当前课程知识点:计算几何 > 05. Delaunay Triangulation > H. Construction > 05-H-03. Maximizing The Minimum Angle
实际上我们刚才通过dual graph
所引入的那种Delaunay triangulation
就会有这么样一个趋势
它会在几何上
使得在所有的
那些可能的三角剖分中
使得其中所用的三角形
尽量的避免这种狭长的
或者说比较畸形的三角形
或者反过来
它会尽可能的使得
每一个三角形
都尽可能的匀称 均衡
让我们来看这样一个具体的实例
同样是四个点
构成的一个凸四边形
所以区别依然在于
到底选用是这条还是这条对角线
我们可以看到Delaunay三角剖分
它要求处处是空圆
所以显然
它应该采用这条对角线
反过来
而不会去采用这条对角线
因为如果采用这条对角线
会存在这么样一个
非空的外接圆
好 我们姑且抛开
刚才那个选取的原则
我们来看效果
同样是这样的一个四边形
难道我们不更应该倾向于
按Delaunay所建议的
那种方案去剖分吗
因为至少按照这样剖分
所得的两个三角形
在几何的形体的
各个方向的比例上
更协调一些
而反过来
如果是按这种方式剖出来的话
我们确实可以看到
出现了相对而言
狭长甚至极端狭长的三角形
从这点讲我们可以说
Delaunay三角剖分是非常聪明的
它可以避免这种畸形的出现
那为什么会避免
这种畸形的出现呢
其实我们可以概括来说
Delaunay三角剖分
会有这么样一个趋势
它会尽可能的
使得我们刚才说的
那个角度序列极大化
使它尽可能的大
那我们知道
任何一个角度序列
取决于它的大小的
首先是前面的那个
相对更小的角
所以要使它更大
就应该会使它那个
尽可能小的角更大
这就是我们为什么称它叫做
maximizing the minimum angle
也就是使得最小角能够最大
那么Delaunay三角剖分
为什么能够实现这种
使最小角最大化的效果呢
-Before we start
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-Evaluation
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-Online Judge
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-Lecture notes
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-Discussion
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-A. History of This Course
--00-A. History of This Course
-B. What's Computational Geometry
--00-B. What's Computational Geometry
-B. What's Computational Geometry--作业
-C. How to Learn CG Better
--00-C. How to Learn CG Better
-C. How to Learn CG Better--作业
-D. Why English
-A. Convexity
-A. Convexity--作业
-B. Extreme Points
-B. Extreme Points--作业
-C. Extreme Edges
-C. Extreme Edges--作业
-D. Incremental Construction
--01-D-01. Decrease and Conquer
--01-D-02. In-Convex-Polygon Test
--01-D-03. Why Not Binary Search
-D. Incremental Construction--作业
-E. Jarvis March
--01-E-06. Lowest-Then-Leftmost
-E. Jarvis March--作业
-F. Lower Bound
--01-F-02. CAO Chong's Methodology
-F. Lower Bound--作业
-G. Graham Scan: Algorithm
-G. Graham Scan: Algorithm--作业
-H. Graham Scan: Example
-H. Graham Scan: Example--作业
-I. Graham Scan: Correctness
-I. Graham Scan: Correctness--作业
-J. Graham Scan: Analysis
-J. Graham Scan: Analysis--作业
-K. Divide-And-Conquer (1)
-K. Divide-And-Conquer (1)--作业
-L. Divide-And-Conquer (2)
--01-L-03. Topmost + Bottommost ?
--01-L-07. More Considerations
-L. Divide-And-Conquer (2)--作业
-M. Wrap-Up
-0. Introduction
-0. Introduction--作业
-A. Preliminary
-A. Preliminary--作业
-B. Interval Intersection Detection
-B. Interval Intersection Detection--作业
-C. Segment Intersection Reporting
-C. Segment Intersection Reporting--作业
-D. BO Algorithm: Strategy
--02-D-01. Proximity & Separability
--02-D-02. Comparability & Ordering
-D. BO Algorithm: Strategy--作业
-E. BO Algorithm: Implementation
--02-E-03. Events & Operations
-E. BO Algorithm: Implementation--作业
-F. BO Algorithm: Analysis
--02-F-04. Complexity of Event Queue
--02-F-05. Complexity of Status Structure
-F. BO Algorithm: Analysis--作业
-G. Convex Polygon Intersection Detection
--02-G-01. Problem Specification
--02-G-02. Monotone Partitioning
--02-G-04. Decrease-And-Conquer
-G. Convex Polygon Intersection Detection--作业
-H. Edge Chasing
--02-H-01. Eliminating Sickles
-H. Edge Chasing--作业
-I. Plane Sweeping
-I. Plane Sweeping--作业
-J. Halfplane Intersection Construction
-J. Halfplane Intersection Construction--作业
-0. Methodology
-0. Methodology--作业
-A. Art Gallery Problem
--03-A-02. Lower & Upper Bounds
--03-A-04. Approximation & Classification
-A. Art Gallery Problem--作业
-B. Art Gallery Theorem
--03-B-01. Necessity of floor(n/3)
--03-B-02. Sufficiency by Fan Decomposition
-B. Art Gallery Theorem--作业
-C. Fisk's Proof
--03-C-04. Pigeon-Hole Principle
-C. Fisk's Proof--作业
-D. Orthogonal Polygons
--03-D-01. Necessity of floor(n/4)
--03-D-02. Sufficiency by Convex Quadrilateralization
-D. Orthogonal Polygons--作业
-E. Triangulation
-E. Triangulation--作业
-F. Triangulating Monotone Polygons
--03-F-02. Monotonicity Testing
--03-F-04. Stack-Chain Consistency
-F. Triangulating Monotone Polygons--作业
-G. Monotone Decomposition
-G. Monotone Decomposition--作业
-I. Tetrahedralization
--03-I-01. Polyhedron Decomposition
--03-I-02. Schonhardt's Polyhedron
-I. Tetrahedralization--作业
-A. Introduction
--04-A-02. Dining Halls on Campus
--04-A-03. More Analogies & Applications
-A. Introduction--作业
-B. Terminologies
--04-B-02. Intersecting Halfspaces
--04-B-04. Planar Voronoi Diagram
-B. Terminologies--作业
-C. Properties
--04-C-03. Nearest = Concyclic
--04-C-04. Number of Nearest Sites = Degree
-C. Properties--作业
-D. Complexity
-D. Complexity--作业
-E. Representation
-E. Representation--作业
-F. DCEL
-F. DCEL--作业
-G. Hardness
--04-G-03. Voronoi Diagram In General Position
-G. Hardness--作业
-H. Sorted Sets
--04-H-01. Convex Hull Made Easier
--04-H-02. Convex Hull As A Combinatorial Structure
--04-H-03. Voronoi Diagram As A Geometric Structure
-H. Sorted Sets--作业
-I. VD_sorted
--04-I-06. Sorting Not Made Easier
-I. VD_sorted--作业
-J. Naive Construction
-J. Naive Construction--作业
-K. Incremental Construction
-K. Incremental Construction--作业
-L. Divide-And-Conquer
--04-L-09. Intersecting with Cells
-L. Divide-And-Conquer--作业
-M. Plane-Sweep
--04-M-09. Circle Event: What, When & Where
-M. Plane-Sweep--作业
-A. Point Set Triangulation
-A. Point Set Triangulation--作业
-B. Delaunay Triangulation
-B. Delaunay Triangulation--作业
-C. Properties
-C. Properties--作业
-D. Proximity Graph
--05-D-02. Relative Neighborhood Graph
-D. Proximity Graph--作业
-E. Euclidean Minimum Spanning Tree
-E. Euclidean Minimum Spanning Tree--作业
-F. Euclidean Traveling Salesman Problem
-G. Minimum Weighted Triangulation
-G. Minimum Weighted Triangulation--作业
-H. Construction
--05-H-03. Maximizing The Minimum Angle
--05-H-04. Evolution By Edge Flipping
-H. Construction--作业
-I. RIC With Example
-I. RIC With Example--作业
-J. Randomized Incremental Construction
--05-J-01. Recursive Implementation
--05-J-02. Iterative Implementation
-J. Randomized Incremental Construction--作业
-K. RIC Analysis
--05-K-04. Types Of Edge Change
--05-K-05. Number Of Edge Changes
--05-K-07. Number Of Rebucketings
--05-K-08. Probability For Rebucketing
--05-K-10. Further Consideration
-0. Online/Offline Algorithms
--06-0. Online/Offline Algorithms
-0. Online/Offline Algorithms--作业
-A. Introduction
--06-A-03. Assumptions For Clarity
--06-A-05. Performance Measurements
-A. Introduction--作业
-B. Slab Method
--06-B-02. Ordering Trapezoids
-B. Slab Method--作业
-C. Persistence
--06-C-01. Ephemeral Structure
--06-C-02. Persistent Structure
-C. Persistence--作业
-D. Path Copying
--06-D-03. Storage Optimization
-D. Path Copying--作业
-E. Node Copying
-E. Node Copying--作业
-F. Limited Node Copying
-G. Kirkpatrick Structure
--06-G-01. Optimal And Simpler
--06-G-06. The More The Better
--06-G-07. The Fewer The Better
--06-G-09. Existence Of Independent Subset
--06-G-10. Construction Of Independent Subset
-G. Kirkpatrick Structure--作业
-H. Trapezoidal Map
--06-H-03. Properties & Complexity
--06-H-04. Search Structure: Example
--06-H-05. Search Structure: Nodes
--06-H-06. Search Structure: Performance
-H. Trapezoidal Map--作业
-I. Constructing Trapezoidal Map
--06-I-04. Case 1: Two Endpoints
--06-I-05. Case 2: One Endpoint
--06-I-06. Case 3: No Endpoints
-J. Performance Of Trapezoidal Map
--06-J-03. Number Of Ray Trimmed
--06-J-04. Number Of Trapezoidals Created (1)
--06-J-05. Number Of Trapezoidals Created (2)
--06-J-06. Time For Point Location
--06-J-07. Size Of Search Structure
--06-J-08. Fixed Query Point + Randomly Created Maps
--06-J-10. Probability Of Enclosing Trapezoid Changed
-A. Range Query
--07-A-01. 1-Dimensional Range Query
-A. Range Query--作业
-B. BBST
--07-B-02. Lowest Common Ancestor
-B. BBST--作业
-C. kd-Tree: Structure
-C. kd-Tree: Structure--作业
-D. kd-Tree: Algorithm
-D. kd-Tree: Algorithm--作业
-E. kd-Tree: Performance
--07-E-01. Preprocessing Time + Storage
-E. kd-Tree: Performance--作业
-F. Range Tree: Structure
--07-F-03. x-Query * y-Queries
-F. Range Tree: Structure--作业
-G. Range Tree: Query
-G. Range Tree: Query--作业
-H. Range Tree: Performance
-H. Range Tree: Performance--作业
-I. Range Tree: Optimization
--07-I-04. Fractional Cascading
-A. Orthogonal Windowing Query
-A. Orthogonal Windowing Query--作业
-B. Stabbing Query
-C. Interval Tree: Construction
-C. Interval Tree: Construction--作业
-D. Interval Tree: Query
-D. Interval Tree: Query--作业
-E. Stabbing With A Segment
--08-E-03. Query Algorithm (1)
--08-E-04. Query Algorithm (2)
-F. Grounded Range Query
--08-F-03. 1D-GRQ Using Range Tree
--08-F-04. 1D-GRQ By Linear Scan
-G. 1D-GRQ Using Heap
-G. 1D-GRQ Using Heap--作业
-H. Priority Search Tree
--08-H-03. Sibling Partitioning
-H. Priority Search Tree--作业
-I. 2D-GRQ Using PST
-I. 2D-GRQ Using PST--作业
-J. Segment Tree
--08-J-01. General Windowing Query
--08-J-02. Elementary Interval
--08-J-06. Solving Stabbing Query
--08-J-11. Constructing A Segment Tree
--08-J-12. Inserting A Segment (1)
--08-J-13. Inserting A Segment (2)
--08-J-14. Inserting A Segment (3)
-K. Vertical Segment Stabbing Query