The Experts below are selected from a list of 106452 Experts worldwide ranked by ideXlab platform

Andreas Fabri - One of the best experts on this subject based on the ideXlab platform.

  • cgal the Computational Geometry algorithms library
    International Conference on Computer Graphics and Interactive Techniques, 2016
    Co-Authors: Pierre Alliez, Andreas Fabri
    Abstract:

    This course provides an overview of CGAL geometric algorithms and data structures. We start with a presentation the objectives and scope of the CGAL open source project. The three next parts cover SIGGRAPH topics: (1) CGAL for point set processing, including denoising, outlier removal, smoothing, resampling, curvature estimation, shape detection and surface reconstruction, (2) CGAL for polygon mesh processing, including Boolean operations, deformation, skeletonization, segmentation, hole filling, isotropic remeshing, simplification, and (3) CGAL for mesh generation, including surface and volume mesh generation, from either 3D images, implicit functions or surface meshes.

  • cgal the Computational Geometry algorithms library
    Advances in Geographic Information Systems, 2009
    Co-Authors: Andreas Fabri, Sylvain Pion
    Abstract:

    We present fundamental geometric data structures and algorithms offered by CGAL, the Computational Geometry Algorithms Library. As Geometry is ubiquitous this library is used by application developers in medical imaging, VLSI, CAD/CAM, geophysics, computer graphics and last but not least GIS. In this demo we focus on those parts of CGAL which are relevant for geographic information systems software development.

  • Computational Geometry algorithms library
    International Conference on Computer Graphics and Interactive Techniques, 2008
    Co-Authors: Pierre Alliez, Andreas Fabri, Efi Fogel
    Abstract:

    The CGAL C++ library offers geometric data structures and algorithms that are reliable, efficient, easy to use, and easy to integrate in existing software. Use of de facto standard libraries like CGAL increases productivity, because they allow software developers to focus on the application layer. This course is an overview of CGAL geometric algorithms and data structures. The lectures cover:•CGAL for 2D vector graphics, including Boolean operations on Bezier curves, offsets, simplification, and Geometry on the sphere.•CGAL for 3D point sets, including principal component analysis, bounding volumes, simplification, outlier removal, normal estimation, normal orientation, denoising, triangulation, and surface reconstruction.•CGAL for mesh-based modeling and processing, including Boolean operations, convex decomposition, simplification, and parameterization.•CGAL for mesh generation, including surface and volume mesh generation, from 3D images, implicit functions, or polyhedral surfaces.The introductory lecture covers non-geometric topics: the exact geometric computing paradigm that makes CGAL reliable without sacrificing efficiency and the generic programming paradigm that facilitates integration into existing software.

  • on the design of cgal a Computational Geometry algorithms library
    Software - Practice and Experience, 2000
    Co-Authors: Andreas Fabri, Stefan Schirra, Geertjan Giezeman, Lutz Kettner, Sven Schonherr
    Abstract:

    CGAL is a Computational Geometry Algorithms Library written in C++. The goal is to make the large body of geometric algorithms developed inthe field of Computational Geometry available for industrial application. In this report we discuss the major design goals for CGAL, which are correctne- ss, flexibility, ease-of-use, efficiency, and robustness, and present our approach to reach these goals. Templates and the relatively new generic programming play a central role in the architecture of CGAL. We give a short introduction to generic programming in C++, compare it to the object-oriented programming paradigm, and present examples where both paradigms are used effectively in CGAL. Moreover, we give an overview on the current structure of the library and consider software engineering aspects in the CGAL-project.

  • scalable parallel Computational Geometry for coarse grained multicomputers
    International Journal of Computational Geometry and Applications, 1996
    Co-Authors: Frank Dehne, Andreas Fabri, Andrew Rauchaplin
    Abstract:

    We study scalable parallel Computational Geometry algorithms for the coarse grained multicomputer model: p processors solving a problem on n data items, were each processor has O(n/p)≫O(1) local memory and all processors are connected via some arbitrary interconnection network (e.g. mesh, hypercube, fat tree). We present O(Tsequential/p+Ts(n, p)) time scalable parallel algorithms for several Computational Geometry problems. Ts(n, p) refers to the time of a global sort operation. Our results are independent of the multicomputer’s interconnection network. Their time complexities become optimal when Tsequential/p dominates Ts(n, p) or when Ts(n, p) is optimal. This is the case for several standard architectures, including meshes and hypercubes, and a wide range of ratios n/p that include many of the currently available machine configurations. Our methods also have some important practical advantages: For interprocessor communication, they use only a small fixed number of one global routing operation, global sort, and all other programming is in the sequential domain. Furthermore, our algorithms use only a small number of very large messages, which greatly reduces the overhead for the communication protocol between processors. (Note however, that our time complexities account for the lengths of messages.) Experiments show that our methods are easy to implement and give good timing results.

Yenwen Chen - One of the best experts on this subject based on the ideXlab platform.

  • Computational Geometry based distributed coverage hole detection protocol for the wireless sensor networks
    Journal of Network and Computer Applications, 2011
    Co-Authors: Prasan Kumar Sahoo, Yenwen Chen
    Abstract:

    In wireless sensor networks, the purpose of surveillance cannot be fulfilled if coverage holes are generated due to accidental death of the nodes caused due to technical failures, explosions and malicious activities or power exhaustion. Since, sensors are normally deployed randomly over the dense forests and harsh terrains, it is not possible to find out the coverage holes manually. Hence, in this work a Computational Geometry approach based distributed hole detection protocol is designed to find out the coverage holes in a post deployment scenario. An efficient geometric method with proper theoretical basis is used to detect the coverage holes of the wireless sensor network, where communication and sensing range of the nodes are same. Performance evaluation of our protocol shows that the hole detection time and energy consumption due to hole detection outperforms over similar hole detection protocols.

Efi Fogel - One of the best experts on this subject based on the ideXlab platform.

  • Computational Geometry algorithms library
    International Conference on Computer Graphics and Interactive Techniques, 2008
    Co-Authors: Pierre Alliez, Andreas Fabri, Efi Fogel
    Abstract:

    The CGAL C++ library offers geometric data structures and algorithms that are reliable, efficient, easy to use, and easy to integrate in existing software. Use of de facto standard libraries like CGAL increases productivity, because they allow software developers to focus on the application layer. This course is an overview of CGAL geometric algorithms and data structures. The lectures cover:•CGAL for 2D vector graphics, including Boolean operations on Bezier curves, offsets, simplification, and Geometry on the sphere.•CGAL for 3D point sets, including principal component analysis, bounding volumes, simplification, outlier removal, normal estimation, normal orientation, denoising, triangulation, and surface reconstruction.•CGAL for mesh-based modeling and processing, including Boolean operations, convex decomposition, simplification, and parameterization.•CGAL for mesh generation, including surface and volume mesh generation, from 3D images, implicit functions, or polyhedral surfaces.The introductory lecture covers non-geometric topics: the exact geometric computing paradigm that makes CGAL reliable without sacrificing efficiency and the generic programming paradigm that facilitates integration into existing software.

  • code flexibility and program efficiency by genericity improving cgal s arrangements
    European Symposium on Algorithms, 2004
    Co-Authors: Efi Fogel, Ron Wein, Dan Halperin
    Abstract:

    Arrangements of planar curves are fundamental structures in Computational Geometry. We describe the recent developments in the arrangement package of Cgal, the Computational Geometry Algorithms Library, making it easier to use, to extend and to adapt to a variety of applications. This improved flexibility of the code does not come at the expense of efficiency as we mainly use generic-programming techniques, which make dexterous use of the compilation process. To the contrary, we expedited key operations as we demonstrate by experiments.

Joachim Ziegler - One of the best experts on this subject based on the ideXlab platform.

  • a Computational basis for higher dimensional Computational Geometry and applications
    Computational Geometry: Theory and Applications, 1998
    Co-Authors: Kurt Mehlhorn, Stefan Naher, Stefan Schirra, Michael Seel, Christian Uhrig, Michael Müller, Joachim Ziegler
    Abstract:

    Abstract In this paper we describe and discuss a kernel for higher-dimensional Computational Geometry and we present its application in the calculation of convex hulls and Delaunay triangulations. The kernel is available in form of a software library module programmed in C++ extending LEDA. We introduce the basic data types like points, vectors, directions, hyperplanes, segments, rays, lines, spheres, affine transformations, and operations connecting these types. The description consists of a motivation for the basic class layout as well as topics like layered software design, runtime correctness via checking routines and documentation issues. Finally we shortly describe the usage of the kernel in the application domain.

  • a Computational basis for higher dimensional Computational Geometry and applications
    Symposium on Computational Geometry, 1997
    Co-Authors: Kurt Mehlhorn, Stefan Naher, Stefan Schirra, Michael Seel, Christian Uhrig, Michael Müller, Joachim Ziegler
    Abstract:

    In this paper we describe and discuss a kernel for higher-dimensional Computational Geometry and we present its application in the calculation of convex hulls and Delaunay triangulations. The kernel is available in form of a software library module programmed in C++ extending LEDA. We introduce the basic data types like points, vectors, directions, hyperplanes, segments, rays, lines, spheres, affine transformations, and operations connecting these types. The description consists of a motivation for the basic class layout as well as topics like layered software design, runtime correctness via checking routines and documentation issues. Finally we shortly describe the usage of the kernel in the application domain. © 1998 Elsevier Science B.V.

L M Moskal - One of the best experts on this subject based on the ideXlab platform.

  • Computational Geometry based retrieval of effective leaf area index using terrestrial laser scanning
    IEEE Transactions on Geoscience and Remote Sensing, 2012
    Co-Authors: Guang Zheng, L M Moskal
    Abstract:

    Quantifying the 3-D forest canopy structure and leaf area index of an individual tree or a forest stand is challenging. The canopy structural information implicitly contained within point cloud data (PCD) generated from terrestrial laser scanning (TLS) makes it possible to characterize directly the spatial distribution of foliage elements. In this paper, a new voxel-based method titled “point cloud slicing” is presented to retrieve the biophysical characteristics of the forest canopy including extinction coefficient, gap fraction, overlapping effect, and effective leaf area (ELA) from PCD. These extractions were performed not only from the whole canopy but also from layers of the canopy to depict the distribution patterns of foliage elements within the canopy. The results showed that the TLS-based ELA estimation method could explain 88.7% (rmse = 0.007, p <; 0.001, and n = 30) variation of the destructive-sample-based leaf area measurement results. It was found that the sampling resolution was a key parameter in defining the dimension of a single voxel. Furthermore, the TLS-based method can also serve as a calibration tool for airborne laser scanning application with ground sampling.