Projective Geometry: from Foundations to Applications
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Projective Geometry: a Short Introduction
Projective Geometry: A Short Introduction Lecture Notes Edmond Boyer Master MOSIG Introduction to Projective Geometry Contents 1 Introduction 2 1.1 Objective . .2 1.2 Historical Background . .3 1.3 Bibliography . .4 2 Projective Spaces 5 2.1 Definitions . .5 2.2 Properties . .8 2.3 The hyperplane at infinity . 12 3 The projective line 13 3.1 Introduction . 13 3.2 Projective transformation of P1 ................... 14 3.3 The cross-ratio . 14 4 The projective plane 17 4.1 Points and lines . 17 4.2 Line at infinity . 18 4.3 Homographies . 19 4.4 Conics . 20 4.5 Affine transformations . 22 4.6 Euclidean transformations . 22 4.7 Particular transformations . 24 4.8 Transformation hierarchy . 25 Grenoble Universities 1 Master MOSIG Introduction to Projective Geometry Chapter 1 Introduction 1.1 Objective The objective of this course is to give basic notions and intuitions on projective geometry. The interest of projective geometry arises in several visual comput- ing domains, in particular computer vision modelling and computer graphics. It provides a mathematical formalism to describe the geometry of cameras and the associated transformations, hence enabling the design of computational ap- proaches that manipulates 2D projections of 3D objects. In that respect, a fundamental aspect is the fact that objects at infinity can be represented and manipulated with projective geometry and this in contrast to the Euclidean geometry. This allows perspective deformations to be represented as projective transformations. Figure 1.1: Example of perspective deformation or 2D projective transforma- tion. Another argument is that Euclidean geometry is sometimes difficult to use in algorithms, with particular cases arising from non-generic situations (e.g. -
Robot Vision: Projective Geometry
Robot Vision: Projective Geometry Ass.Prof. Friedrich Fraundorfer SS 2018 1 Learning goals . Understand homogeneous coordinates . Understand points, line, plane parameters and interpret them geometrically . Understand point, line, plane interactions geometrically . Analytical calculations with lines, points and planes . Understand the difference between Euclidean and projective space . Understand the properties of parallel lines and planes in projective space . Understand the concept of the line and plane at infinity 2 Outline . 1D projective geometry . 2D projective geometry ▫ Homogeneous coordinates ▫ Points, Lines ▫ Duality . 3D projective geometry ▫ Points, Lines, Planes ▫ Duality ▫ Plane at infinity 3 Literature . Multiple View Geometry in Computer Vision. Richard Hartley and Andrew Zisserman. Cambridge University Press, March 2004. Mundy, J.L. and Zisserman, A., Geometric Invariance in Computer Vision, Appendix: Projective Geometry for Machine Vision, MIT Press, Cambridge, MA, 1992 . Available online: www.cs.cmu.edu/~ph/869/papers/zisser-mundy.pdf 4 Motivation – Image formation [Source: Charles Gunn] 5 Motivation – Parallel lines [Source: Flickr] 6 Motivation – Epipolar constraint X world point epipolar plane x x’ x‘TEx=0 C T C’ R 7 Euclidean geometry vs. projective geometry Definitions: . Geometry is the teaching of points, lines, planes and their relationships and properties (angles) . Geometries are defined based on invariances (what is changing if you transform a configuration of points, lines etc.) . Geometric transformations -
Study Guide for the Midterm. Topics: • Euclid • Incidence Geometry • Perspective Geometry • Neutral Geometry – Through Oct.18Th
Study guide for the midterm. Topics: • Euclid • Incidence geometry • Perspective geometry • Neutral geometry { through Oct.18th. You need to { Know definitions and examples. { Know theorems by names. { Be able to give a simple proof and justify every step. { Be able to explain those of Euclid's statements and proofs that appeared in the book, the problem set, the lecture, or the tutorial. Sources: • Class Notes • Problem Sets • Assigned reading • Notes on course website. The test. • Excerpts from Euclid will be provided if needed. • The incidence axioms will be provided if needed. • Postulates of neutral geometry will be provided if needed. • There will be at least one question that is similar or identical to a homework question. Tentative large list of terms. For each of the following terms, you should be able to write two sentences, in which you define it, state it, explain it, or discuss it. Euclid's geometry: - Euclid's definition of \right angle". - Euclid's definition of \parallel lines". - Euclid's \postulates" versus \common notions". - Euclid's working with geometric magnitudes rather than real numbers. - Congruence of segments and angles. - \All right angles are equal". - Euclid's fifth postulate. - \The whole is bigger than the part". - \Collapsing compass". - Euclid's reliance on diagrams. - SAS; SSS; ASA; AAS. - Base angles of an isosceles triangle. - Angles below the base of an isosceles triangle. - Exterior angle inequality. - Alternate interior angle theorem and its converse (we use the textbook's convention). - Vertical angle theorem. - The triangle inequality. - Pythagorean theorem. Incidence geometry: - collinear points. - concurrent lines. - Simple theorems of incidence geometry. - Interpretation/model for a theory. -
Arxiv:1609.06355V1 [Cs.CC] 20 Sep 2016 Outlaw Distributions And
Outlaw distributions and locally decodable codes Jop Bri¨et∗ Zeev Dvir† Sivakanth Gopi‡ September 22, 2016 Abstract Locally decodable codes (LDCs) are error correcting codes that allow for decoding of a single message bit using a small number of queries to a corrupted encoding. De- spite decades of study, the optimal trade-off between query complexity and codeword length is far from understood. In this work, we give a new characterization of LDCs using distributions over Boolean functions whose expectation is hard to approximate (in L∞ norm) with a small number of samples. We coin the term ‘outlaw distribu- tions’ for such distributions since they ‘defy’ the Law of Large Numbers. We show that the existence of outlaw distributions over sufficiently ‘smooth’ functions implies the existence of constant query LDCs and vice versa. We also give several candidates for outlaw distributions over smooth functions coming from finite field incidence geometry and from hypergraph (non)expanders. We also prove a useful lemma showing that (smooth) LDCs which are only required to work on average over a random message and a random message index can be turned into true LDCs at the cost of only constant factors in the parameters. 1 Introduction Error correcting codes (ECCs) solve the basic problem of communication over noisy channels. They encode a message into a codeword from which, even if the channel partially corrupts it, arXiv:1609.06355v1 [cs.CC] 20 Sep 2016 the message can later be retrieved. With one of the earliest applications of the probabilistic method, formally introduced by Erd˝os in 1947, pioneering work of Shannon [Sha48] showed the existence of optimal (capacity-achieving) ECCs. -
Connections Between Graph Theory, Additive Combinatorics, and Finite
UNIVERSITY OF CALIFORNIA, SAN DIEGO Connections between graph theory, additive combinatorics, and finite incidence geometry A dissertation submitted in partial satisfaction of the requirements for the degree Doctor of Philosophy in Mathematics by Michael Tait Committee in charge: Professor Jacques Verstra¨ete,Chair Professor Fan Chung Graham Professor Ronald Graham Professor Shachar Lovett Professor Brendon Rhoades 2016 Copyright Michael Tait, 2016 All rights reserved. The dissertation of Michael Tait is approved, and it is acceptable in quality and form for publication on microfilm and electronically: Chair University of California, San Diego 2016 iii DEDICATION To Lexi. iv TABLE OF CONTENTS Signature Page . iii Dedication . iv Table of Contents . .v List of Figures . vii Acknowledgements . viii Vita........................................x Abstract of the Dissertation . xi 1 Introduction . .1 1.1 Polarity graphs and the Tur´annumber for C4 ......2 1.2 Sidon sets and sum-product estimates . .3 1.3 Subplanes of projective planes . .4 1.4 Frequently used notation . .5 2 Quadrilateral-free graphs . .7 2.1 Introduction . .7 2.2 Preliminaries . .9 2.3 Proof of Theorem 2.1.1 and Corollary 2.1.2 . 11 2.4 Concluding remarks . 14 3 Coloring ERq ........................... 16 3.1 Introduction . 16 3.2 Proof of Theorem 3.1.7 . 21 3.3 Proof of Theorems 3.1.2 and 3.1.3 . 23 3.3.1 q a square . 24 3.3.2 q not a square . 26 3.4 Proof of Theorem 3.1.8 . 34 3.5 Concluding remarks on coloring ERq ........... 36 4 Chromatic and Independence Numbers of General Polarity Graphs . -
On Collineation Groups of Finite Planes
On collineation groups of finite planes Arrigo BONISOLI Dipartimento di Matematica Universit`adella Basilicata via N.Sauro 85 85100 Potenza (Italy) Socrates Intensive Programme Finite Geometries and Their Applications Gent, April of the WMY Please send all remarks to the author's e{mail address: [email protected] 1 Introduction From the Introduction to P. Dembowski's Finite Geometries, Springer, Berlin 1968: \ ::: An alternative approach to the study of projective planes began with a paper by BAER 1942 in which the close relationship between Desargues' theorem and the existence of central collineations was pointed out. Baer's notion of (p; L){transitivity, corresponding to this relationship, proved to be extremely fruitful. On the one hand, it provided a better understanding of coordinate structures (here SCHWAN 1919 was a forerunner); on the other hand it led eventually to the only coordinate{free, and hence geometrically satisfactory, classification of projective planes existing today, namely that by LENZ 1954 and BARLOTTI 1957. Due to deep discoveries in finite group theory the analysis of this classification has been particularly penetrating for 1 finite planes in recent years. In fact, finite groups were also applied with great success to problems not connected with (p; L){transitivity. ::: The field is influenced increasingly by problems, methods, and results in the theory of finite groups, mainly for the well known reason that the study of automorphisms \has always yielded the most powerful results" (E. Artin, Geometric Algebra, Interscience, New York 1957, p. 54). Finite{geometrical arguments can serve to prove group theoretical results, too, and it seems that the fruitful interplay between finite geometries and finite groups will become even closer in the future. -
Collineations in Perspective
Collineations in Perspective Now that we have a decent grasp of one-dimensional projectivities, we move on to their two di- mensional analogs. Although they are more complicated, in a sense, they may be easier to grasp because of the many applications to perspective drawing. Speaking of, let's return to the triangle on the window and its shadow in its full form instead of only looking at one line. Perspective Collineation In one dimension, a perspectivity is a bijective mapping from a line to a line through a point. In two dimensions, a perspective collineation is a bijective mapping from a plane to a plane through a point. To illustrate, consider the triangle on the window plane and its shadow on the ground plane as in Figure 1. We can see that every point on the triangle on the window maps to exactly one point on the shadow, but the collineation is from the entire window plane to the entire ground plane. We understand the window plane to extend infinitely in all directions (even going through the ground), the ground also extends infinitely in all directions (we will assume that the earth is flat here), and we map every point on the window to a point on the ground. Looking at Figure 2, we see that the lamp analogy breaks down when we consider all lines through O. Although it makes sense for the base of the triangle on the window mapped to its shadow on 1 the ground (A to A0 and B to B0), what do we make of the mapping C to C0, or D to D0? C is on the window plane, underground, while C0 is on the ground. -
FINITE FOURIER SERIES and OVALS in PG(2, 2H)
J. Aust. Math. Soc. 81 (2006), 21-34 FINITE FOURIER SERIES AND OVALS IN PG(2, 2h) J. CHRIS FISHERY and BERNHARD SCHMIDT (Received 2 April 2004; revised 7 May 2005) Communicated by L. Batten Abstract We propose the use of finite Fourier series as an alternative means of representing ovals in projective planes of even order. As an example to illustrate the method's potential, we show that the set [w1 + wy' + w ~y' : 0 < j < 2;'| c GF(22/1) forms an oval if w is a primitive (2h + l)sl root of unity in GF(22'') and GF(22'') is viewed as an affine plane over GF(2;'). For the verification, we only need some elementary 'trigonometric identities' and a basic irreducibility lemma that is of independent interest. Finally, we show that our example is the Payne oval when h is odd, and the Adelaide oval when h is even. 2000 Mathematics subject classification: primary 51E20, 05B25. 1. Introduction In any finite projective plane of order q, an oval is a set of q + 1 points, no three of which are collinear. In the classical plane PG(2, q) over GF(g), a nondegenerate conic is the prototypical oval. If the order of a plane is even, then the tangents to an oval all pass through a point that is called the nucleus of the oval. We call an oval together with its nucleus a hyperoval. During the 1950s Beniamino Segre proved that in PG(2, q), (1) when q is odd, then there exist no ovals other than the conies, and (2) when q — 2\ coordinates may be chosen so that the points of a hyperoval are the elements of the set {(*, f{x), 1) | JC G GF(<?)} U {(0, 1,0), (1,0, 0)}, where / is a permutation polynomial of degree at most q — 2 for which /(0) = 0, /(I) = 1, and with the additional property that for all 5 in GF(^), the function /,. -
Arcs, Ovals, and Segre's Theorem
Arcs, Ovals, and Segre's Theorem Brian Kronenthal Most recently updated on: October 6, 2012 1 Preliminary Definitions and Results Let π be a projective plane of order q. Definition 1.1. A k-arc is a set of k points in π, no three collinear. Proposition 1.2. Let K be a k-arc. Then k ≤ q + 2. Furthermore, if q is odd, then k ≤ q + 1. Proof. Let K be a k-arc, x 2 K. Since π has q + 1 lines through any point, there are exactly q + 1 lines containing x. Furthermore, since π has a unique line through any pair of points (x; y) with y 2 K n fxg, each of the k − 1 pairs corresponds to a unique line of the plane (if two pairs corresponded to the same line, we would have 3 collinear points in K, a contradiction). Since the number of such lines cannot excceed the total number of lines in π that contain x, we conclude k − 1 ≤ q + 1; thus, k ≤ q + 2. We will now prove the contrapositive of the second statement. To that end, suppose k = q + 2. Then equality holds in the above argument, and so every line L of π with x 2 L must also contain some y 2 K nfxg. Therefore, every line of π must contain either 0 or 2 points of K. Now, choose a fixed point z2 = K. Since every pair in the set S = f(x; z)jx 2 Kg determines a line, jSj = q + 2. As every line contains 0 or 2 points of K, every line intersecting K is represented by exactly two q+2 pairs of the form (x; z), x 2 K. -
The Trigonometry of Hyperbolic Tessellations
Canad. Math. Bull. Vol. 40 (2), 1997 pp. 158±168 THE TRIGONOMETRY OF HYPERBOLIC TESSELLATIONS H. S. M. COXETER ABSTRACT. For positive integers p and q with (p 2)(q 2) Ù 4thereis,inthe hyperbolic plane, a group [p, q] generated by re¯ections in the three sides of a triangle ABC with angles ôÛp, ôÛq, ôÛ2. Hyperbolic trigonometry shows that the side AC has length †,wherecosh†≥cÛs,c≥cos ôÛq, s ≥ sin ôÛp. For a conformal drawing inside the unit circle with centre A, we may take the sides AB and AC to run straight along radii while BC appears as an arc of a circle orthogonal to the unit circle.p The circle containing this arc is found to have radius 1Û sinh †≥sÛz,wherez≥ c2 s2, while its centre is at distance 1Û tanh †≥cÛzfrom A. In the hyperbolic triangle ABC,the altitude from AB to the right-angled vertex C is ê, where sinh ê≥z. 1. Non-Euclidean planes. The real projective plane becomes non-Euclidean when we introduce the concept of orthogonality by specializing one polarity so as to be able to declare two lines to be orthogonal when they are conjugate in this `absolute' polarity. The geometry is elliptic or hyperbolic according to the nature of the polarity. The points and lines of the elliptic plane ([11], x6.9) are conveniently represented, on a sphere of unit radius, by the pairs of antipodal points (or the diameters that join them) and the great circles (or the planes that contain them). The general right-angled triangle ABC, like such a triangle on the sphere, has ®ve `parts': its sides a, b, c and its acute angles A and B. -
Definitions and Nondefinability in Geometry 475 2
Definitions and Nondefinability in Geometry1 James T. Smith Abstract. Around 1900 some noted mathematicians published works developing geometry from its very beginning. They wanted to supplant approaches, based on Euclid’s, which han- dled some basic concepts awkwardly and imprecisely. They would introduce precision re- quired for generalization and application to new, delicate problems in higher mathematics. Their work was controversial: they departed from tradition, criticized standards of rigor, and addressed fundamental questions in philosophy. This paper follows the problem, Which geo- metric concepts are most elementary? It describes a false start, some successful solutions, and an argument that one of those is optimal. It’s about axioms, definitions, and definability, and emphasizes contributions of Mario Pieri (1860–1913) and Alfred Tarski (1901–1983). By fol- lowing this thread of ideas and personalities to the present, the author hopes to kindle interest in a fascinating research area and an exciting era in the history of mathematics. 1. INTRODUCTION. Around 1900 several noted mathematicians published major works on a subject familiar to us from school: developing geometry from the very beginning. They wanted to supplant the established approaches, which were based on Euclid’s, but which handled awkwardly and imprecisely some concepts that Euclid did not treat fully. They would present geometry with the precision required for general- ization and applications to new, delicate problems in higher mathematics—precision beyond the norm for most elementary classes. Work in this area was controversial: these mathematicians departed from tradition, criticized previous standards of rigor, and addressed fundamental questions in logic and philosophy of mathematics.2 After establishing background, this paper tells a story about research into the ques- tion, Which geometric concepts are most elementary? It describes a false start, some successful solutions, and a demonstration that one of those is in a sense optimal. -
Projective Planes
Projective Planes A projective plane is an incidence system of points and lines satisfying the following axioms: (P1) Any two distinct points are joined by exactly one line. (P2) Any two distinct lines meet in exactly one point. (P3) There exists a quadrangle: four points of which no three are collinear. In class we will exhibit a projective plane with 57 points and 57 lines: the game of The Fano Plane (of order 2): SpotIt®. (Actually the game is sold with 7 points, 7 lines only 55 lines; for the purposes of this 3 points on each line class I have added the two missing lines.) 3 lines through each point The smallest projective plane, often called the Fano plane, has seven points and seven lines, as shown on the right. The Projective Plane of order 3: 13 points, 13 lines The second smallest 4 points on each line projective plane, 4 lines through each point having thirteen points 0, 1, 2, …, 12 and thirteen lines A, B, C, …, M is shown on the left. These two planes are coordinatized by the fields of order 2 and 3 respectively; this accounts for the term ‘order’ which we shall define shortly. Given any field 퐹, the classical projective plane over 퐹 is constructed from a 3-dimensional vector space 퐹3 = {(푥, 푦, 푧) ∶ 푥, 푦, 푧 ∈ 퐹} as follows: ‘Points’ are one-dimensional subspaces 〈(푥, 푦, 푧)〉. Here (푥, 푦, 푧) ∈ 퐹3 is any nonzero vector; it spans a one-dimensional subspace 〈(푥, 푦, 푧)〉 = {휆(푥, 푦, 푧) ∶ 휆 ∈ 퐹}.