The Trifocal TensorClass 17

Multiple View GeometryComp 290-089Marc Pollefeys

Multiple View Geometry course schedule(subject to change)

Jan. 7, 9 Intro & motivation Projective 2D Geometry

Jan. 14, 16

(no class) Projective 2D Geometry

Jan. 21, 23

Projective 3D Geometry (no class)

Jan. 28, 30

Parameter Estimation Parameter Estimation

Feb. 4, 6 Algorithm Evaluation Camera Models

Feb. 11, 13

Camera Calibration Single View Geometry

Feb. 18, 20

Epipolar Geometry 3D reconstruction

Feb. 25, 27

Fund. Matrix Comp. Fund. Matrix Comp.

Mar. 4, 6 Rect. & Structure Comp.

Planes & Homographies

Mar. 18, 20

Trifocal Tensor Three View Reconstruction

Mar. 25, 27

Multiple View Geometry

MultipleView Reconstruction

Apr. 1, 3 Bundle adjustment Papers

Apr. 8, 10

Auto-Calibration Papers

Apr. 15, 17

Dynamic SfM Papers

Apr. 22, 24

Cheirality Project Demos

Scene planes and homographies

plane induces homography between two views

0HFFH TT

H'eF

ve'Fe'H

Hee'

6-point algorithm

6655 Hx'xHx'xe'

x1,x2,x3,x4 in plane, x5,x6 out of plane

Compute H from x1,x2,x3,x4

He'F

Three-view geometry

The trifocal tensor

Three back-projected lines have to meet in a single line

Incidence relation provides constraint on lines

Let us derive the corresponding algebraic constraint…

Notations

iii lll

0]|[IP ]a|[AP' 4 ]b|[BP" 4

0

llPπ T

l'al'Al'P'π' T

4

TT

l"bl"Bl"P"π" T

4

TT

Incidence

iii lll

0

llPπ T

l'al'Al'P'π' T

4

TT

l"bl"Bl"P"π" T

4

TT

2rank is ]π"π'[πM ,,

e.g. is part of bundle formed by ’ and ”

l"bl'a0l"Bl'Al]m,m,m[M T

4T

4

TT

321

321 βmαmm "lβb'lαa0 T4

T4

'la T4k

"lb T

4k "lB'la'lA"lbl TT4

TT4

Incidence relation

"lBa'l'lAb"l"lB'la'lA"lbl T4

TT4

TTT4

TT4

"lba'l'lab"l T4

TT4

Tiiil "lba'l"lba'l T

4TT

4T

ii

T4

T4 babaT iii

"lT'l Tiil

The Trifocal Tensor

"lT,T,T'll 321TT

Trifocal Tensor = {T1,T2,T3}

"lT'l,"lT'l,"lT'l 3T

2T

1T

Only depends on image coordinates and is thus independent of 3D projective basis

"lT'll' TTi 'lT"ll" TT

iAlso and but no simple relation

General expression not as simple asT

4T

4 babaT iii

DOF T: 3x3x3=27 elements, 26 up to scale 3-view relations: 11x3-15=18 dof

8(=26-18) independent algebraic constraints on T(compare to 1 for F, i.e. rank-2)

l"'ll

Homographies induced by a plane

Line-line-line relation

Eliminate scale factor:

(up to scale)

Point-line-line relation

Point-line-point relation

note: valid for any line through x”, e.g. l”=[x”]xx”arbitrary

Point-point-point relation

note: valid for any line through x’, e.g. l’=[x’]xx’arbitrary

Overview incidence relations

Non-incident configurationincidence in image does not guarantee incidence in space

Epipolar lines

if l’ is epipolar line, then satisfied for arbitrary l”

inversely,

epipolar lines are right and left null-space of

Epipoles

With points

becomes respectively

Epipoles are intersection of right resp. left null-space of

(e=P’C and e”=P”C)

Extracting F

21Fgood choice for l” is e” (V3

Te”=0)

Computing P,P‘,P“

?

ok, but not

specifically, (no derivation)

matrix notation is impractical

Use tensor notation instead

0 jkikj

i Tllx

jkiT

Definition affine tensor

• Collection of numbers, related to coordinate choice, indexed by one or more indices

• Valency = (n+m)• Indices can be any value between 1

and the dimension of space (d(n+m)

coefficients)

Conventions

0iijbA

Einstein’s summation:(once above, once below)

ii

iji

ij bAbA

Index rule: jbA iij ,0

More on tensors

• Transformations

iji

j xAx

ijji llA

(covariant)

(contravariant)

Some special tensors

• Kronecker delta

• Levi-Cevita epsilon

(valency 2 tensor)

(valency 3 tensor)

Trilinearities

Transfer: epipolar transfer

Transfer: trifocal transfer

Avoid l’=epipolar line

Transfer: trifocal transferpoint transfer

line transfer

degenerate when known lines are corresponding epipolar lines

Image warping using T(1,2,N)(Avidan and Shashua `97)

Next class: Computing Three-View Geometry

building block for structure and motion computation