CS-9645 Introduction to Computer Vision Techniques Winter 2019

Similar documents
Multiple View Geometry in Computer Vision

Projective geometry for Computer Vision

Projective 2D Geometry

3D Computer Vision II. Reminder Projective Geometry, Transformations

Robot Vision: Projective Geometry

MAT 3271: Selected Solutions to the Assignment 6

Multiple View Geometry in Computer Vision

EM225 Projective Geometry Part 2

Epipolar Geometry Prof. D. Stricker. With slides from A. Zisserman, S. Lazebnik, Seitz

Part 0. The Background: Projective Geometry, Transformations and Estimation

Computer Vision I - Appearance-based Matching and Projective Geometry

Auto-calibration. Computer Vision II CSE 252B

CSE 252B: Computer Vision II

Computer Vision Projective Geometry and Calibration. Pinhole cameras

Computer Vision I - Appearance-based Matching and Projective Geometry

Inversive Plane Geometry

Homogeneous Coordinates. Lecture18: Camera Models. Representation of Line and Point in 2D. Cross Product. Overall scaling is NOT important.

TECHNISCHE UNIVERSITÄT BERLIN WS2005 Fachbereich 3 - Mathematik Prof. Dr. U. Pinkall / Charles Gunn Abgabe:

Provide a drawing. Mark any line with three points in blue color.

Epipolar Geometry and the Essential Matrix

Geometric transformations assign a point to a point, so it is a point valued function of points. Geometric transformation may destroy the equation

Interpretations and Models. Chapter Axiomatic Systems and Incidence Geometry

Multiple Views Geometry

Computer Vision I - Algorithms and Applications: Multi-View 3D reconstruction

Technische Universität München Zentrum Mathematik

Test 1, Spring 2013 ( Solutions): Provided by Jeff Collins and Anil Patel. 1. Axioms for a finite AFFINE plane of order n.

Camera Projection Models We will introduce different camera projection models that relate the location of an image point to the coordinates of the

calibrated coordinates Linear transformation pixel coordinates

CS 664 Slides #9 Multi-Camera Geometry. Prof. Dan Huttenlocher Fall 2003

Camera model and multiple view geometry

Visual Recognition: Image Formation

Synthetic Geometry. 1.1 Foundations 1.2 The axioms of projective geometry

N-Views (1) Homographies and Projection

274 Curves on Surfaces, Lecture 5

Projective geometry, camera models and calibration

PROJECTIVE SPACE AND THE PINHOLE CAMERA

Steiner's Porism: An Activity Using the TI-92 Paul Beem Indiana University South Bend, IN

Multiple View Geometry in Computer Vision

Computer Vision Project-1

Metric Rectification for Perspective Images of Planes

METR Robotics Tutorial 2 Week 2: Homogeneous Coordinates

Topics in geometry Exam 1 Solutions 7/8/4

(1) Page #1 24 all. (2) Page #7-21 odd, all. (3) Page #8 20 Even, Page 35 # (4) Page #1 8 all #13 23 odd

TWO COORDINATIZATION THEOREMS FOR PROJECTIVE PLANES

Technische Universität München Zentrum Mathematik

Ray-Triangle and Ray-Quadrilateral Intersections in Homogeneous Coordinates

3D reconstruction class 11

Projective spaces and Bézout s theorem

MA 323 Geometric Modelling Course Notes: Day 21 Three Dimensional Bezier Curves, Projections and Rational Bezier Curves

Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives. Partial Derivatives

CHAPTER 3. Single-view Geometry. 1. Consequences of Projection

Multiple View Geometry in computer vision

Camera Calibration Using Line Correspondences

Single View Geometry. Camera model & Orientation + Position estimation. What am I?

Homogeneous coordinates, lines, screws and twists

7. The Gauss-Bonnet theorem

Generation of lattices of points for bivariate interpolation

Definition 1 (Hand-shake model). A hand shake model is an incidence geometry for which every line has exactly two points.

LECTURE 13, THURSDAY APRIL 1, 2004

Projective geometry and the extended Euclidean plane

1 Affine and Projective Coordinate Notation

Computer Vision. 2. Projective Geometry in 3D. Lars Schmidt-Thieme

Homogeneous Coordinates and Transformations of the Plane

CSE 252B: Computer Vision II

Duality of Plane Curves

2 Solution of Homework

Structure from Motion. Prof. Marco Marcon

A Transformation Based on the Cubic Parabola y = x 3

Geometric Algebra. 8. Conformal Geometric Algebra. Dr Chris Doran ARM Research

A Communications Network???

Invariance of l and the Conic Dual to Circular Points C

Notes on Spherical Geometry

Conic Duality. yyye

Parameterization of triangular meshes

C / 35. C18 Computer Vision. David Murray. dwm/courses/4cv.

Basic Euclidean Geometry

We have set up our axioms to deal with the geometry of space but have not yet developed these ideas much. Let s redress that imbalance.

The Three Dimensional Coordinate System

Definition 2 (Projective plane). A projective plane is a class of points, and a class of lines satisfying the axioms:

Computer Vision I Name : CSE 252A, Fall 2012 Student ID : David Kriegman Assignment #1. (Due date: 10/23/2012) x P. = z

Unlabeled equivalence for matroids representable over finite fields

Viewing. Reading: Angel Ch.5

In what follows, we will focus on Voronoi diagrams in Euclidean space. Later, we will generalize to other distance spaces.

Technische Universität München Zentrum Mathematik

Part II. Working and Playing with Geometry

Coordinate Free Perspective Projection of Points in the Conformal Model Using Transversions

Final Exam 1:15-3:15 pm Thursday, December 13, 2018

Gergonne and Nagel Points for Simplices in the n-dimensional Space

ON THE CONSTRUCTION OF ORTHOGONAL ARRAYS

Jorg s Graphics Lecture Notes Coordinate Spaces 1

Linear Multi View Reconstruction and Camera Recovery Using a Reference Plane

Chapter 6. Curves and Surfaces. 6.1 Graphs as Surfaces

Vectors and the Geometry of Space

Projective Geometry for Image Analysis

Computer Vision Projective Geometry and Calibration. Pinhole cameras

Convex Optimization. 2. Convex Sets. Prof. Ying Cui. Department of Electrical Engineering Shanghai Jiao Tong University. SJTU Ying Cui 1 / 33

A Stratified Approach for Camera Calibration Using Spheres

Planar homographies. Can we reconstruct another view from one image? vgg/projects/singleview/

3D Geometric Computer Vision. Martin Jagersand Univ. Alberta Edmonton, Alberta, Canada

Mathematically, the path or the trajectory of a particle moving in space in described by a function of time.

Transcription:

Table of Contents Projective Geometry... 1 Definitions...1 Axioms of Projective Geometry... Ideal Points...3 Geometric Interpretation... 3 Fundamental Transformations of Projective Geometry... 4 The D Projective Plane...4 Ideal Points and Lines at Infinity... 5 Conics...5 Projective Transformations...6 Projective Geometry The concept of homogeneous coordinates can be properly understood only within the framework of projective geometry, which defines proper invariants under projections and sections. Definitions Let α be a plane in R 3. To each line in this plane (l α) we associate an ideal point (at infinity) L such that distinct intersecting lines have distinct ideal points. Thus, ideal points signify direction. When the slope of line is of interest, then its associated ideal point is denoted as P m. The pair (l, L ) is called an augmented line. For lines r, s α, their intersection is an ordinary point P if the lines are not parallel, or is either R or S if they are parallel. Given a plane π in R 3, let p ={L l π, (l, L )} be the set of all ideal points (directions) on π. Then, p satisfies the axioms of a line and is called an ideal line. The pair (π, p ) is called an augmented plane for it satisfies the axioms of a plane. The set of all ideal lines for each plane π R 3 is denoted by π ={ p π R 3, (π, p )} where π is an augmented plane and (R 3, π ) is the augmented space. Therefore, points can be ordinary or ideal, lines can be ordinary or ideal, and planes can be augmented planes or the ideal plane.

Illustration 1 shows Hilbert's model of the projective plane. The semi-sphere sits at the origin of a plane. It is easy to see how parallel lines on this plane project onto the semi-sphere as semi-cicles, assuming that the center of projection is the center of the sphere of which the semi-sphere is a part. It can be clearly seen that these semi-circles formed by parallel lines all intersect at their common ideal point. Axioms of Projective Geometry Illustration 1: Hilbert's model of the projective plane Two distinct points are incident to a unique line Three distinct, non-collinear points are on a unique plane Two distinct coplanar lines are on a unique point A plane and a line not contained by the plane are incident to a unique point

Two distinct planes are incident to a unique line Duality expresses the fact that points and lines are equivalent in D, and that points an planes are equivalent in 3D. In Euclidean geometry, infinity is a concept that does not exist and one of the purposes of homogeneous coordinates is to capture it in its essence. Given a point ( x, y, ω) T in homogeneous coordinates, its corresponding coordinates in the xy plane is ( x/ω, y/ω) T. Hence, a point (3,4,5) T in homogeneous coordinates converts to a point (3/5,4/5) T in this plane. Similarly, a point ( x, y, z, ω) T in homogeneous coordinates converts to ( x/ω, y/ω, z/ω) T in R 3 space. Conversely, the homogeneous coordinates of ( x, y) T are ( x, y, 1) T. But in general, the homogeneous coordinates for this point are not unique. They are represented by ( x ω, y ω, z ω,ω) T for any ω 0. Ideal Points Let a point ( x, y) T be fixed and converted to homogeneous coordinates by multiplying it with 1/ ω as we let ω 0. Then ( x/ω, y/ω) T moves farther away in the direction ( x, y) T. In the limit, ( x/ω, y/ω) is at infinity. Hence, the homogeneous coordinates ( x, y, ω) T = (x, y, 0) T Illustration : Perspective projection creates is the ideal vanishing points point in the direction ( x, y) T, as ω 0. In the field of computer vision, ideal points take the form of vanishing points. For example, under perspective projection, the tracks of a railroad will join at infinity while never intersecting. Similarly, the vanishing point of an optical flow field (known as the focus of expansion) specifies the 3D translation of the observer (See Illustrations and 3). Geometric Interpretation The homogeneous coordinate ( x, y, ω) T intersects the plane ω=1 at ( x/ω, y /ω,1) T. This is known as a perspective projection of a 3D scene point onto a D image plane, parallel to the xy plane and away from the origin by a distance of 1. One important point to remember is that the transformation from

ordinary coordinates to homogeneous coordinates is not unique. Fundamental Transformations of Projective Geometry Consider two directed lines p and p ' and a point P not on either of these lines. Then, a line on P intersecting p at A and p ' at A' establishes a one-toone correspondence between the points of the lines, called perspectivity, denoted as: Illustration 3: The focus of expansion in an optical flow field is p( A, B,C, D, ) P = p' ( A', B ',C ', ) a vanishing point and the lines are said to be in perspective with respect to point P (See illustration 4; the dual concept also exists). Given a perspectivity, a cross-ratio can be defined as: ( A, B ; C, D) = AB/ BC AD / BD which is invariant under perspectivity. This definition is in the Euclidean plane. However, it can be generalized to the augmented plane (π, p ), the cross-ratio invariance being a projective property. Illustration 4: Two lines in perspective of a point The set of lines on a point is called pencil of lines (also dual), and may undergo successive perspectives: A sequence of perspectivities is called a projectivity. As a consequence of the cross-ratio theorem, projective transformations are linear. An important result, for which the proof lies beyond the scope of this course. The D Projective Plane p 1 p 1 = p p 1 = p n 1 = A line in the plane is represented by an equation such as ax+by+c=0. A line is thus naturally expressed as a vector (a,b, c) T. The correspondence between lines and vectors is not a bijection (one-to-one) and the lines ax+by+c=0 and kax+kby+kc=0 are the same for any k 0. Hence, any vector (a,b, c) T is said to be homogeneous and representative of an equivalence class p n

{k (a, b, c) T k 0}. A point x=( x, y) T lies on a line l=(a,b,c) T if and only if ( x, y,1)l=0. For any constant k 0 and line l the equation k ( x, y,1)l=0 if and only if ( x, y,1)l=0. It is thus natural to consider the set of vectors (kx, ky, k) T to be a representation of the point ( x, y) T in R. Then, an arbitrary homogeneous vector ( x 1, x, x 3 ) represents ( x 1 / x 3, x / x 3 ) T in R. The point x lies on the line l if and only if x T l=0 Given two lines l 1 and l, their intersection is given by l 1 l. The line through two points x 1 and x is l= x 1 x Ideal Points and Lines at Infinity Consider two lines l 1 =(a,b, c) and l =(a, b, c' ). These lines are parallel but computing their intersection as l 1 l is possible and yields (c c' )(b, a, 0) T.. Ignoring the scale factor (c c' ), the intersection point is thus (b, a,0) T. If we attempt to compute the inhomogeneous coordinates of this point we obtain (b/0, a/0) T which makes no sense except to suggest that the coordinates of the intersection point are infinitely large. In general, points with homogeneous coordinates ( x, y, 0) T do not correspond to any finite point in R. Homogeneous vectors ( x 1, x, x 3 ) T such that x 3 0 correspond to finite points in R. We can augment R by adding points with last coordinate x 3 =0, known as ideal points. The result is the set of all homogeneous 3-vectors, called the D projective space. The set of all ideal points lies on a line at infinity l =(0,0,1) T. This can be verified by realizing that ( x 1, x, 0)(0,0,1) T =0 for all ( x 1, x, 0) T. Line l=(a,b,c) T intersects with line at infinity l at ideal point l l =(b, a,0) T which is a vector tangent to l and represents the direction of the line. Hence the line at infinity can be thought of as the set of directions of lines in the plane. We can think of the D projective plane as a set of rays in R 3. The set of all vectors k (x 1, x, x 3 ) T as k varies forms a ray through the origin. Such a ray may be thought of as representing a single point in the D projective plane. Using this analogy, a line in the projective plane is a plane passing through the origin of R 3. Conics A conic is a curve described by a second degree equation in the plane. In D projective geometry, all conics are equivalent under projective transformations. The equation of a conic in inhomogeneous coordinates is given by:

which is a polynomial of degree. Using homogeneous coordinates (that is, replacing x by x 1 / x 3 and y by x / x 3 ) gives: or in matrix form: where ax +bxy+cy +dx+ey+ f =0 a x 1 +b x 1 x +c x +d x 1 x 3 +e x x 3 + f x 3 =0 x T C x [ a b/ d / ] C = b/ c e/ d / e/ f Note that this matrix is symmetric. A minimum number of five points define a conic. A general constraint for a point x i =(x i, y i ) T can be written as: where c=(a, b, c, d,e, f ) T yields:. Defining the system of equations for five points [ x1 x x 3 x 4 x 5 where c is the solution, called the null vector, as it yields the null space. An interesting result is the form a line tangent to a conic at a point x takes: The line l tangent to a conic at x is given by l = C x. The conic C as defined above is called a point conic. However, due to duality, also five lines define a conic. Projective Transformations ( x i, x i y i, y i, x i, y i,1) c x 1 y 1 y 1 x y y x 3 y 3 y 3 x 4 y 4 y 4 x 5 y 5 y 5 x 1 y 1 1 x y 1 x 3 y 3 1 c = 0 x 4 y 4 1 x 5 y 5 1] A projectivity is an invertible mapping h from the D projective space into itself such that three points x 1, x, x 3 lie on the same line if and only if h( x 1 ), h( x ), and h( x 3 ) also do. A projectivity is also called a collineation, a projective transformation, or a homography. These terms are synonymous. A planar projective transformation is a linear transformation on homogeneous 3-

vectors represented by a non-singular 3 by 3 matrix: x =H x 1. Note that this matrix may be changed by a scale factor without altering the projective transformation. We consequently say that the matrix is homogeneous since only the ratio of the matrix elements is significant. There are eight independent ratios amongst the nine elements of H, and it follows that a projective transformation has eight degrees of freedom.