Vision-based Registration for AR

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Vision-based Registration for AR Presented by Diem Vu Nov 20, 2003

description

Vision-based Registration for AR. Presented by Diem Vu Nov 20, 2003. Markerless Tracking using Planar Structure in the Scene . G. Simon, A.W. Fitzgibbon and A. Zisserman, 2000. Calibration-Free Augmented Reality . K.N Kutulakos and J.R. Vallino , 1998. Planar-surface tracking. - PowerPoint PPT Presentation

Transcript of Vision-based Registration for AR

Page 1: Vision-based Registration for AR

Vision-based Registration for AR

Presented by Diem VuNov 20, 2003

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Markerless Tracking using Planar Structure in the Scene. G. Simon, A.W. Fitzgibbon and A. Zisserman, 2000.

Calibration-Free Augmented Reality. K.N Kutulakos and J.R. Vallino, 1998.

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Planar-surface tracking.Camera position can be recovered from

planar homography.Planar structure is common in almost all

scenarios.

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y

x

z

Hw

World to image homography

jiH

Image to image homography

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World to image homographyConsider our tracking plane is the plane

Z=0

y

x

z

Hw

1H

1w YX

yx

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Projection matrix

trrr 321KP

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trrrr 2121 KP

Projection matrix

1yx

10YX

y

x

z

P

10

K1

2

YX

yx

trrr 31

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trrrr 2121 KP

Projection matrix

1yx

10YX

y

x

z

P

1K

1YX

yx

trr 21

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If K and Hw are known, then r1, r2 and t can be recovered, thus P.

Question: How to compute Hw?Direct.Indirect.

trr 21KHw

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Direct measurement of Hw

Select 4 points {xk} on a rectangle in the scene.

Compute H which maps the unit square to {xk}.

(0,0)

(0,1) (1,1)

((1,0))

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Direct measurement of Hw

Select 4 points {xk} on a rectangle in the scene.

Compute H which maps the unit square to {xk}.

s,1)(1,diagH H w

trr 21 s HK -1

s,1)(1,diagK H trr 21

Compute Hw=Hdiag(1,1/s,1)

(0,0)

(0,s) (1,s)

((1,0))

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Indirect measurement of Hw

iwH

jiH

? H jw

y

x

z

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Indirect measurement of Hw

iwH

jiH

iw

ji

jw HHH

y

x

z

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Algorithm summaryCompute (direct measure).For each frame i, compute frame to frame

homography (RANSAC)Compute by:

0wH

1-iw

i1-i

iw HHH

i1-iH

iwH

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Other …Using only 2 points in direct method ??Matching the frame i with frame 0 in order

to reduce error.Estimate intrinsic parameters K Hand-off mechanism.

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Possible problems?Homography is only up-to-scale?Plain surface (no texture) or moving

objects in the foreground ?Depth order, occlusion ?Speed ?

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Affine virtual object representation

Represent virtual objects so that their projection can be computed as a linear combination of the projection of the fiducial points.

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Project a point from its affine coordinates

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Compute affine coordinates from projection along two viewing

direction

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Algorithm Setup the affine basis

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Algorithm Setup the affine basis Locate the object in 2 frames.

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Algorithm Setup the affine basis Locate the object in 2 frames. Compute the affine coordinates

for each point.

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Algorithm Setup the affine basis Locate the object in 2 frames. Compute the affine coordinates

for each point. Compute projection of the object

and render the object in each frame.

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Camera viewing direction and are the first and second row of

2x3.The camera viewing direction expressed in

the coordinate frame of the affine basis points: =

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Depth order

w is the z-value of point p (x,y,z).

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AdvantagesNo need any metric information.Able to use with the existing hardware to

accelerate graphics operations.Can be used to improve tracking.

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LimitationAffine constraints.Lost of metric information.