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Online Structure and Motion for General Camera Models Gerald Schweighofer

Online Structure and Motion for General Camera Models Gerald Schweighofer. Motivation: Robots. Motivation: Robots. Motivation: User Guidance. Agenda. Robust Pose Online SaM SaM for GCM Online Robust. Experiments Feature Generation Simulations Real Sequenzes. Robust Pose.

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Online Structure and Motion for General Camera Models Gerald Schweighofer

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  1. Online Structure and Motion for General Camera ModelsGerald Schweighofer

  2. Motivation: Robots

  3. Motivation: Robots

  4. Motivation: User Guidance

  5. Agenda • Robust Pose • Online SaM • SaM for GCM • Online • Robust • Experiments • Feature Generation • Simulations • Real Sequenzes

  6. Robust Pose

  7. Robust Pose

  8. Robust Pose

  9. Robust Pose

  10. Robust Pose

  11. Robust Pose 4th order polynomial

  12. Results

  13. Results

  14. Results

  15. Online SaM for GCM General Camera Model Object space cost Globally Convergent SaM SaM as an optimization problem closed form solutions for structure and camera position Proven convergence Online/Realtime SaM constant amount of CPU time / frame Robustness

  16. v c Camera • An example • Stereo Setup General Camera Model • Measurements are rays of light (c,v) • c ... a point • v ... a vector

  17. Object Space Cost for GCM

  18. Structure & Motion

  19. Closed form Solution for Structure

  20. Closed form Solution for Camera translation

  21. closed form structure closed form translation Iterative Rotation estimation • Solve one iteration using SVD or quaternions • Results in a globally convergent algorithm.

  22. Convergence

  23. pre-calculate Online/Realtime SaM • Assumption: old Frames stay constant.

  24. pre-calculate Online/Realtime SaM • Assumption: old Frames stay constant.

  25. Robustness

  26. Robustness

  27. Experiments Simulation Natural Landmarks Artificial Landmarks House Sequence Bridging Marker less Environment Laboratory Sequence

  28. Simulation Object: Cylinder 70 random points diameter: 1 meter height: 1 meter Motion: Circle diameter: 6 meter 100 frames / every 3.6° 0.5 Pixel Gaussian noise

  29. Simulation 10 ms := 100 Frames / sec for SaM

  30. Simulation

  31. Artficial Landmarks • ARToolKit Marker

  32. Natural Landmark Tracking

  33. House Sequence

  34. House Sequence

  35. House Sequence

  36. House Sequence

  37. Bridging Marker less Environments

  38. Automatic Generation of Scene Description

  39. Automatic Generation of Scene Description

  40. Automatic Generation of Scene Description standard deviation: 0.48 %

  41. Conclusion • Robust Pose • Structure and Motion for GCM • General Camera Model • Online Algorithm • Robust to Outliers • Experiments

  42. Institute of Electrical Measurement and Measurement Signal Processing Online SaM for GCM RIGOROSUM 03.07.2008 Gerald Schweighofer Publications

  43. Natural Landmark Tracking

  44. Simulation

  45. Time Complexity

  46. Frames to optimize affected Points classical algorithms proposed algorithms Time Complexity Points Frames

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