A Flexible Camera Calibration Tool for 3D Capture - PowerPoint PPT Presentation

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A Flexible Camera Calibration Tool for 3D Capture

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  1. A Flexible Camera Calibration Tool for 3D Capture Lei Wang Media and Machine Lab Advisor: Cindy Grimm

  2. 3D Capture • Data Acquisition • Camera Calibration • Shape Integration • Texture Synthesis • Shape Texture Integration

  3. Camera Calibration • Camera Model • Global Approach • Requirement • Previous Work • Our Approach • Conclusion

  4. Pinhole Camera Model

  5. 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

  6. Equation

  7. Global Approach • Take pictures • Detect the pattern • Extract the feature • Solve for intrinsic parameters (one for all) • Solve for extrinsic parameters (one for each)

  8. Requirement • Automated • Hemisphere Visibility • Not occlude the object • Robust on lighting conditions • Easy to build • Easy to detect

  9. 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

  10. Improved Planar Pattern • Move the pattern by hand • Place two or more patterns on different plane • Place mirrors and use the additional reflected pattern

  11. Our Approach – Outline • Design Calibrating Pattern • Build Calibrating Pattern • Feature Extraction • Feature Mapping – Gradient Search • Test

  12. 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

  13. Basic Shapes • Circles • Ellipses • Lines • Points

  14. Stable Color Ratio

  15. Parameterized Representation • Line • Circle • Ellipse

  16. The Printable Planar Pattern • 3D equation, 2D print translation • Physical tips

  17. Boundary Detection • Color ratio • Grouping

  18. Ellipses • Ellipse detection • Ellipse fitting

  19. Lines • Line detection • Line fitting

  20. Points • Direct Point detection • Intersection of two shapes - Line-line intersection - Line-circle intersection - Line-ellipse intersection - Ellipse-ellipse intersection(not recommend)

  21. Solve for Intrinsic Parameters • Checkerboard • OpenCV • Flagged Checkerboard

  22. Extrinsic by Points • Use Points • Linear • Limitation - Hard to label - Inaccurate - Six points rules not guaranteed

  23. Extrinsic by Shapes • Other Shape • Non-Linear • Gradient-decent Search - Cost Function - Initial Guess - Step Choose - Stop Condition

  24. Extrinsic by Lines • Cost Function • Initial Guess • Step Choose • Stop Condition

  25. Extrinsic by Conics • Cost Function • Initial Guess • Step Choose • Stop Condition

  26. General Extrinsic • General Case • Use Combination Pattern

  27. Test

  28. Conclusion • Easiness • Efficiency

  29. Conclusion • Accuracy

  30. References

  31. Questions?

  32. Thank You