Alpha Shapes. Used for Shape Modelling Creates shapes out of point sets Gives a hierarchy of shapes. Has been used for detecting pockets in proteins.

Slides:



Advertisements
Similar presentations
Incremental Linear Programming Linear programming involves finding a solution to the constraints, one that maximizes the given linear function of variables.
Advertisements

Tyler White MATH 493 Dr. Wanner
Surface Reconstruction From Unorganized Point Sets
Kick-off Meeting, July 28, 2008 ONR MURI: NexGeNetSci Distributed Coordination, Consensus, and Coverage in Networked Dynamic Systems Ali Jadbabaie Electrical.
 Distance Problems: › Post Office Problem › Nearest Neighbors and Closest Pair › Largest Empty and Smallest Enclosing Circle  Sub graphs of Delaunay.
Voronoi Diagrams in n· 2 O(√lglg n ) Time Timothy M. ChanMihai Pătraşcu STOC’07.
Proximity graphs: reconstruction of curves and surfaces
KIM TAEHO PARK YOUNGMIN.  Curve Reconstruction problem.
Computational Geometry II Brian Chen Rice University Computer Science.
C o m p u t i n g C O N V E X H U L L S by Kok Lim Low 10 Nov 1998 COMP Presentation.
S. J. Shyu Chap. 1 Introduction 1 The Design and Analysis of Algorithms Chapter 1 Introduction S. J. Shyu.
Sampling conditions and topological guarantees for shape reconstruction algorithms Andre Lieutier, Dassault Sytemes Thanks to Dominique Attali for some.
Flow Complex Joachim Giesen Friedrich-Schiller-Universität Jena.
The Divide-and-Conquer Strategy
Convex Hulls in Two Dimensions Definitions Basic algorithms Gift Wrapping (algorithm of Jarvis ) Graham scan Divide and conquer Convex Hull for line intersections.
Divide and Conquer. Recall Complexity Analysis – Comparison of algorithm – Big O Simplification From source code – Recursive.
Medial axis computation of exact curves and surfaces M. Ramanathan Department of Engineering Design, IIT Madras Medial object.
By Groysman Maxim. Let S be a set of sites in the plane. Each point in the plane is influenced by each point of S. We would like to decompose the plane.
Convex Hull Problem Presented By Erion Lin. Outline Convex Hull Problem Voronoi Diagram Fermat Point.
What does that mean? To get the taste we will just look only at some sample problems... [Adapted from S.Suri]
DEpthLAUNAY1 DEpthLAUNAY Manuel Abellanas Alfredo de las Vegas Facultad de Informática - UPM.
3/5/15CMPS 3130/6130 Computational Geometry1 CMPS 3130/6130 Computational Geometry Spring 2015 Delaunay Triangulations II Carola Wenk Based on: Computational.
Tuesday, May 14 Genetic Algorithms Handouts: Lecture Notes Question: when should there be an additional review session?
1st Meeting Industrial Geometry Computational Geometry ---- Some Basic Structures 1st IG-Meeting.
Computational Geometry Piyush Kumar (Lecture 3: Convexity and Convex hulls) Welcome to CIS5930.
Computational Geometry -- Voronoi Diagram
Discrete geometry Lecture 2 1 © Alexander & Michael Bronstein
2. Voronoi Diagram 2.1 Definiton Given a finite set S of points in the plane , each point X of  defines a subset S X of S consisting of the points of.
Computational Geometry and Spatial Data Mining
1cs542g-term Notes. 2 Meshing goals  Robust: doesn’t fail on reasonable geometry  Efficient: as few triangles as possible Easy to refine later.
Delaunay Triangulation Computational Geometry, WS 2006/07 Lecture 11 Prof. Dr. Thomas Ottmann Algorithmen & Datenstrukturen, Institut für Informatik Fakultät.
An Algorithm for Polytope Decomposition and Exact Computation of Multiple Integrals.
Lecture 10 : Delaunay Triangulation Computational Geometry Prof. Dr. Th. Ottmann 1 Overview Motivation. Triangulation of Planar Point Sets. Definition.
Voronoi Diagrams and Delaunay Triangulations Generalized spaces and distances.
Image Morphing : Rendering and Image Processing Alexei Efros.
CS CS 175 – Week 3 Triangulating Point Clouds VD, DT, MA, MAT, Crust.
UNC Chapel Hill M. C. Lin Overview of Last Lecture About Final Course Project –presentation, demo, write-up More geometric data structures –Binary Space.
Computing the Delaunay Triangulation By Nacha Chavez Math 870 Computational Geometry; Ch.9; de Berg, van Kreveld, Overmars, Schwarzkopf By Nacha Chavez.
Voronoi diagrams of “nice” point sets Nina Amenta UC Davis “The World a Jigsaw”
Image Morphing, Triangulation CSE399b, Spring 07 Computer Vision.
Well Separated Pair Decomposition 16 GigaYears and 3.3 Million Light Years Playing.
Algorithmic Art Mathematical Expansions –Geometric, Arithmetic Series, Fibonacci Numbers Computability –Turing Fractals and Brownian Motion, CA –Recursive.
Lab 3 How’d it go?.
ADA: 14. Intro to CG1 Objective o give a non-technical overview of Computational geometry, concentrating on its main application areas Algorithm.
Dobrina Boltcheva, Mariette Yvinec, Jean-Daniel Boissonnat INRIA – Sophia Antipolis, France 1. Initialization Use the.
Algorithms for Triangulations of a 3D Point Set Géza Kós Computer and Automation Research Institute Hungarian Academy of Sciences Budapest, Kende u
PRE-TRIANGULATIONS Generalized Delaunay Triangulations and Flips Franz Aurenhammer Institute for Theoretical Computer Science Graz University of Technology,
General (point-set) topology Jundong Liu Ohio Univ.
Curves.
C o m p u t i n g C O N V E X H U L L S. Presentation Outline 2D Convex Hulls –Definitions and Properties –Approaches: Brute Force Gift Wrapping QuickHull.
Curves. First of all… You may ask yourselves “What did those papers have to do with computer graphics?” –Valid question Answer: I thought they were cool,
Managing Complexity: Systems Design March 2, 2001.
Voronoi Diagram (Supplemental)
UMass Lowell Computer Science Advanced Algorithms Computational Geometry Prof. Karen Daniels Spring, 2010 Shewchuck 2D Triangular Meshing.
A New Voronoi-based Reconstruction Algorithm
Kansas State University Department of Computing and Information Sciences Friday, July 13, 2001 Mantena V. Raju Department of Computing and Information.
Alpha shapes Reporter: Lincong Fang 10th Jan, 2007.
UNC Chapel Hill M. C. Lin Delaunay Triangulations Reading: Chapter 9 of the Textbook Driving Applications –Height Interpolation –Constrained Triangulation.
Algorithm for computing positive α-hull for a set of planar closed curves Vishwanath A. Venkataraman, Ramanathan Muthuganapathy Advanced Geometric Computing.
Multimedia Programming 10: Image Morphing
1 Giuseppe Romeo Voronoi based Source Detection. 2 Voronoi cell The Voronoi tessellation is constructed as follows: for each data point  i (also called.
UNC Chapel Hill M. C. Lin Randomized Linear Programming For any set of H of half-planes, there is a good order to treat them. Thus, we can improve the.
Convex hulls in 3D Maciej Kot. Finding convex hull Given a set of points, find a convex hull that contains all of them and is minimal.
Topology Preserving Edge Contraction Paper By Dr. Tamal Dey et al Presented by Ramakrishnan Kazhiyur-Mannar.
Polygon Triangulation
Computational Geometry Piyush Kumar (Lecture 1: Introduction) Welcome to CIS5930.
Sept 25, 2013: Applicable Triangulations.
Localizing the Delaunay Triangulation and its Parallel Implementation
Meshing of 3-D Data Clouds for Object Description
Presentation transcript:

Alpha Shapes

Used for Shape Modelling Creates shapes out of point sets Gives a hierarchy of shapes. Has been used for detecting pockets in proteins. For reverse engineering

Convexity A set S in Euclidean space is said to be convex if every straight line segment having its two end points in S lies entirely in S.

Convex Hulls The smallest convex set that contains the entire point set.

Triangulations

Voronoi Diagrams This set is a convex polyhedra since it is an intersection of half spaces. These polyhedra define a decomposition of R d. The voronoi complex V(P) of P is the collection of all voronoi objects. Delaunay complex is the dual of the voronoi complex.

Delaunay Triangulations

Voronoi Diagrams Post offices for the population in an area Subdivision of the plane into cells. Always Convex cells Curse of Dimension cells.

Lifting Map: Magic Map Map Convex Hull back -> Delaunay Map mapped back to lower dimension is the Voronoi diagram!!!

Other Definitions General Position of points in k-simplex, Simplicial Complex Flipping in 2D and 3D

k-simplex

Simplicial Complex Delaunay triangulations are simplicial complexes.

Flipping

Alpha Shapes The space generated by point pairs that can be touched by an empty disc of radius alpha.

Alpha Shapes Alpha Controls the desired level of detail.

Sample Outputs

Sample Output

Implementing Alpha Shapes Decide on Speed / Accuracy Trade off Exact Arithmetic : Keep Away SoS : Keep Away Simple Solution: Juggle Juggle and Juggle (To get to General Position)

Delaunay: How??? Lot of Algorithms available!!! Incremental Flipping? Divide and Conquer? Sweep? Randomized or Deterministic? Do I calculate Voronoi or Delaunay?? ( I got confused )

Predicates?? What are Predicates??? Why do I bother?? Which one do I pick? When do I use Exact Predicates? What else is available?

What Data Structure! What data structure is used to compute Delaunay? Which algorithm is easy to code? How do I implement the Alpha Shape in my code? Any example codes available to cheat? Creativity is the art of hiding Sources!

Theory Its not so bad…;) Lets get started, Simple things first Union of Balls If the facts don't fit the theory, change the facts. --Albert Einstein

That was simple! Weighted Voronoi: Seems not so tough yet

An example in the dual Courtesy Dey, Giesen and John 04. Edelsbrunner: Union of balls and alpha shapes are homotopy equivalent for all alpha.

What Next? The Dual Complex: Assuming General position, at most 3 Voronoi Cells meet at a point. For fixed weights, alpha, Its a alpha complex!

Example of Dynamic Balls!

Alpha Complex The subset of delaunay tesselation in d- dimensions that has simplices having Circumradius greater than Alpha. Its a Simplicial Complex all the way ( for a topologist )

Filter and Filtration A Filter!!!! (an order on the simplices) A Filtration??? (sequence of complexes)

Filteration??? Filteration = All Alpha Shapes!!! Alpha Shapes in 3D!! Covers, Nerves, Homotopy, Homology?? (Keep Away for now)

Alpha Shapes?? What the hell were Alpha Shapes??? As the Balls grow(Alpha becomes bigger) on the input point set, the dual marches thru the Filteration, defining a set of shapes. Thats it!! Wasnt it a cute idea for 1983!

So Far So Good! How do I calculate Alpha?? How do I decide the weights for a weighted Alpha shape? Is there an Alpha Shape that is Piecewise Linear 2-Manifold? Isnt the sampling criterion too strict?? Delaunay is Costly, Can we use Point Set Distribution information??

Future Work U want to work on Alpha Shapes?? (And get papers accepted too, Thats tough) Alpha shapes is old now, u could try something new! What else can we try? Try Energy Minimization, Optimization! Noise. With provability thrown in, That is still open.

Thats all Folks