Markless registration for scans of free form objects


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Markless registration for scans of free form objects

  1. 1. MARKLESS REGISTRATION FOR SCANS OF FREE-FORM OBJECTS <br />Laboratory of photogrammetry of NTUAArtemis Valanis, PhD StudentCharalambos Ioannidis, Professor<br />
  2. 2. Target: to initialize the ICP algorithm<br /> in order to register partial scans <br /> of uniform or free-form objects<br />Difficulty: no targets present <br />no characteristic points identifiable <br /> in the area of overlap <br />Problem identification<br />
  3. 3. Motivation<br />Initial state<br />Front view<br />Side view<br />
  4. 4. Motivation<br />Result of ICP - no prior processing<br />Front view<br />Side view<br />
  5. 5. Various approaches for automatic ICP initialization:<br />Bae & Lichti, 2004 Geometric primitives<br />Gelfand, 2005 Feature points<br />Hansen, 2006 Plane-matching<br />Makadia, 2006 Extended Gaussian Images<br />Biswas, 2006 Isosurfaces<br />Related Literature<br />
  6. 6. Bae & Lichti, 2004 Geometric primitives <br />Gelfand, 2005 Feature points <br />Hansen, 2006 Plane-matching<br />Makadia, 2006 Extended Gaussian Images<br />Biswas, 2006 Isosurfaces<br />Example Objects<br />
  7. 7. Constrained acquisition process<br />Properly adjusted methods that:<br />Recover the relative transformation between two or more partial scans<br />Approximately align the point clouds<br />Enable the initialization of ICP<br />Achieve the optimal alignment of partial scans without the use of targetsor the identification of conjugate points<br />Proposed approach<br />
  8. 8. Worked cases<br />
  9. 9. Worked cases<br />
  10. 10. HDS2500<br />FOV 40ox40o<br />spot size = 6mm <br />position accuracy = ±6mm (50m range)<br />Equipment used<br />
  11. 11. Key Idea<br />Y<br />Y<br />ω<br />Z<br />Z<br />X<br />X<br />Y<br />Z<br />X<br />Acquisition scenario<br />
  12. 12. Key Idea<br />Y<br />Y<br />Y<br />Y<br />Z<br />ω<br />ω<br />X<br />Z<br />X<br />Z<br />Z<br />X<br />X<br />Acquisition scenario<br />Acquired data<br />Proposed approach<br />
  13. 13. Initial state<br />Front view<br />Side view<br />
  14. 14. Result of ICP combined with the proposed method<br />Front view<br />Front view<br />Side view<br />
  15. 15. Data imported:<br />2 scans acquired either by rotating the scan head vertically (ω angle) or horizontally (φ angle)<br />Process:<br /> The space of the unknown parameter (ω or φ angle) is sequentially sampled in order to obtain an approximation of the unknown angle. If the value of the evaluated measure is minimized then an approximate value is derived<br />Proposed algorithm<br />
  16. 16. If the unknown rotation is ω<br />The ω is given an initial value 0 that is increased by 5g in every loop<br />For every ω value, a rotation matrix is calculated and applied to the point-cloud that needs to be registered<br />After the transformation, the area of overlap between the reference and the moving scan is calculated and a rectangular grid is defined<br />Sampling process 1/2<br />
  17. 17. The evaluated function i.e. the median of the distances of the two point clouds at the nodes of the grid along the Z direction, is derived based on 2D tesselations created for each point-cloud<br />Once the comparison measure reaches a minimum, the process is repeated at the respective interval with a step of 1g<br />When another minimum is detected, the final value is derived by a simple interpolation<br />Sampling process 2/2<br />
  18. 18. 2 scans acquired by different ω angle<br />5 targets used to evaluate the results<br />Algorithm implemented in Matlab <br />Calculation of the unknown transform in Cyclone and in Matlab<br />Method Validation<br />
  19. 19. Initial State<br />
  20. 20. Target distances as calculated for the original scans<br />
  21. 21. Results of the sampling process<br />
  22. 22. Results after the approximate alignment<br />
  23. 23. Results after the approximate alignment<br />
  24. 24. Result of ICP after the application of the proposed algorithm<br />
  25. 25. Results of ICP after the application of the proposed algorithm<br />
  26. 26. Application of the method for the monument of Zalongon<br />9 set-ups<br />14 scans in total<br />4 scans with no tagets<br />Back<br />3 set-ups<br />4 scans (2 single and a scan-pair)<br />Front<br />6 set-ups<br />10 scans (3 single, 2 scan-pairs and a scan-triplet)<br />
  27. 27. Accuracy evaluation for 2 scan-pairs<br />
  28. 28. Accuracy evaluation for a scan-triplet<br />
  29. 29. Registration results<br />
  30. 30. 3D surface model<br />
  31. 31. With minor modifications, it is as easily applied for horizontal rotations<br />Applicable also for sequences of scans acquired under the described conditions<br />Provides a solution in cases of serious space limitations <br />A non-elaborate and effective solution for all of those who have invested on similar equipment<br />Merits of the proposed approach<br />
  32. 32. Thank you for your attention!<br />