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Projective Geometry and Geometric Invariance in Computer Vision

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### Projective Geometry and Geometric Invariance in Computer Vision

Babak N. Araabi

Electrical and Computer Eng. Dept.

University of Tehran

Workshop on image and video processing

Mordad 13, 1382

Do parallel lines intersect? Vision

Perhaps!

Fifth Euclid's postulate Vision

- For any line L and a point P not on L, there exists a unique line that is parallel to L (never meets L) and passes through P.
- At first glance it would seem that the parallel postulate ought to be a theorem deducible from the other more basic postulates.
- For centuries mathematicians tried to prove it.
- Eventually it was discovered that the parallel postulate is logically independent of the other postulates, and you get a perfectly consistent system even if you assume that parallel postulate is false.

Alternative postulates Vision

- Non-Euclidean geometry; though not a typical one
- The projective axiom: Any two lines intersect (in exactly one point).
- More intuitive approach:Take each line of ordinary Euclidean geometry and add to it one extra object called a point at infinity. In addition, the collection of all the extra objects together is also called a line in projective plane (called the line at infinity).

Why Projective Geometry? Vision

- A more appropriate framework when dealing with projection related issues.
- Perspective projection: Photophraphy Human vision
- Perspective projection is a non-linear mapping with Euclidean coordinates, but a linear mapping with homogeneous coordinates

Overview Vision

- 2D Projective Geometry
- 3D Projective Geometry
- Application: Invariant matching
- From 2D images to 3D space

Projective 2D Geometry Vision

Homogeneous representation of points Vision

on

if and only if

Homogeneous coordinates

but only 2DOF

Inhomogeneous coordinates

Homogeneous coordinatesHomogeneous representation of lines

equivalence class of vectors, any vector is representative

Set of all equivalence classes in R3(0,0,0)T forms P2

The point x lies on the line l if and only if xTl=lTx=0

Line joining two points Vision

The line through two points and is

Points from lines and vice-versaIntersections of lines

The intersection of two lines and is

Example

tangent vector Vision

normal direction

Example

Ideal points

Line at infinity

Ideal points and the line at infinityIntersections of parallel lines

Note that in P2 there is no distinction

between ideal points and others

A model for the projective plane Vision

exactly one line through two points

exaclty one point at intersection of two lines

Duality principle: Vision

To any theorem of 2-dimensional projective geometry there corresponds a dual theorem, which may be derived by interchanging the role of points and lines in the original theorem.

For instance, the basic axiom that "for any two points, there is a unique line that intersects both those points", when turned around, becomes "for any two lines, there is a unique point that intersects (i.e., lies on) both those lines"

DualityIn projective geometry, points and lines are completely interchangeable!

or Visionhomogenized

or in matrix form

with

ConicsCurve described by 2nd-degree equation in the plane

5DOF:

6 parameters

or Vision

stacking constraints yields

Five points define a conicFor each point the conic passes through

Theorem: Vision

A mapping h:P2P2is a projectivity if and only if there exist a non-singular 3x3 matrixH such that for any point in P2 reprented by a vector x it is true that h(x)=Hx

Definition: Projective transformation

or

8DOF

Projective transformationsDefinition:

A projectivity is an invertible mapping h from P2 to itself such that three points x1,x2,x3lie on the same line if and only if h(x1),h(x2),h(x3) do.

projectivity=collineation=projective transformation=homography

Removing projective distortion Vision

select four points in a plane with know coordinates

(linear in hij)

(2 constraints/point, 8DOF 4 points needed)

Remark: no calibration at all necessary,

better ways to compute

More examples Vision

Transformation for conics Vision

Transformation of lines and conicsFor a point transformation

Transformation for lines

A hierarchy of transformations Vision

Projective linear group

Affine group (last row (0,0,1))

Euclidean group (upper left 2x2 orthogonal)

Oriented Euclidean group (upper left 2x2 det 1)

Alternative, characterize transformation in terms of elements or quantities that are preserved or invariant

e.g. Euclidean transformations leave distances unchanged

orientation preserving: Vision

orientation reversing:

Class I: Isometries(iso=same, metric=measure)

3DOF (1 rotation, 2 translation)

special cases: pure rotation, pure translation

Invariants: length, angle, area

Class II: Similarities Vision

(isometry + scale)

4DOF (1 scale, 1 rotation, 2 translation)

also know as equi-form (shape preserving)

metric structure = structure up to similarity (in literature)

Invariants: ratios of length, angle, ratios of areas, parallel lines

Class III: Affine transformations Vision

6DOF (2 scale, 2 rotation, 2 translation)

non-isotropic scaling! (2DOF: scale ratio and orientation)

Invariants: parallel lines, ratios of parallel lengths,

ratios of areas

Class VI: Projective transformations Vision

8DOF (2 scale, 2 rotation, 2 translation, 2 line at infinity)

Action non-homogeneous over the plane

Invariants: cross-ratio of four points on a line

ratio of ratio of area

Action of affinities and projectivities Visionon line at infinity

Line at infinity stays at infinity,

but points move along line

Line at infinity becomes finite,

allows to observe vanishing points, horizon,

Decomposition of projective transformations Vision

decomposition unique (if chosen s>0)

upper-triangular,

Example:

Overview transformations Vision

Concurrency, collinearity, order of contact (intersection, tangency, inflection, etc.), cross ratio

Projective

8dof

Parallellism, ratio of areas, ratio of lengths on parallel lines (e.g midpoints), linear combinations of vectors (centroids).

The line at infinity l∞

Affine

6dof

Ratios of lengths, angles.

The circular points I,J

Similarity

4dof

Euclidean

3dof

lengths, areas.

Number of invariants? Vision

The number of functional invariants is equal to, or greater than, the number of degrees of freedom of the configuration less the number of degrees of freedom of the transformation

e.g. configuration of 4 points in general position has 8 dof (2/pt) and so 4 similarity, 2 affinity and zero projective invariants

Projective geometry of 1D Vision

3DOF (2x2-1)

The cross ratio

Invariant under projective transformations

Projective 3D Geometry Vision

Projective 3D Geometry Vision

- Points, lines, planes and quadrics
- Transformations
- П∞, ω∞and Ω ∞

Points, lines and planes Vision

Hierarchy of transformations Vision

Projective

15dof

Intersection and tangency

Parallellism of planes,

Volume ratios, centroids,

The plane at infinity π∞

Affine

12dof

Similarity

7dof

The absolute conic Ω∞

Euclidean

6dof

Volume

The plane at infinity Vision

The plane at infinity π is a fixed plane under a projective transformation H iff H is an affinity

- canonical position
- contains directions
- two planes are parallel line of intersection in π∞
- line // line (or plane) point of intersection in π∞

Application in VisionInvariant Matching

How to define an invariant Vision2D identifier patch on an image?

- Consider a multilateral identifier patch.
- Lines are invariant under the perspective projection.

- 3 (4) reference points are required to obtain an affine (projective) invariant representation of the multilateral identifier patch.
- Weak-perspective/perspective camera models.

R Vision3

R2

R1

X

A

Affine invariant representation of a planar point- Three reference points.
- Ratio of areas are invariant.
- X at intersection of R1R2 and R3A.
- (r1,r2) invariants defined by:

R Vision3

R2

R1

X

R4

A

Projective invariant representation of a planar point- Four reference points.
- Ratio of ratio of areas are invariant.
- X at intersection of R1R4 and R3A.
- (r1,r2) invariants defined by:

R Vision3

A

R2

R1

Affine invariant parallelogram:Three reference pointsSelect A to make a parallelogram with three reference points R1, R2, and R3

R Vision3

A

B2

B1

R2

R1

Affine invariant parallelogram:Construction of identifier patch (1)Select B1 on R2R3

R Vision3

B2

C2

C1

B1

R1

Affine invariant parallelogram:Construction of identifier patch (2)Select C1 on B1R1

R Vision3

D2

C2

C1

D1

R1

Affine invariant parallelogram:Construction of identifier patch (3)Select D1 on C1R1

From 2D to 3D Vision

p Vision1

p3

p2

q1

p4

q2

q3

q4

q5

Focal point

p5

q6

p6

Image plane

Perspective projection- Perspective projection of 6 (feature) points from 3D world (dorsal fin) to 2D image:
pi=(xi,yi,zi) qi=(ui,vi) i=1,…,6

3D and 2D Projective Invariants Vision

- I1, I2, and I3 are 3D projective invariants (under PGL(4)).
- i1, i2, i3, and i4 are 2D projective invariants (under PGL(3)).
- There is no general case view-invariant.
- 2D invariants impose constraints (in the form of polynomial relations) on 3D invariants.
* PGL(n): Projective General Linear group of order n.

P Vision4

P1

P2

P4

P3

P3

P1

P2

P1

P3

P2

P4

Invariants of point sets:Algebraic invariantsTransfer images to a reference frame.

A unique projective/affine transformation between any two sets of 4/3 corresponding points.

Coordinate of any other point is invariant in the reference frame.

Reference frame

Globalinvariant

Invariant Relations Vision

- Constraints (here for 6 points) typically have the following form
- This is a fundamental object-image relation for six arbitrary 3D points and their 2D perspective projections.
- Therefore having at least 6 points in correspondence over a number of images, 3D invariants (Ik’s) can be estimated and invariant relations can be used as geometric invariant models.

n 6 points3n-15 Ik’s2n-8 ik’s2n-11 relations

or

Where are we going? Vision

Thanks for your VisionAttention!

Questions?

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