1 Numerical geometry of non-rigid shapes Mathematical background Mathematical background Tutorial 1 © Maks Ovsjanikov, Alex & Michael Bronstein tosca.cs.technion.ac.il/book.

Slides:



Advertisements
Similar presentations
The proof is quite similar to that of a previous result: a compact subspace of a Hausdorff is closed. Theorem: If topological X  space is compact and.
Advertisements

Binary Operations Let S be any given set. A binary operation  on S is a correspondence that associates with each ordered pair (a, b) of elements of S.
Differential geometry I
The Engineering Design of Systems: Models and Methods
Lecture 6 Hyperreal Numbers (Nonstandard Analysis)
Discrete Geometry Tutorial 2 1
Math 3121 Abstract Algebra I
Algebraic Structures: Group Theory II
1.  Detailed Study of groups is a fundamental concept in the study of abstract algebra. To define the notion of groups,we require the concept of binary.
Isometry-Invariant Similarity
Prolog Algebra / Analysis vs Geometry Relativity → Riemannian Geometry Symmetry → Lie Derivatives → Lie Group → Lie Algebra Integration → Differential.
Discrete geometry Lecture 2 1 © Alexander & Michael Bronstein
1 Numerical geometry of non-rigid shapes Geometry Numerical geometry of non-rigid shapes Shortest path problems Alexander Bronstein, Michael Bronstein,
1 Numerical geometry of non-rigid shapes Consistent approximation of geodesics in graphs Consistent approximation of geodesics in graphs Tutorial 3 © Alexander.
1 Numerical geometry of non-rigid shapes A taste of geometry A Taste of Geometry Alexander Bronstein, Michael Bronstein © 2008 All rights reserved. Web:
Isometry invariant similarity
Numerical geometry of objects
Correspondence & Symmetry
1 Numerical geometry of non-rigid shapes Spectral Methods Tutorial. Spectral Methods Tutorial 6 © Maks Ovsjanikov tosca.cs.technion.ac.il/book Numerical.
1 Numerical Geometry of Non-Rigid Shapes Invariant shape similarity Invariant shape similarity © Alexander & Michael Bronstein, © Michael Bronstein,
1 Numerical geometry of non-rigid shapes Non-Euclidean Embedding Non-Euclidean Embedding Lecture 6 © Alexander & Michael Bronstein tosca.cs.technion.ac.il/book.
MA5209 Algebraic Topology Wayne Lawton Department of Mathematics National University of Singapore S ,
MA4266 Topology Wayne Lawton Department of Mathematics S ,
Relative Location of a Point with Respect to a Straight Line (0,0) 5 5 (2, 2) (4, 5) (0, 5) (6, 3) -3x + 2y +2 = 0 s = A x t + B y t + C s < 0 s > 0.
Foundations of Discrete Mathematics Chapter 3 By Dr. Dalia M. Gil, Ph.D.
Network Systems Lab. Korea Advanced Institute of Science and Technology No.1 Appendix A. Mathematical Background EE692 Parallel and Distribution Computation.
General (point-set) topology Jundong Liu Ohio Univ.
Relations, Functions, and Matrices Mathematical Structures for Computer Science Chapter 4 Copyright © 2006 W.H. Freeman & Co.MSCS SlidesFunctions.
Properties of Real Numbers. Sets In mathematics, a set is a collection of things Sets can be studies as a topic all on its own (known as set theory),
8.3 Representing Relations Directed Graphs –Vertex –Arc (directed edge) –Initial vertex –Terminal vertex.
Sets and Functions Contents  Set language  Basic knowledge on sets  Intervals  Functions (Mappings)
Sets Define sets in 2 ways  Enumeration  Set comprehension (predicate on membership), e.g., {n | n  N   k  k  N  n = 10  k  0  n  50} the set.
MA5296 Lecture 1 Completion and Uniform Continuity Wayne M. Lawton Department of Mathematics National University of Singapore 2 Science Drive 2 Singapore.
The Real Number System Section P.1. Set, Unions, and Intersections Part 1.
MA4266 Topology Wayne Lawton Department of Mathematics S ,
Discrete Mathematics R. Johnsonbaugh
CHAPTER 3 FUZZY RELATION and COMPOSITION. 3.1 Crisp relation Product set Definition (Product set) Let A and B be two non-empty sets, the product.
Dr. Wang Xingbo Fall , 2005 Mathematical & Mechanical Method in Mechanical Engineering.
Rules of the game  You will work with your Unit 3 group  We will have 4 rounds of 6 questions each. Most are multiple choice; some are fill in the blank.
Introduction to Real Analysis Dr. Weihu Hong Clayton State University 8/19/2008.
Embeddings, flow, and cuts: an introduction University of Washington James R. Lee.
Math 3121 Abstract Algebra I Lecture 7: Finish Section 7 Sections 8.
Sets Definition: A set is an unordered collection of objects, called elements or members of the set. A set is said to contain its elements. We write a.
Unit II Discrete Structures Relations and Functions SE (Comp.Engg.)
Discrete Mathematics Set.
CS Lecture 14 Powerful Tools     !. Build your toolbox of abstract structures and concepts. Know the capacities and limits of each tool.
Chapter 8: Relations. 8.1 Relations and Their Properties Binary relations: Let A and B be any two sets. A binary relation R from A to B, written R : A.
1 Numerical geometry of non-rigid shapes Projects Quasi-isometries Project 1 © Alexander & Michael Bronstein tosca.cs.technion.ac.il/book Numerical geometry.
SECTION 8 Groups of Permutations Definition A permutation of a set A is a function  ϕ : A  A that is both one to one and onto. If  and  are both permutations.
Set Theory Concepts Set – A collection of “elements” (objects, members) denoted by upper case letters A, B, etc. elements are lower case brackets are used.
FUNCTIONS COSC-1321 Discrete Structures 1. Function. Definition Let X and Y be sets. A function f from X to Y is a relation from X to Y with the property.
Summary of the Last Lecture This is our second lecture. In our first lecture, we discussed The vector spaces briefly and proved some basic inequalities.
Topology Preserving Edge Contraction Paper By Dr. Tamal Dey et al Presented by Ramakrishnan Kazhiyur-Mannar.
Week 8 - Wednesday.  What did we talk about last time?  Relations  Properties of relations  Reflexive  Symmetric  Transitive.
INTERPOLATORY SOLUTIONS OF LINEAR ODE’S AND EXTENSIONS Wayne M. Lawton Dept. of Mathematics, National University of Singapore 2 Science Drive 2, Singapore.
Math 3121 Abstract Algebra I
Relations, Functions, and Matrices
Unit-III Algebraic Structures
Introduction to Relations
Chapter 3 The Real Numbers.
Continuity of Darboux functions Nikita Shekutkovski, Beti Andonovic
Great Theoretical Ideas In Computer Science
Principles of GIS Fundamental spatial concepts – Part II Shaowen Wang
Compactness in Metric space
Some Review Problems for Math 141 Final
Chapter 3 The Real Numbers.
CS201: Data Structures and Discrete Mathematics I
Section 10.1 Groups.
Set – collection of objects
Section 9.1 Groups.
Presentation transcript:

1 Numerical geometry of non-rigid shapes Mathematical background Mathematical background Tutorial 1 © Maks Ovsjanikov, Alex & Michael Bronstein tosca.cs.technion.ac.il/book Numerical geometry of non-rigid shapes Stanford University, Winter 2009

2 Numerical geometry of non-rigid shapes Mathematical background Metric balls Euclidean ballL 1 ballL  ball Open ball: Closed ball:

3 Numerical geometry of non-rigid shapes Mathematical background Topology A set is open if for any there exists such that Empty set is open Union of any number of open sets is open Finite intersection of open sets is open Collection of all open sets in is called topology The metric induces a topology through the definition of open sets Topology can be defined independently of a metric through an axiomatic definition of an open set A set, whose compliment is open is called closed

4 Numerical geometry of non-rigid shapes Mathematical background Topological spaces A set together with a set of subsets of form a topological space if Empty set and are both in Union of any collection of sets in is also in Intersection of a finite number of sets in is also in The sets in are called open sets The metric induces a topology through the definition of open sets is called a topology on

5 Numerical geometry of non-rigid shapes Mathematical background Connectedness ConnectedDisconnected The space is connected if it cannot be divided into two disjoint nonempty closed sets, and disconnected otherwise Stronger property: path connectedness

6 Numerical geometry of non-rigid shapes Mathematical background Compactness The space is compact if any open covering has a finite subcovering For a subset of Euclidean space, compact = closed and bounded (finite diameter) Infinite Finite

7 Numerical geometry of non-rigid shapes Mathematical background Convergence Topological definitionMetric definition for any open set containing exists such that for all for all exists such that for all A sequence converges to (denoted ) if

8 Numerical geometry of non-rigid shapes Mathematical background Continuity Topological definitionMetric definition for any open set, preimage is also open. for all exists s.t. for all satisfying it follows that A function is called continuous if

9 Numerical geometry of non-rigid shapes Mathematical background Properties of continuous functions Map limits to limits, i.e., if, then Map open sets to open sets Map compact sets to compact sets Map connected sets to connected sets Continuity is a local property: a function can be continuous at one point and discontinuous at another

10 Numerical geometry of non-rigid shapes Mathematical background Homeomorphisms A bijective (one-to-one and onto) continuous function with a continuous inverse is called a homeomorphism Homeomorphisms copy topology – homeomorphic spaces are topologically equivalent Torus and cup are homeomorphic

11 Numerical geometry of non-rigid shapes Mathematical background Topology of Latin alphabet a b d e o p q c f h k n r s ij l m t u v w x y z homeomorphic to

12 Numerical geometry of non-rigid shapes Mathematical background Lipschitz continuity A function is called Lipschitz continuous if there exists a constant such that for all. The smallest possible is called Lipschitz constant Lipschitz continuous function does not change the distance between any pair of points by more than times Lipschitz continuity is a global property For a differentiable function

13 Numerical geometry of non-rigid shapes Mathematical background Bi-Lipschitz continuity A function is called bi-Lipschitz continuous if there exists a constant such that for all

14 Numerical geometry of non-rigid shapes Mathematical background Examples of Lipschitz continuity Continuous, not Lipschitz on [0,1] Bi-Lipschitz on [0,1]Lipschitz on [0,1]

15 Numerical geometry of non-rigid shapes Mathematical background Isometries A bi-Lipschitz function with is called distance-preserving or an isometric embedding A bijective distance-preserving function is called isometry Isometries copy metric geometries – two isometric spaces are equivalent from the point of view of metric geometry

16 Numerical geometry of non-rigid shapes Mathematical background Dilation Maximum relative change of distances by a function is called dilation Dilation is the Lipschitz constant of the function Almost isometry has

17 Numerical geometry of non-rigid shapes Mathematical background Distortion Maximum absolute change of distances by a function is called distortion Almost isometry has

18 Numerical geometry of non-rigid shapes Mathematical background Groups A set with a binary operation is called a group if the following properties hold: Closure: for all Associativity: for all Identity element: such that for all Inverse element: for any, such that

19 Numerical geometry of non-rigid shapes Mathematical background Examples of groups Integers with addition operation Closure: sum of two integers is an integer Associativity: Identity element: Inverse element: Non-zero real numbers with multiplication operation Closure: product of two non-zero real numbers is a non-zero real number Associativity: Identity element: Inverse element:

20 Numerical geometry of non-rigid shapes Mathematical background Self-sometries A function is called a self-isometry if for all Set of all self-isometries of is denoted by with the function composition operation is a group Closure is a self-isometry for all Associativity from definition of function composition Identity element Inverse element (exists because isometries are bijective)

21 Numerical geometry of non-rigid shapes Mathematical background Isometry groups A B C A B C A B C C B A C B A C B Cyclic group (reflection) Permutation group (reflection+rotation) Trivial group (asymmetric) A A B C

22 Numerical geometry of non-rigid shapes Mathematical background Symmetry in Nature Snowflake (dihedral) Butterfly (reflection) Diamond