A flexible camera calibration tool for 3d capture
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A Flexible Camera Calibration Tool for 3D Capture. Lei Wang Media and Machine Lab Advisor: Cindy Grimm. 3D Capture. Data Acquisition Camera Calibration Shape Integration Texture Synthesis Shape Texture Integration. Camera Calibration. Camera Model Global Approach Requirement

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A Flexible Camera Calibration Tool for 3D Capture

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A flexible camera calibration tool for 3d capture

A Flexible Camera Calibration Tool for 3D Capture

Lei Wang

Media and Machine Lab

Advisor: Cindy Grimm


3d capture

3D Capture

  • Data Acquisition

  • Camera Calibration

  • Shape Integration

  • Texture Synthesis

  • Shape Texture Integration


Camera calibration

Camera Calibration

  • Camera Model

  • Global Approach

  • Requirement

  • Previous Work

  • Our Approach

  • Conclusion


Pinhole camera model

Pinhole Camera Model


Denotation

Denotation

  • 2D Point: m = [u, v, 1]T

  • 3D Point: M = [X, Y, Z]T

  • 2D – 3D: s m =A [R T] M

  • A: Intrinsic Parameters

  • [R T]: Extrinsic Parameters


Equation

Equation


Global approach

Global Approach

  • Take pictures

  • Detect the pattern

  • Extract the feature

  • Solve for intrinsic parameters (one for all)

  • Solve for extrinsic parameters (one for each)


Requirement

Requirement

  • Automated

  • Hemisphere Visibility

  • Not occlude the object

  • Robust on lighting conditions

  • Easy to build

  • Easy to detect


Planar pattern

Planar Pattern

  • Checkerboard

    Tsai’s Algorithm

    Zhang’s Algorithm

  • Geometry Pattern

  • Concentric Circle

    Jun-Sik Kim, Ho-Won Kim and In-So Kweon’s Algorithm


Improved planar pattern

Improved Planar Pattern

  • Move the pattern by hand

  • Place two or more patterns on different plane

  • Place mirrors and use the additional reflected pattern


Our approach outline

Our Approach – Outline

  • Design Calibrating Pattern

  • Build Calibrating Pattern

  • Feature Extraction

  • Feature Mapping – Gradient Search

  • Test


Cone with basic 3d shapes

Cone with basic 3D shapes

  • Automated

  • Hemisphere visibility

  • Not occlude the object: part of the shape is enough for relying on a group of points

  • Robust for lighting conditions: color ratio

  • Easy to detect: color boundary

  • Easy to build: build from a planar pattern


Basic shapes

Basic Shapes

  • Circles

  • Ellipses

  • Lines

  • Points


Stable color ratio

Stable Color Ratio


Parameterized representation

Parameterized Representation

  • Line

  • Circle

  • Ellipse


The printable planar pattern

The Printable Planar Pattern

  • 3D equation, 2D print translation

  • Physical tips


Boundary detection

Boundary Detection

  • Color ratio

  • Grouping


Ellipses

Ellipses

  • Ellipse detection

  • Ellipse fitting


Lines

Lines

  • Line detection

  • Line fitting


Points

Points

  • Direct Point detection

  • Intersection of two shapes

    - Line-line intersection

    - Line-circle intersection

    - Line-ellipse intersection

    - Ellipse-ellipse intersection(not recommend)


Solve for intrinsic parameters

Solve for Intrinsic Parameters

  • Checkerboard

  • OpenCV

  • Flagged Checkerboard


Extrinsic by points

Extrinsic by Points

  • Use Points

  • Linear

  • Limitation

    - Hard to label

    - Inaccurate

    - Six points rules not guaranteed


Extrinsic by shapes

Extrinsic by Shapes

  • Other Shape

  • Non-Linear

  • Gradient-decent Search

    - Cost Function

    - Initial Guess

    - Step Choose

    - Stop Condition


Extrinsic by lines

Extrinsic by Lines

  • Cost Function

  • Initial Guess

  • Step Choose

  • Stop Condition


Extrinsic by conics

Extrinsic by Conics

  • Cost Function

  • Initial Guess

  • Step Choose

  • Stop Condition


General extrinsic

General Extrinsic

  • General Case

  • Use Combination Pattern


Talk

Test


Conclusion

Conclusion

  • Easiness

  • Efficiency


Conclusion1

Conclusion

  • Accuracy


References

References


Questions

Questions?


Thank you

Thank You


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