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TODAY: Affine Structure from Motion IV

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TODAY: Affine Structure from Motion IV. Reading: Projective Structure ... Singular Value Decomposition. We can take. From uncalibrated to calibrated cameras ... – PowerPoint PPT presentation

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Title: TODAY: Affine Structure from Motion IV


1
TODAY Affine Structure from Motion IV
  • Affine Structure from Motion from two Views
  • Affine Epipolar Geometry
  • An Algebraic Approach
  • Affine Structure from Motion from two Views
  • An SVD-Based Approach Factorization
  • Computing Euclidean Upgrades
  • Reading Projective Structure from Motion
  • This file on feather.ai.uiuc.edu in
    pub/ponce/lect19.ppt.gz
  • Programming assignment on feather in
    pub/ponce/prog19.tex,
  • due next Thursday.


2
The Affine Epipolar Constraint
Note the epipolar lines are parallel.
3
Affine Epipolar Geometry
4
The Affine Fundamental Matrix
where
5
An Affine Trick..
Algebraic Scene Reconstruction Method
6
The Affine Structure of Affine Images
Suppose we observe a scene with m fixed cameras..
The set of all images of a fixed scene is a 3D
affine space!
7
has rank 4!
8
From Affine to Vectorial Structure
Idea pick one of the points (or their center of
mass) as the origin.
9
What if we could factorize D? (Tomasi and
Kanade, 1992)
Affine SFM is solved!
Singular Value Decomposition
We can take
10
From uncalibrated to calibrated cameras
Weak-perspective camera
Calibrated camera
Problem what is Q ?
Note Absolute scale cannot be recovered. The
Euclidean shape (defined up to an arbitrary
similitude) is recovered.
11
(No Transcript)
12
The Projective Structure-from-Motion Problem
Given m perspective images of n fixed points P
we can write
j
2mn equations in 11m3n unknowns
Overconstrained problem, that can be solved using
(non-linear) least squares!
13
The Projective Ambiguity of Projective SFM
When the intrinsic and extrinsic parameters are
unknown
and Q is an arbitrary non-singular 4x4 matrix.
Q is a projective transformation.
14
Projective Spaces (Semi-Formal) Definition
15
3
A Model of P( R )
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