Geometric Transformations CSE P 576 Larry Zitnick

Slides:



Advertisements
Similar presentations
Image Rectification for Stereo Vision
Advertisements

CS 691 Computational Photography Instructor: Gianfranco Doretto Image Warping.
Computer Vision, Robert Pless
Recovery of affine and metric properties from images in 2D Projective space Ko Dae-Won.
Correcting Projector Distortions on Planar Screens via Homography
1 pb.  camera model  calibration  separation (int/ext)  pose Don’t get lost! What are we doing? Projective geometry Numerical tools Uncalibrated cameras.
1 Computer Graphics Chapter 6 2D Transformations.
Image alignment Image from
Lecture 11: Transformations CS4670/5760: Computer Vision Kavita Bala.
Single-view metrology
The 2D Projective Plane Points and Lines.
Lecture 8: Geometric transformations CS4670: Computer Vision Noah Snavely.
Uncalibrated Geometry & Stratification Sastry and Yang
Lecture 7: Image Alignment and Panoramas CS6670: Computer Vision Noah Snavely What’s inside your fridge?
3D reconstruction of cameras and structure x i = PX i x’ i = P’X i.
Lecture 9: Image alignment CS4670: Computer Vision Noah Snavely
1 Geometrical Transformation Tong-Yee Lee. 2 Modeling Transform Specify transformation for objects Allow definitions of objects in own coordinate systems.
MSU CSE 803 Stockman CV: Matching in 2D Matching 2D images to 2D images; Matching 2D images to 2D maps or 2D models; Matching 2D maps to 2D maps.
Image Stitching Ali Farhadi CSE 455
Out-of-plane Rotations Environment constraints ● Surveillance systems ● Car driver images ASM: ● Similarity does not remove 3D pose ● Multiple-view database.
Projective Geometry and Geometric Invariance in Computer Vision Babak N. Araabi Electrical and Computer Eng. Dept. University of Tehran Workshop on image.
Geometry Notes Lesson 4.3B – Similarity and Scale Drawings T.2.G.1 Apply congruence (SSS …) and similarity (AA …) correspondences and properties of figures.
Warping CSE 590 Computational Photography Tamara Berg.
Homogeneous Coordinates (Projective Space) Let be a point in Euclidean space Change to homogeneous coordinates: Defined up to scale: Can go back to non-homogeneous.
Autonomous Navigation for Flying Robots Lecture 2.2: 2D Geometry
Imaging Geometry for the Pinhole Camera Outline: Motivation |The pinhole camera.
Digital Image Processing Lecture 7: Geometric Transformation March 16, 2005 Prof. Charlene Tsai.
Metrology 1.Perspective distortion. 2.Depth is lost.
Single View Geometry Course web page: vision.cis.udel.edu/cv April 9, 2003  Lecture 20.
Geometry Lesson 4.3A Similarity
Geometric Transformations CSE 455 Ali Farhadi Many slides from Steve Seitz and Larry Zitnick.
Term Transformation Describe The change in the position of a geometric figure, the pre-image, that produces a new figure called the image Representation.
L6 – Transformations in the Euclidean Plane NGEN06(TEK230) – Algorithms in Geographical Information Systems by: Irene Rangel, updated by Sadegh Jamali.
Reconnaissance d’objets et vision artificielle Jean Ponce Equipe-projet WILLOW ENS/INRIA/CNRS UMR 8548 Laboratoire.
Lecture 15: Transforms and Alignment CS4670/5670: Computer Vision Kavita Bala.
Transformations. Transformations Introduce standard transformations ◦ Rotation ◦ Translation ◦ Scaling ◦ Shear Derive homogeneous coordinate transformation.
 A transformation is an operation that moves or changes a geometric figure in some way to produce a new figure. The new figure is called the image. Another.
Computer Graphics Lecture 15 Fasih ur Rehman. Last Class Combining Transformations Affine versus Rigid body Transformations Homogenous Transformations.
Lecture 10 Geometric Transformations In 3D(Three- Dimensional)
Transformations What’s it all about?.
Do Now Find the value of every missing variable:.
2D Transformation.
Lecture 7 Geometric Transformations (Continued)
Homogeneous Coordinates (Projective Space)
Linear Algebra Review.
Lecture 08: Coordinate Transformation II
Geometric Transformations
Lecture 3: Camera Rotations and Homographies
Geometric Transformations
Viewing and Perspective Transformations
CV: Matching in 2D Matching 2D images to 2D images; Matching 2D images to 2D maps or 2D models; Matching 2D maps to 2D maps MSU CSE 803 Stockman.
Geometric Transformations
2D transformations (a.k.a. warping)
Geometric Transformations
Chapter 3: Solving Equations
Kashif Murtaza Lectures 15, 16 and 17
9.2 REFLECTIONS.
Geometrical Transformations
4.1: Dilations and Similar Triangles Tonight’s Homework: 4.1 Handout
Transformations.
Math Jeopardy Add Your Title Here.
Question 29.
Homework: Study for Unit Test & Complete Test Prep Packet Learning Target: I can demonstrate how transformations and angle relationships impact geometric.
Geometric Transformations
Image Stitching Linda Shapiro ECE/CSE 576.
Geometric Transformations
Translation in Homogeneous Coordinates
UNIT 1B REVIEW Triangle Theorems, dilations, congruence, Parallel lines cut by a transversal.
Image Stitching Linda Shapiro ECE P 596.
Geometric Transformations
Presentation transcript:

Geometric Transformations CSE P 576 Larry Zitnick

What are geometric transformations?

Translation

Translation and rotation

Scale

Similarity transformations Similarity transform (4 DoF) = translation + rotation + scale

Aspect ratio

Shear

Affine transformations Affine transform (6 DoF) = translation + rotation + scale + aspect ratio + shear

What is missing? Are there any other planar transformations? Canaletto

General affine We already used these How do we compute projective transformations?

Homogeneous coordinates One extra step:

Projective transformations a.k.a. Homographies “keystone” distortions

Finding the transformation How can we find the transformation between these images?

Finding the transformation Translation = 2 degrees of freedom Similarity = 4 degrees of freedom Affine = 6 degrees of freedom Homography = 8 degrees of freedom How many corresponding points do we need to solve?