Title: Geometry
1Geometry Tensors
2Outline
- N-Views and Trifocal Tensor
- Tensor Notation
- Multiview Constraints
- 2-view
- 3-view
- 4-view
3Geometry of N views
- Often more views are available
- Can we use this in matching ?
- Answer yes, up to 4 views
4Trinocular Epipolar Constraints
These constraints are not independent!
5Trinocular Epipolar Constraints Transfer
Given p and p , p can be computed as the
solution of linear equations.
1
2
3
6Tensor Notation
7Tensor Notation
- Different way of writing vectors, matrices
- In general tensors
- row and column replaced by contravariant and
covariant indices - Index name indicates the space
- Geek Cool Einstein Summation
8Tensor Notation
9Join cross product !
- Join of two lines is a point
- Join of two points is a line
10Cross Product Magic
11Homography
Maps points from image B to image A
image B
image A
xB
xA
123D Projective Space
13Projective Camera
xa
3D space a
Mixed 3D to 2D tensor
image A
14Multiview Tensors
152 Views Fundamental Matrix
F maps points in view A to lines in view B gt
Tensor with two covariant indices FAB
2 Cameras have 22 DOF, 15 DOF ambiguity 7 DOF
in Fundamental Matrix FAB
164 Views Quadrifocal tensors
- Constraint on 4 lines gt 4-valent contravariant
tensor QABCD
17Quadrifocal DOF
- 4 Cameras 44 parameters
- 15 DOF ambiguity
- Total DOF 44-1529
- Q Tensor 3333 81 entries
- Q must have 81-29 52 algebraic constraints
18Trifocal tensors
- Relate three views
- Depends on covariant view
- Indices suggest 3-view constraints
19line-line-line transfer
- Two lines in views B and C determine line in view
A - Obvious !
20point-line-point
- line in B -gt induces plane homography from C to A
21point-point-point
22Whats in a Tensor ?
23What is Quadrifocal Tensor ?
- Take 3 planes, calculate x
24Whats an F Matrix ?
xa
xB
xA
PA
PB
25Important to Remember
- All tensors encapsulate incidence constraints
- Hence invariant to projective transformations
- Valency suggests derived constraints