Lecture 9 : Point Set Processing

Slides:



Advertisements
Similar presentations
Department of Computer Science and Engineering Defining and Computing Curve-skeletons with Medial Geodesic Function Tamal K. Dey and Jian Sun The Ohio.
Advertisements

1 st Meeting, Industrial Geometry, 2005 Approximating Solids by Balls (in collaboration with subproject: "Applications of Higher Geometrics") Bernhard.
CSE554Cell ComplexesSlide 1 CSE 554 Lecture 3: Shape Analysis (Part II) Fall 2014.
Problems in curves and surfaces M. Ramanathan Problems in curves and surfaces.
GATE Reconstruction from Point Cloud (GATE-540) Dr.Çağatay ÜNDEĞER Instructor Middle East Technical University, GameTechnologies & General Manager.
Surface Reconstruction From Unorganized Point Sets
Surface normals and principal component analysis (PCA)
Proximity graphs: reconstruction of curves and surfaces
KIM TAEHO PARK YOUNGMIN.  Curve Reconstruction problem.
Computational Geometry II Brian Chen Rice University Computer Science.
Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.
Computational Topology for Computer Graphics Klein bottle.
The Voronoi Diagram David Johnson. Voronoi Diagram Creates a roadmap that maximizes clearance –Can be difficult to compute –We saw an approximation in.
COMPUTER GRAPHICS CS 482 – FALL 2014 OCTOBER 13, 2014 IMPLICIT REPRESENTATIONS IMPLICIT FUNCTIONS IMPLICIT SURFACES MARCHING CUBES.
Flow Complex Joachim Giesen Friedrich-Schiller-Universität Jena.
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.
Course Syllabus 1.Color 2.Camera models, camera calibration 3.Advanced image pre-processing Line detection Corner detection Maximally stable extremal regions.
Discrete Geometry Tutorial 2 1
1st Meeting Industrial Geometry Computational Geometry ---- Some Basic Structures 1st IG-Meeting.
Computing Stable and Compact Representation of Medial Axis Wenping Wang The University of Hong Kong.
The generic model of a modular machine vision system
Computing Medial Axis and Curve Skeleton from Voronoi Diagrams Tamal K. Dey Department of Computer Science and Engineering The Ohio State University Joint.
Discrete geometry Lecture 2 1 © Alexander & Michael Bronstein
By Dor Lahav. Overview Straight Skeletons Convex Polygons Constrained Voronoi diagrams and Delauney triangulations.
Surface Reconstruction Some figures by Turk, Curless, Amenta, et al.
CS CS 175 – Week 3 Triangulating Point Clouds VD, DT, MA, MAT, Crust.
Voronoi diagrams of “nice” point sets Nina Amenta UC Davis “The World a Jigsaw”
1 Street Generation for City Modeling Xavier Décoret, François Sillion iMAGIS GRAVIR/IMAG - INRIA.
T. J. Peters, University of Connecticut K. Abe, J. Bisceglio, A. C. Russell Computational Topology on Approximated Manifolds.
Tamal K. Dey The Ohio State University Computing Shapes and Their Features from Point Samples.
UNC Chapel Hill M. C. Lin Point Location Chapter 6 of the Textbook –Review –Algorithm Analysis –Dealing with Degeneracies.
Junjun Pan 1, Xiaosong Yang 1, Xin Xie 1, Philip Willis 2, Jian J Zhang 1
Gerald Dalley Signal Analysis and Machine Perception Laboratory The Ohio State University 07 Feb 2002 Linux Clustering Software + Surface Reconstruction.
© Manfred Huber Autonomous Robots Robot Path Planning.
SURFACE RECONSTRUCTION FROM POINT CLOUD Bo Gao Master’s Thesis December, 2007 Thesis Committee: Professor Harriet Fell Professor Robert Futrelle College.
Shape Analysis and Retrieval Structural Shape Descriptors Notes courtesy of Funk et al., SIGGRAPH 2004.
Digital Image Processing CCS331 Relationships of Pixel 1.
TEL-AVIV UNIVERSITY RAYMOND AND BEVERLY SACKLER FACULTY OF EXACT SCIENCES SCHOOL OF MATHEMATICAL SCIENCES An Algorithm for the Computation of the Metric.
Extended Grassfire Transform on Medial Axes of 2D Shapes
Week 24 - Vocabulary 3-Dimensional Figures.
Lecture 7 : Point Set Processing Acknowledgement : Prof. Amenta’s slides.
Voronoi Diagram (Supplemental)
CSE554SkeletonsSlide 1 CSE 554 Lecture 2: Shape Analysis (Part I) Fall 2015.
CSE554ContouringSlide 1 CSE 554 Lecture 4: Contouring Fall 2015.
A New Voronoi-based Reconstruction Algorithm
9 of 18 Introduction to medial axis transforms and their computation Outline DefinitionsMAS PropertiesMAS CAD modelsTJC The challenges for computingTJC.
References Books: Chapter 11, Image Processing, Analysis, and Machine Vision, Sonka et al Chapter 9, Digital Image Processing, Gonzalez & Woods.
UNC Chapel Hill M. C. Lin Delaunay Triangulations Reading: Chapter 9 of the Textbook Driving Applications –Height Interpolation –Constrained Triangulation.
Shape Reconstruction from Samples with Cocone Tamal K. Dey Dept. of CIS Ohio State University.
1/57 CS148: Introduction to Computer Graphics and Imaging Geometric Modeling CS148 Lecture 6.
Dynamic Programming (DP), Shortest Paths (SP)
Image Features (I) Dr. Chang Shu COMP 4900C Winter 2008.
CDS 301 Fall, 2008 Domain-Modeling Techniques Chap. 8 November 04, 2008 Jie Zhang Copyright ©
Bigyan Ankur Mukherjee University of Utah. Given a set of Points P sampled from a surface Σ,  Find a Surface Σ * that “approximates” Σ  Σ * is generally.
Coverage and Deployment 1. Coverage Problems Coverage: is a measure of the Quality of Service (QoS) of a sensor network How well can the network observe.
CMPS 3130/6130 Computational Geometry Spring 2017
Decimating Samples for Mesh Simplification
CSE 554 Lecture 2: Shape Analysis (Part I)
고급 컴퓨터 그래픽스 (Advanced Computer Graphics)
Decimation Of Triangle Meshes
Shape Dimension and Approximation from Samples
Haim Kaplan and Uri Zwick
Fitting Curve Models to Edges
Localizing the Delaunay Triangulation and its Parallel Implementation
Domain-Modeling Techniques
Meshing of 3-D Data Clouds for Object Description
CSE 554 Lecture 3: Shape Analysis (Part II)
Point-Cloud 3D Modeling.
Presentation transcript:

Lecture 9 : Point Set Processing Acknowledgement : Prof. Amenta’s slides

Point Set (Point Cloud) Often obtained from laser snanners

Building Information Modeling (BIM)

Human Body Shapes

Triangulations (Delaunay) & Dual Diagrams (Voronoi) Union of Balls Triangulations (Delaunay) & Dual Diagrams (Voronoi) Union of balls Triangulation & Dual

Data Structures for Point Set Data Voronoi Diagram Delaunay Triangulation Medial Axis

Voronoi Diagram/Delaunay Triangulation Refer to Prof. Vigneron’s slides

Medial Axis A Transformation For Extracting New Descriptors of Shape Locus of points equidistant from contour Skeleton

Applications of medial axis Shape matching Animation Computer Vision Dimension reduction (Simplification) Solid modeling

Definitions of medial axis Locus of points equidistant from contour Grass-fire, prairie-fire, wave-front collision Locus of centers of maximal circles Local maxima in distance transform Result of topology preserving thinning

medial axis Blum’s equivalent definitions :

Medial Axis A set of points with more than one closest surface point

3D Medial Axis A set of points with more than one closest surface point

Medial Axis Maximal ball avoiding surface is a medial ball Every solid is a union of balls

Relation to Voronoi Voronoi balls approximate medial balls For dense surface samples in 2D, all voronoi vertices lie near axis

Convergence In 2D, set of Voronoi vertices converges to the medial axis as sampling density increases.

Discrete Union of Balls Voronoi balls approximate the object and its complement.

2D Curve Reconstruction Blue Delaunay edges reconstruct the curve, pink triangulate interior/exterior. Many algorithms, with proofs, for coloring edges.

2D Curve Reconstruction <Voronoi Diagram of point set S> Delaunay Triangulation of point set S and voronoi vertices V Black lines represent curve reconstruction

2D Medial Axis Reconstruction Pink approximate medial axis.

3D Case Different from 2D In 3D, some Voronoi vertices are not near medial axis Red : voronoi cell of the blue point Notice the red voronoi vertex that is far from the medial axis

Union of Balls centered on voronoi vertices Even when samples are arbitrarily dense

Poles Farthest voronoi vertices Subset of voronoi vertices, p+ , p- (opposite sides) Subset of voronoi vertices, the poles, approximate near medial axis

Union of balls centered on interior poles

3D surface reconstruction Similar to 2D surface reconstruction, but use poles instead of entire voronoi vertices

Results [Amenta 1998,2001] Laser range data, power crust, simplified approximate medial axis

Shape Feature Segmentation [Dey 2003] Based on Voronoi Diagram and Delaunay Triangulation

Flow Field of Shape

Shape Feature Segmentation