Automorphisms of Classical Geometries in the Sense of Klein
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Globally Optimal Affine and Metric Upgrades in Stratified Autocalibration
Globally Optimal Affine and Metric Upgrades in Stratified Autocalibration Manmohan Chandrakery Sameer Agarwalz David Kriegmany Serge Belongiey [email protected] [email protected] [email protected] [email protected] y University of California, San Diego z University of Washington, Seattle Abstract parameters of the cameras, which is commonly approached by estimating the dual image of the absolute conic (DIAC). We present a practical, stratified autocalibration algo- A variety of linear methods exist towards this end, how- rithm with theoretical guarantees of global optimality. Given ever, they are known to perform poorly in the presence of a projective reconstruction, the first stage of the algorithm noise [10]. Perhaps more significantly, most methods a pos- upgrades it to affine by estimating the position of the plane teriori impose the positive semidefiniteness of the DIAC, at infinity. The plane at infinity is computed by globally which might lead to a spurious calibration. Thus, it is im- minimizing a least squares formulation of the modulus con- portant to impose the positive semidefiniteness of the DIAC straints. In the second stage, the algorithm upgrades this within the optimization, not as a post-processing step. affine reconstruction to a metric one by globally minimizing This paper proposes global minimization algorithms for the infinite homography relation to compute the dual image both stages of stratified autocalibration that furnish theoreti- of the absolute conic (DIAC). The positive semidefiniteness cal certificates of optimality. That is, they return a solution at of the DIAC is explicitly enforced as part of the optimization most away from the global minimum, for arbitrarily small . -
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 -
On Absolute Points of Correlations in PG $(2, Q^ N) $
On absolute points of correlations in PG(2,qn) Jozefien D’haeseleer ∗ Department of Mathematics: Analysis, Logic and Discrete Mathematics Ghent University Gent, Flanders, Belgium [email protected] Nicola Durante Dipartimento di Matematica e Applicazioni ”Caccioppoli” Universit`adi Napoli ”Federico II”, Complesso di Monte S. Angelo Napoli, Italy [email protected] Submitted: Aug 1, 2019; Accepted: May 8, 2020; Published: TBD c The authors. Released under the CC BY-ND license (International 4.0). Abstract Let V bea(d+1)-dimensional vector space over a field F. Sesquilinear forms over V have been largely studied when they are reflexive and hence give rise to a (possibly degenerate) polarity of the d-dimensional projective space PG(V ). Everything is known in this case for both degenerate and non-degenerate reflexive forms if F is either R, C or a finite field Fq. In this paper we consider degenerate, non- F3 reflexive sesquilinear forms of V = qn . We will see that these forms give rise to degenerate correlations of PG(2,qn) whose set of absolute points are, besides cones, m the (possibly degenerate) CF -sets studied in [8]. In the final section we collect some results from the huge work of B.C. Kestenband regarding what is known for the set of the absolute points of correlations in PG(2,qn) induced by a non-degenerate, F3 non-reflexive sesquilinear form of V = qn . Mathematics Subject Classifications: 51E21,05B25 arXiv:2005.05698v1 [math.CO] 12 May 2020 1 Introduction and definitions Let V and W be two vector spaces over the same field F. -
[Math.GR] 9 Jul 2003 Buildings and Classical Groups
Buildings and Classical Groups Linus Kramer∗ Mathematisches Institut, Universit¨at W¨urzburg Am Hubland, D–97074 W¨urzburg, Germany email: [email protected] In these notes we describe the classical groups, that is, the linear groups and the orthogonal, symplectic, and unitary groups, acting on finite dimen- sional vector spaces over skew fields, as well as their pseudo-quadratic gen- eralizations. Each such group corresponds in a natural way to a point-line geometry, and to a spherical building. The geometries in question are pro- jective spaces and polar spaces. We emphasize in particular the rˆole played by root elations and the groups generated by these elations. The root ela- tions reflect — via their commutator relations — algebraic properties of the underlying vector space. We also discuss some related algebraic topics: the classical groups as per- mutation groups and the associated simple groups. I have included some remarks on K-theory, which might be interesting for applications. The first K-group measures the difference between the classical group and its subgroup generated by the root elations. The second K-group is a kind of fundamental group of the group generated by the root elations and is related to central extensions. I also included some material on Moufang sets, since this is an in- arXiv:math/0307117v1 [math.GR] 9 Jul 2003 teresting topic. In this context, the projective line over a skew field is treated in some detail, and possibly with some new results. The theory of unitary groups is developed along the lines of Hahn & O’Meara [15]. -
Morita Equivalence and Isomorphisms Between General Linear Groups
Morita Equivalence and Isomorphisms between General Linear Groups by LOK Tsan-ming , f 〜 旮 // (z 织.'U f/ ’; 乂.: ,...‘. f-- 1 K SEP :;! : \V:丄:、 -...- A thesis Submitted to the Graduate School of The Chinese University of Hong Kong (Division of Mathematics) In Partial Fulfiilinent of the Requirement the Degree of Master of Philosophy(M. Phil.) HONG KONG June, 1994 I《)/ l入 G:升 16 1 _ j / L- b ! ? ^ LL [I l i Abstract In this thesis, we generalize Bolla's theorem. We replace progenerators in Bolla's theorem by quasiprogenerators. Then, we use this result to describe the isomorphisms between general linear groups over rings. Some characterizations of these isomorphisms are obtained. We also prove some results about the endomorphism ring of infinitely generated projective module. The relationship between the annihilators and closed submodules of infinitely generated projective module is investigated. Acknowledgement I would like to express my deepest gratitude to Dr. K. P. Shum for his energetic and stimulating guidance. His supervision has helped me a lot during the preparation of this thesis. LOK Tsan-ming The Chinese University of Hong Kong June, 1994 The Chinese University of Hong Kong Graduate School The undersigned certify that we have read a thesis, entitled “Morita Equivalence and Isomorphisms between General Linear Groups" submitted to the Graduate School by LOK Tsan-ming ( ) in Partial fulfillment of the requirements for the degree of Master of Philosophy in Mathematics. We recommend that it be accepted. Dr. K. P. Shum, Supervisor Dr. K. W. Leung ( ) ( ) Dr. C. W. Leung Prof. Yonghua Xu, External Examiner ( ) ("I今永等)各^^L^ Prof. -
148. Symplectic Translation Planes by Antoni
Lecture Notes of Seminario Interdisciplinare di Matematica Vol. 2 (2003), pp. 101 - 148. Symplectic translation planes by Antonio Maschietti Abstract1. A great deal of important work on symplectic translation planes has occurred in the last two decades, especially on those of even order, because of their link with non-linear codes. This link, which is the central theme of this paper, is based upon classical groups, particularly symplectic and orthogonal groups. Therefore I have included an Appendix, where standard notation and basic results are recalled. 1. Translation planes In this section we give an introductory account of translation planes. Compre- hensive textbooks are for example [17] and [3]. 1.1. Notation. We will use linear algebra to construct interesting geometrical structures from vector spaces, with special regard to vector spaces over finite fields. Any finite field has prime power order and for any prime power q there is, up to isomorphisms, a unique finite field of order q. This unique field is commonly de- noted by GF (q)(Galois Field); but also other symbols are usual, such as Fq.If q = pn with p a prime, the additive structure of F is that of an n dimensional q − vector space over Fp, which is the field of integers modulo p. The multiplicative group of Fq, denoted by Fq⇤, is cyclic. Finally, the automorphism group of the field Fq is cyclic of order n. Let A and B be sets. If f : A B is a map (or function or else mapping), then the image of x A will be denoted! by f(x)(functional notation). -
Feature Matching and Heat Flow in Centro-Affine Geometry
Symmetry, Integrability and Geometry: Methods and Applications SIGMA 16 (2020), 093, 22 pages Feature Matching and Heat Flow in Centro-Affine Geometry Peter J. OLVER y, Changzheng QU z and Yun YANG x y School of Mathematics, University of Minnesota, Minneapolis, MN 55455, USA E-mail: [email protected] URL: http://www.math.umn.edu/~olver/ z School of Mathematics and Statistics, Ningbo University, Ningbo 315211, P.R. China E-mail: [email protected] x Department of Mathematics, Northeastern University, Shenyang, 110819, P.R. China E-mail: [email protected] Received April 02, 2020, in final form September 14, 2020; Published online September 29, 2020 https://doi.org/10.3842/SIGMA.2020.093 Abstract. In this paper, we study the differential invariants and the invariant heat flow in centro-affine geometry, proving that the latter is equivalent to the inviscid Burgers' equa- tion. Furthermore, we apply the centro-affine invariants to develop an invariant algorithm to match features of objects appearing in images. We show that the resulting algorithm com- pares favorably with the widely applied scale-invariant feature transform (SIFT), speeded up robust features (SURF), and affine-SIFT (ASIFT) methods. Key words: centro-affine geometry; equivariant moving frames; heat flow; inviscid Burgers' equation; differential invariant; edge matching 2020 Mathematics Subject Classification: 53A15; 53A55 1 Introduction The main objective in this paper is to study differential invariants and invariant curve flows { in particular the heat flow { in centro-affine geometry. In addition, we will present some basic applications to feature matching in camera images of three-dimensional objects, comparing our method with other popular algorithms. -
Estimating Projective Transformation Matrix (Collineation, Homography)
Estimating Projective Transformation Matrix (Collineation, Homography) Zhengyou Zhang Microsoft Research One Microsoft Way, Redmond, WA 98052, USA E-mail: [email protected] November 1993; Updated May 29, 2010 Microsoft Research Techical Report MSR-TR-2010-63 Note: The original version of this report was written in November 1993 while I was at INRIA. It was circulated among very few people, and never published. I am now publishing it as a tech report, adding Section 7, with the hope that it could be useful to more people. Abstract In many applications, one is required to estimate the projective transformation between two sets of points, which is also known as collineation or homography. This report presents a number of techniques for this purpose. Contents 1 Introduction 2 2 Method 1: Five-correspondences case 3 3 Method 2: Compute P together with the scalar factors 3 4 Method 3: Compute P only (a batch approach) 5 5 Method 4: Compute P only (an iterative approach) 6 6 Method 5: Compute P through normalization 7 7 Method 6: Maximum Likelihood Estimation 8 1 1 Introduction Projective Transformation is a concept used in projective geometry to describe how a set of geometric objects maps to another set of geometric objects in projective space. The basic intuition behind projective space is to add extra points (points at infinity) to Euclidean space, and the geometric transformation allows to move those extra points to traditional points, and vice versa. Homogeneous coordinates are used in projective space much as Cartesian coordinates are used in Euclidean space. A point in two dimensions is described by a 3D vector. -
• Rotations • Camera Calibration • Homography • Ransac
Agenda • Rotations • Camera calibration • Homography • Ransac Geometric Transformations y 164 Computer Vision: Algorithms andx Applications (September 3, 2010 draft) Transformation Matrix # DoF Preserves Icon translation I t 2 orientation 2 3 h i ⇥ ⇢⇢SS rigid (Euclidean) R t 3 lengths S ⇢ 2 3 S⇢ ⇥ h i ⇢ similarity sR t 4 angles S 2 3 S⇢ h i ⇥ ⇥ ⇥ affine A 6 parallelism ⇥ ⇥ 2 3 h i ⇥ projective H˜ 8 straight lines ` 3 3 ` h i ⇥ Table 3.5 Hierarchy of 2D coordinate transformations. Each transformation also preserves Let’s definethe properties families listed of in thetransformations rows below it, i.e., similarity by the preserves properties not only anglesthat butthey also preserve parallelism and straight lines. The 2 3 matrices are extended with a third [0T 1] row to form ⇥ a full 3 3 matrix for homogeneous coordinate transformations. ⇥ amples of such transformations, which are based on the 2D geometric transformations shown in Figure 2.4. The formulas for these transformations were originally given in Table 2.1 and are reproduced here in Table 3.5 for ease of reference. In general, given a transformation specified by a formula x0 = h(x) and a source image f(x), how do we compute the values of the pixels in the new image g(x), as given in (3.88)? Think about this for a minute before proceeding and see if you can figure it out. If you are like most people, you will come up with an algorithm that looks something like Algorithm 3.1. This process is called forward warping or forward mapping and is shown in Figure 3.46a. -
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Acta Math. Univ. Comenianae 911 Vol. LXXXVIII, 3 (2019), pp. 911{916 COSET GEOMETRIES WITH TRIALITIES AND THEIR REDUCED INCIDENCE GRAPHS D. LEEMANS and K. STOKES Abstract. In this article we explore combinatorial trialities of incidence geome- tries. We give a construction that uses coset geometries to construct examples of incidence geometries with trialities and prescribed automorphism group. We define the reduced incidence graph of the geometry to be the oriented graph obtained as the quotient of the geometry under the triality. Our chosen examples exhibit interesting features relating the automorphism group of the geometry and the automorphism group of the reduced incidence graphs. 1. Introduction The projective space of dimension n over a field F is an incidence geometry PG(n; F ). It has n types of elements; the projective subspaces: the points, the lines, the planes, and so on. The elements are related by incidence, defined by inclusion. A collinearity of PG(n; F ) is an automorphism preserving incidence and type. According to the Fundamental theorem of projective geometry, every collinearity is composed by a homography and a field automorphism. A duality of PG(n; F ) is an automorphism preserving incidence that maps elements of type k to elements of type n − k − 1. Dualities are also called correlations or reciprocities. Geometric dualities, that is, dualities in projective spaces, correspond to sesquilinear forms. Therefore the classification of the sesquilinear forms also give a classification of the geometric dualities. A polarity is a duality δ that is an involution, that is, δ2 = Id. A duality can always be expressed as a composition of a polarity and a collinearity. -
Arxiv:1305.5974V1 [Math-Ph]
INTRODUCTION TO SPORADIC GROUPS for physicists Luis J. Boya∗ Departamento de F´ısica Te´orica Universidad de Zaragoza E-50009 Zaragoza, SPAIN MSC: 20D08, 20D05, 11F22 PACS numbers: 02.20.a, 02.20.Bb, 11.24.Yb Key words: Finite simple groups, sporadic groups, the Monster group. Juan SANCHO GUIMERA´ In Memoriam Abstract We describe the collection of finite simple groups, with a view on physical applications. We recall first the prime cyclic groups Zp, and the alternating groups Altn>4. After a quick revision of finite fields Fq, q = pf , with p prime, we consider the 16 families of finite simple groups of Lie type. There are also 26 extra “sporadic” groups, which gather in three interconnected “generations” (with 5+7+8 groups) plus the Pariah groups (6). We point out a couple of physical applications, in- cluding constructing the biggest sporadic group, the “Monster” group, with close to 1054 elements from arguments of physics, and also the relation of some Mathieu groups with compactification in string and M-theory. ∗[email protected] arXiv:1305.5974v1 [math-ph] 25 May 2013 1 Contents 1 Introduction 3 1.1 Generaldescriptionofthework . 3 1.2 Initialmathematics............................ 7 2 Generalities about groups 14 2.1 Elementarynotions............................ 14 2.2 Theframeworkorbox .......................... 16 2.3 Subgroups................................. 18 2.4 Morphisms ................................ 22 2.5 Extensions................................. 23 2.6 Familiesoffinitegroups ......................... 24 2.7 Abeliangroups .............................. 27 2.8 Symmetricgroup ............................. 28 3 More advanced group theory 30 3.1 Groupsoperationginspaces. 30 3.2 Representations.............................. 32 3.3 Characters.Fourierseries . 35 3.4 Homological algebra and extension theory . 37 3.5 Groupsuptoorder16..........................