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oint Depth and Color Camera alibration with istortion Correction

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oint Depth and Color Camera alibration with istortion Correction. Daniel Herrera C., Juho Kannala, Janne Heikkilä Center for Machine Vision Research, University of Oulu, Finland. Abstract. Problem. Depth discontinuities are noisy for depth calibration. - PowerPoint PPT Presentation
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oint Depth and Color Camera alibration with istortion Correction We present an algorithm that simultaneously calibrates two color cameras, a depth camera, and the relative pose between them. Characteristics: Accurate, practical, and applicable to a wide range of sensors. Does not use depth discontinuities. Applied to a Kinect device. Requirements: Planar surface imaged from several poses. Rigidly attached depth and color cameras. Depth discontinuities are noisy for depth calibration. How to calibrate a color and a depth camera jointly? Kinect’s color camera has low resolution. How to learn a distortion model for the Kinect? Abstract Problem Results Constraints Kinect distortion correction Daniel Herrera C., Juho Kannala, Janne Heikkilä Center for Machine Vision Research, University of Oulu, Finland Color camera External camera Depth camera Checkerboard pattern is known. Detected vs. reprojected corners Points are known to be coplanar. Measured vs. predicted disparity : = ^ 2 2 + ^ 2 2 + ( ^ ) 2 2 Non-linear minimization (LM) All cameras have geometric distortion: Kinect also has a fixed error pattern that vanishes at long distance. 0.5m 1.2m Decouple fixed pattern from the distance dependent component: ( , , ) = ( , ) ( ) 300 400 500 600 700 800 900 1000 1 0 1 2 3 4 5 M e a su re d d isp a rity (k d u) M e d ia n o f n o rm a lize d e rror F itte d exponential is constant is exponential 0 0.5 1 1.5 2 2.5 3 3.5 4 0 5 10 15 20 25 30 35 D ep th (m) E rro r std . d e v. (m m) D e p th u ncerta in ty O u r m e th od M a n u fa ctu re r c a libration Simulated, d = 0.6 = + ( , ) exp ( 0 1 ) Accurate, practical, and flexible algorithm. Adaptable to different depth sensors. Better Kinect accuracy than manufacturer (half the error at 1m). Open source toolbox: http://http://www.ee.oulu.fi/ ~dherrera/kinect/ Rigidly attached Constraints of one camera affect the others! Reference Herrera C., D., Kannala, J., Heikkilä, J., “Joint depth and color camera calibration with distortion correction”, TPAMI, in press 2012.
Transcript
Page 1: oint  Depth and Color Camera     alibration with       istortion  Correction

oint Depth and Color Camera alibration with istortion Correction

We present an algorithm that simultaneously calibrates two color cameras, a depth camera, and the relative pose between them.

Characteristics: • Accurate, practical, and applicable to a wide range of

sensors. • Does not use depth discontinuities.• Applied to a Kinect device.

Requirements: • Planar surface imaged from several poses.• Rigidly attached depth and color cameras.

• Depth discontinuities are noisy for depth calibration.• How to calibrate a color and a depth camera jointly?• Kinect’s color camera has low resolution.• How to learn a distortion model for the Kinect?

Abstract Problem

Results

Constraints

Kinect distortion correction

Daniel Herrera C., Juho Kannala, Janne HeikkiläCenter for Machine Vision Research, University of Oulu, Finland

Color camera External camera Depth camera

Checkerboard pattern is known.Detected vs. reprojected corners

Points are known to be coplanar.Measured vs. predicted disparity :

𝐶=∑‖�̂� 𝑐−𝒑𝑐‖

2

𝜎 𝑐2 +

∑‖�̂� 𝑒−𝒑𝑒‖2

𝜎 𝑒2 +

∑ ( �̂�−𝑑)2

𝜎𝑑2

Non-linear minimization (LM)

All cameras have geometric distortion:

Kinect also has a fixed error pattern that vanishes at long distance.

0.5m 1.2m

Decouple fixed pattern from the distance dependent component: 𝐸𝑟𝑟𝑜𝑟 (𝑢 ,𝑣 ,𝑑 )= 𝑓 (𝑢 ,𝑣 ) ∙𝑔 (𝑑 )

300 400 500 600 700 800 900 1000 1

0

1

2

3

4

5

M easured disparity (kdu)

M edian o f normalized errorF itted exponentia l

is constant is exponential

0 0.5 1 1.5 2 2.5 3 3.5 40

5

10

15

20

25

30

35

D epth (m)

Erro

r std.

dev.

(mm)

D epth uncerta inty

O ur methodM anufacturer ca libra tionS imulated, d=0.6

𝑑𝑘=𝑑+𝐷 (𝑢 ,𝑣 ) ∙exp (𝛼0−𝛼1𝑑 )

• Accurate, practical, and flexible algorithm.

• Adaptable to different depth sensors.

• Better Kinect accuracy than manufacturer (half the error at 1m).

• Open source toolbox:http://http://www.ee.oulu.fi/~dherrera/kinect/

Rigidly attached

Constraints of one camera affect the others!

ReferenceHerrera C., D., Kannala, J., Heikkilä, J., “Joint depth and color camera calibration with distortion correction”, TPAMI, in press 2012.

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