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Improving and Filtering Laser Data for Extrinsic Laser Range Finder/Camera Calibration

Improving and Filtering Laser Data for Extrinsic Laser Range Finder/Camera Calibration. Sukhum Sattaratnamai Advisor: Dr.Nattee Niparnan. Outline. Introduction Objective Calibration Process Our Work Improving Laser Data Automate Data Collection Conclusion. LRF-Camera System. α.

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Improving and Filtering Laser Data for Extrinsic Laser Range Finder/Camera Calibration

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  1. Improving and Filtering Laser Data for Extrinsic Laser Range Finder/Camera Calibration SukhumSattaratnamai Advisor: Dr.NatteeNiparnan

  2. Outline • Introduction • Objective • Calibration Process • Our Work • Improving Laser Data • Automate Data Collection • Conclusion

  3. LRF-Camera System α

  4. LRF-Camera System α

  5. LRF-Camera Calibration • Problem Definition • Find the transformation [R |t ] of the camera w.r.t. LRF

  6. Objective Proposal • Improving Laser Data • Filtering Laser Data Related Work • LRF-Camera Calibration Calibration of a multi-sensor system laser rangefinder/camera, 1995 • More Accurate Result Extrinsic calibration of a camera and laser range finder (improves camera calibration), 2004 • Easier Process An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features, 2007

  7. Objective Proposal • Improving Laser Data • Filtering Laser Data Thesis • Improving Laser Data • On Improving Laser Data for Extrinsic LRF/Camera Calibration, 2011 • Automated Process • Automated Calibration Data Collection in LRF/Camera Calibration with Online Feedback, 2012 Related Work • LRF-Camera Calibration Calibration of a multi-sensor system laser rangefinder/camera, 1995 • More Accurate Result Extrinsic calibration of a camera and laser range finder (improves camera calibration), 2004 • Easier Process An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features, 2007

  8. Objective Proposal • Improving Laser Data • Filtering Laser Data Thesis • Improving Laser Data • On Improving Laser Data for Extrinsic LRF/Camera Calibration, 2011 • Automated Process • Automated Calibration Data Collection in LRF/Camera Calibration with Online Feedback, 2012 Related Work • LRF-Camera Calibration Calibration of a multi-sensor system laser rangefinder/camera, 1995 • More Accurate Result Extrinsic calibration of a camera and laser range finder (improves camera calibration), 2004 • Easier Process An algorithm for extrinsic parameters calibration of a camera and a laser range finder using line features, 2007

  9. Calibration Process Start Data Collection Feature Detection Optimization Check Result End

  10. Calibration Process • Data Collection

  11. Calibration Process • Feature Detection

  12. Calibration Process • Projection Error

  13. Calibration Process • Optimization • Simulated Annealing : Find global minimum • Levenberg-Marquardt : Find local minimum

  14. Calibration Process • Result • Project laser data onto an image

  15. Our Work • Improving Laser Data • Automatic Data Collection

  16. Improving Laser Data • Angular Error • =>

  17. Simulation • Angular Error • =>

  18. Simulation • Laser Data Improvement

  19. Experiment • Laser Range Finder • Camera

  20. Experiment • Laser Data Improvement

  21. Experiment • Number of Data

  22. Improving Laser Data • Lower bound

  23. Simulation • Lower Bound

  24. Automate Data Collection Start Data Collection 5 นาที 5 นาที 2 นาที Feature Detection 30 นาที 30 นาที Optimization 1 วินาที Check Result End

  25. Automate Data Collection • Feature Detection

  26. Automate Data Collection • False Detection => Tracking

  27. Experiment • Data Distribution

  28. Automate Data Collection • Working Space Covering • Data Bin (x, y, angle)

  29. Automate Data Collection • Moving Calibration Object => Velocity Metric

  30. Experiment • Velocity & Accuracy

  31. Experiment • Accuracy & Time

  32. Experiment

  33. Automate Data Collection • User Interface • Data Quality Metric • Tracking, Velocity • Data Distribution • Data Bins, Current Bin, Target Bin

  34. Automate Data Collection • User Interface • Result • Laser Data Projection • Acknowledge & Warning Sound • Data Acquire, Tracking Lost

  35. Conclusion • Improved calibration method • Reduce projection error to 50 percent • Automatic data collection process • Faster and easier for all user

  36. Thank you

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