal. We define an objective function for the reflective self-matching and develop an algorithm based on genetic programming to solve the global search problem for the backbone. The extracted backbone then guides the symmetrization of the Skeleton, which in turn, guides the symmetrization of the whole shape. We show numerous intrinsic symmetrization results of hand drawn sketches and artist-modeled or reconstructed 3D shapes, as well as several applications of Skeleton-intrinsic symmetrization of shapes.
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l 1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Shihao Wu, Minglun Gong, Guiqing Li, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
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l1 medial Skeleton of point cloud
International Conference on Computer Graphics and Interactive Techniques, 2013Co-Authors: Hui Huang, Hao Zhang, Daniel Cohenor, Minglun Gong, Baoquan ChenAbstract:We introduce L1-medial Skeleton as a Curve Skeleton representation for 3D point cloud data. The L1-median is well-known as a robust global center of an arbitrary set of points. We make the key observation that adapting L1-medians locally to a point set representing a 3D shape gives rise to a one-dimensional structure, which can be seen as a localized center of the shape. The primary advantage of our approach is that it does not place strong requirements on the quality of the input point cloud nor on the geometry or topology of the captured shape. We develop a L1-medial Skeleton construction algorithm, which can be directly applied to an unoriented raw point scan with significant noise, outliers, and large areas of missing data. We demonstrate L1-medial Skeletons extracted from raw scans of a variety of shapes, including those modeling high-genus 3D objects, plant-like structures, and Curve networks.
Gabriella Sanniti Di Baja - One of the best experts on this subject based on the ideXlab platform.
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distance driven Skeletonization in voxel images
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2011Co-Authors: C Arcelli, Gabriella Sanniti Di Baja, L SerinoAbstract:A distance-driven method to compute the surface and Curve Skeletons of 3D objects in voxel images is described. The method is based on the use of the ; weighted distance transform, on the detection of anchor points, and on the application of topology preserving removal operations. The obtained surface and Curve Skeletons are centered within the object, have the same topology as the object, and have unit thickness. The object can be almost completely recovered from the surface Skeleton since this includes almost all of the centers of maximal balls of the object. Hence, the surface Skeleton is a faithful representation. In turn, though only partial recovery is possible from the Curve Skeleton, this still provides an appealing representation of the object.
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Skeletonizing volume objects part 2 from surface to Curve Skeleton
Lecture Notes in Computer Science, 1998Co-Authors: Gunilla Borgefors, Ingela Nyström, Gabriella Sanniti Di BajaAbstract:Volume imaging techniques are becoming common and Skeletonization has begun to prove valuable for shape analysis also in 3D. In this paper, a method to reduce solid volume objects to their 3D Curve Skeletons is presented. The method consists of two major steps. The first step is aimed at the computation of the surface Skeleton, and is an improvement of a previous method. In the second step, the surface Skeleton is further reduced to the 3D Curve Skeleton. Our Skeletonization method preserves topology; no disconnections, holes or tunnels are created. It also preserves the general geometry of the object, especially in the case of elongated objects. Resulting Skeletons for a number of synthetic and real images are presented.
