"Greedy triangulation"의 두 판 사이의 차이

수학노트
둘러보기로 가기 검색하러 가기
(→‎노트: 새 문단)
 
(→‎노트: 새 문단)
22번째 줄: 22번째 줄:
 
# neigh_orient_tol <alpha> reports the surface curvature parameter 'alpha' "alpha" "alpha" "alpha" "alpha" "alpha" in degrees that was used for the triangulation.<ref name="ref_8ccecd41" />
 
# neigh_orient_tol <alpha> reports the surface curvature parameter 'alpha' "alpha" "alpha" "alpha" "alpha" "alpha" in degrees that was used for the triangulation.<ref name="ref_8ccecd41" />
 
# implicit'"implicit""implicit""implicit""implicit""implicit" an implicit triangulation algorithm based on a Poisson solver (see the paper in References) is invoked.<ref name="ref_8ccecd41" />
 
# implicit'"implicit""implicit""implicit""implicit""implicit" an implicit triangulation algorithm based on a Poisson solver (see the paper in References) is invoked.<ref name="ref_8ccecd41" />
 +
===소스===
 +
<references />
 +
 +
== 노트 ==
 +
 +
===위키데이터===
 +
* ID :  [https://www.wikidata.org/wiki/Q28811699 Q28811699]
 +
===말뭉치===
 +
# We present a new method for testing compatibility of candidate edges in the greedy triangulation, and new results on the rank of edges in various triangulations.<ref name="ref_98811a4b">[https://www.sciencedirect.com/science/article/pii/S0925772197891493 Fast greedy triangulation algorithms ☆]</ref>
 +
# Based on these results, we present fast greedy triangulation algorithms with expected case running time of O(n log n) for uniform distributions over convex regions.<ref name="ref_98811a4b" />
 +
# We prove that the greedy triangulation heuristic for minimum weight triangulation of convex polygons yields solutions within a constant factor from the optimum.<ref name="ref_c0e53a57">[https://link.springer.com/content/pdf/10.1007/BF01840358.pdf On approximation behavior of the greedy triangulation for convex polygons]</ref>
 +
# bound on the approximation factor of the Delaunay triangulation heuristic for minimum weight triangulation of convexn-vertex polygons.<ref name="ref_c0e53a57" />
 +
# Finally, we observe that the greedy triangulation for convex polygons having so-called semicircular property can be constructed in timeO(n logn).<ref name="ref_c0e53a57" />
 +
# Since we use more knowledge about the structure of a random point set and its greedy triangulation, our algorithm needs only elementary data structures and simple bucketing techniques.<ref name="ref_76612a8f">[http://www.ist.tugraz.at/publication2/abstracts/adr-sltgt-95/index.html A Simple Linear Time Greedy Triangulation Algorithm for Uniformly Distributed Points]</ref>
 +
# Rather than solve one problem, this is based on propose to Delaunay Triangulation as an alternative for different application on the area.<ref name="ref_65949268">[https://www.researchgate.net/publication/263413000_Fast_Greedy_Triangulation_Algorithms (PDF) Fast Greedy Triangulation Algorithms.]</ref>
 +
# GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections.<ref name="ref_8cacf5dc">[https://pdal.io/stages/filters.greedyprojection.html filters.greedyprojection — pdal.io]</ref>
 +
# First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation.<ref name="ref_c0de9c57">[https://www.mdpi.com/2076-3417/8/10/1776 3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation]</ref>
 +
# We also prove properties about the expected lengths of edges in greedy and Delaunay triangulations of uniformly distributed points.<ref name="ref_56acbf1a">[https://digitalcommons.dartmouth.edu/cs_tr/92/ Fast Greedy Triangulation Algorithms]</ref>
 +
# 1) times the length of a minimum weight triangulation of the polygon (under the assumption that no three vertices lie on the same line).<ref name="ref_494bed4e">[http://www.diva-portal.org/smash/record.jsf?pid=diva2:1307638 New results about the approximation behavior of the greedy triangulation]</ref>
 +
# Finally, a simple linear-time algorithm is presented and analyzed for computing greedy triangulations of polygons with the so called semi-circle property.<ref name="ref_494bed4e" />
 +
# A common approach for finding good decompositions is iteratively executing a greedy triangulation algorithm (e.g. minfill) with randomized tie-breaking.<ref name="ref_4f250903">[https://openreview.net/forum?id=Hy48SAgubS Stopping Rules for Randomized Greedy Triangulation Schemes]</ref>
 +
# Don't consider points for triangulation if their normal deviates more than this value from the query point's normal.<ref name="ref_c95d7f31">[https://pointclouds.org/documentation/classpcl_1_1_greedy_projection_triangulation.html Point Cloud Library (PCL): pcl::GreedyProjectionTriangulation< PointInT > Class Template Reference]</ref>
 +
# By selecting MethodMethodMethodMethodMethodmethod ='greedy'"greedy""greedy""greedy""greedy""greedy", a so called greedy triangulation algorithm is invoked.<ref name="ref_8ccecd41">[https://www.mvtec.com/doc/halcon/13/en/triangulate_object_model_3d.html 3d [HALCON Operator Reference / Version 13.0.4]]</ref>
 +
# The greedy triangulation algorithm starts by initializing a surface with one triangle constructed from three SNC-eligible, neighboring points.<ref name="ref_8ccecd41" />
 +
# neigh_orient_tol <alpha> reports the surface curvature parameter 'alpha' "alpha" "alpha" "alpha" "alpha" "alpha" in degrees that was used for the triangulation.<ref name="ref_8ccecd41" />
 +
# implicit'"implicit""implicit""implicit""implicit""implicit" an implicit triangulation algorithm based on a Poisson solver (see the paper in References) is invoked.<ref name="ref_8ccecd41" />
 +
# Computing the triangulation of a polygon is a fundamental algorithm in computational geometry.<ref name="ref_0d2be8b4">[http://gamma.cs.unc.edu/SEIDEL/ Fast Polygon Triangulation Based on Seidel's Algorithm]</ref>
 +
# The triangulation does not introduce any additional vertices and decomposes the polygon into n-2 triangles.<ref name="ref_0d2be8b4" />
 +
# This measure can also be calculated based on two other dimensions of the network: the Minimum Spanning Tree (MST) and the Greedy Triangulation (GT).<ref name="ref_5ac45dc0">[https://transportgeography.org/?page_id=6107 Cost in a Graph]</ref>
 +
# The Greedy Triangulation (GT) adds missing links between all nodes so as to make it complete (maximal) without breaking its planarity (C).<ref name="ref_5ac45dc0" />
 +
# Triangulation is performed locally, by projecting the local neighborhood of a point along the point’s normal, and connecting unconnected points.<ref name="ref_f53e1dec">[https://pcl.readthedocs.io/projects/tutorials/en/latest/greedy_projection.html Fast triangulation of unordered point clouds — Point Cloud Library 0.0 documentation]</ref>
 
===소스===
 
===소스===
 
  <references />
 
  <references />

2020년 12월 23일 (수) 05:00 판

노트

위키데이터

말뭉치

  1. We present a new method for testing compatibility of candidate edges in the greedy triangulation, and new results on the rank of edges in various triangulations.[1]
  2. Based on these results, we present fast greedy triangulation algorithms with expected case running time of O(n log n) for uniform distributions over convex regions.[1]
  3. We prove that the greedy triangulation heuristic for minimum weight triangulation of convex polygons yields solutions within a constant factor from the optimum.[2]
  4. bound on the approximation factor of the Delaunay triangulation heuristic for minimum weight triangulation of convexn-vertex polygons.[2]
  5. Finally, we observe that the greedy triangulation for convex polygons having so-called semicircular property can be constructed in timeO(n logn).[2]
  6. First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation.[3]
  7. Rather than solve one problem, this is based on propose to Delaunay Triangulation as an alternative for different application on the area.[4]
  8. GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections.[5]
  9. Since we use more knowledge about the structure of a random point set and its greedy triangulation, our algorithm needs only elementary data structures and simple bucketing techniques.[6]
  10. We also prove properties about the expected lengths of edges in greedy and Delaunay triangulations of uniformly distributed points.[7]
  11. 1) times the length of a minimum weight triangulation of the polygon (under the assumption that no three vertices lie on the same line).[8]
  12. Finally, a simple linear-time algorithm is presented and analyzed for computing greedy triangulations of polygons with the so called semi-circle property.[8]
  13. A common approach for finding good decompositions is iteratively executing a greedy triangulation algorithm (e.g. minfill) with randomized tie-breaking.[9]
  14. Don't consider points for triangulation if their normal deviates more than this value from the query point's normal.[10]
  15. By selecting MethodMethodMethodMethodMethodmethod ='greedy'"greedy""greedy""greedy""greedy""greedy", a so called greedy triangulation algorithm is invoked.[11]
  16. The greedy triangulation algorithm starts by initializing a surface with one triangle constructed from three SNC-eligible, neighboring points.[11]
  17. neigh_orient_tol <alpha> reports the surface curvature parameter 'alpha' "alpha" "alpha" "alpha" "alpha" "alpha" in degrees that was used for the triangulation.[11]
  18. implicit'"implicit""implicit""implicit""implicit""implicit" an implicit triangulation algorithm based on a Poisson solver (see the paper in References) is invoked.[11]

소스

  1. ↑ 1.0 1.1 Fast greedy triangulation algorithms ☆
  2. ↑ 2.0 2.1 2.2 On approximation behavior of the greedy triangulation for convex polygons
  3. ↑ 3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation
  4. ↑ (PDF) Fast Greedy Triangulation Algorithms.
  5. ↑ filters.greedyprojection — pdal.io
  6. ↑ A Simple Linear Time Greedy Triangulation Algorithm for Uniformly Distributed Points
  7. ↑ Fast Greedy Triangulation Algorithms
  8. ↑ 8.0 8.1 New results about the approximation behavior of the greedy triangulation
  9. ↑ Stopping Rules for Randomized Greedy Triangulation Schemes
  10. ↑ Point Cloud Library (PCL): pcl::GreedyProjectionTriangulation< PointInT > Class Template Reference
  11. ↑ 11.0 11.1 11.2 11.3 3d [HALCON Operator Reference / Version 13.0.4]

노트

위키데이터

말뭉치

  1. We present a new method for testing compatibility of candidate edges in the greedy triangulation, and new results on the rank of edges in various triangulations.[1]
  2. Based on these results, we present fast greedy triangulation algorithms with expected case running time of O(n log n) for uniform distributions over convex regions.[1]
  3. We prove that the greedy triangulation heuristic for minimum weight triangulation of convex polygons yields solutions within a constant factor from the optimum.[2]
  4. bound on the approximation factor of the Delaunay triangulation heuristic for minimum weight triangulation of convexn-vertex polygons.[2]
  5. Finally, we observe that the greedy triangulation for convex polygons having so-called semicircular property can be constructed in timeO(n logn).[2]
  6. Since we use more knowledge about the structure of a random point set and its greedy triangulation, our algorithm needs only elementary data structures and simple bucketing techniques.[3]
  7. Rather than solve one problem, this is based on propose to Delaunay Triangulation as an alternative for different application on the area.[4]
  8. GreedyProjectionTriangulation is an implementation of a greedy triangulation algorithm for 3D points based on local 2D projections.[5]
  9. First, the feature information is comprehensively described using FPFH feature description and the local correlation of the feature information is established using greedy projection triangulation.[6]
  10. We also prove properties about the expected lengths of edges in greedy and Delaunay triangulations of uniformly distributed points.[7]
  11. 1) times the length of a minimum weight triangulation of the polygon (under the assumption that no three vertices lie on the same line).[8]
  12. Finally, a simple linear-time algorithm is presented and analyzed for computing greedy triangulations of polygons with the so called semi-circle property.[8]
  13. A common approach for finding good decompositions is iteratively executing a greedy triangulation algorithm (e.g. minfill) with randomized tie-breaking.[9]
  14. Don't consider points for triangulation if their normal deviates more than this value from the query point's normal.[10]
  15. By selecting MethodMethodMethodMethodMethodmethod ='greedy'"greedy""greedy""greedy""greedy""greedy", a so called greedy triangulation algorithm is invoked.[11]
  16. The greedy triangulation algorithm starts by initializing a surface with one triangle constructed from three SNC-eligible, neighboring points.[11]
  17. neigh_orient_tol <alpha> reports the surface curvature parameter 'alpha' "alpha" "alpha" "alpha" "alpha" "alpha" in degrees that was used for the triangulation.[11]
  18. implicit'"implicit""implicit""implicit""implicit""implicit" an implicit triangulation algorithm based on a Poisson solver (see the paper in References) is invoked.[11]
  19. Computing the triangulation of a polygon is a fundamental algorithm in computational geometry.[12]
  20. The triangulation does not introduce any additional vertices and decomposes the polygon into n-2 triangles.[12]
  21. This measure can also be calculated based on two other dimensions of the network: the Minimum Spanning Tree (MST) and the Greedy Triangulation (GT).[13]
  22. The Greedy Triangulation (GT) adds missing links between all nodes so as to make it complete (maximal) without breaking its planarity (C).[13]
  23. Triangulation is performed locally, by projecting the local neighborhood of a point along the point’s normal, and connecting unconnected points.[14]

소스

  1. ↑ 1.0 1.1 Fast greedy triangulation algorithms ☆
  2. ↑ 2.0 2.1 2.2 On approximation behavior of the greedy triangulation for convex polygons
  3. ↑ A Simple Linear Time Greedy Triangulation Algorithm for Uniformly Distributed Points
  4. ↑ (PDF) Fast Greedy Triangulation Algorithms.
  5. ↑ filters.greedyprojection — pdal.io
  6. ↑ 3-D Point Cloud Registration Algorithm Based on Greedy Projection Triangulation
  7. ↑ Fast Greedy Triangulation Algorithms
  8. ↑ 8.0 8.1 New results about the approximation behavior of the greedy triangulation
  9. ↑ Stopping Rules for Randomized Greedy Triangulation Schemes
  10. ↑ Point Cloud Library (PCL): pcl::GreedyProjectionTriangulation< PointInT > Class Template Reference
  11. ↑ 11.0 11.1 11.2 11.3 3d [HALCON Operator Reference / Version 13.0.4]
  12. ↑ 12.0 12.1 Fast Polygon Triangulation Based on Seidel's Algorithm
  13. ↑ 13.0 13.1 Cost in a Graph
  14. ↑ Fast triangulation of unordered point clouds — Point Cloud Library 0.0 documentation
원본 주소 "https://wiki.mathnt.net/index.php?title=Greedy_triangulation&oldid=46730"