1. MARKLESS REGISTRATION FOR SCANS OF FREE-FORM OBJECTS Laboratory of photogrammetry of NTUAArtemis Valanis, PhD StudentCharalambos Ioannidis, Professor

2. Target: to initialize the ICP algorithm in order to register partial scans of uniform or free-form objects Difficulty: no targets present no characteristic points identifiable in the area of overlap Problem identification

3. Motivation Initial state Front view Side view

4. Motivation Result of ICP - no prior processing Front view Side view

5. Various approaches for automatic ICP initialization: Bae & Lichti, 2004 Geometric primitives Gelfand, 2005 Feature points Hansen, 2006 Plane-matching Makadia, 2006 Extended Gaussian Images Biswas, 2006 Isosurfaces Related Literature

6. Bae & Lichti, 2004 Geometric primitives Gelfand, 2005 Feature points Hansen, 2006 Plane-matching Makadia, 2006 Extended Gaussian Images Biswas, 2006 Isosurfaces Example Objects

7. Constrained acquisition process Properly adjusted methods that: Recover the relative transformation between two or more partial scans Approximately align the point clouds Enable the initialization of ICP Achieve the optimal alignment of partial scans without the use of targetsor the identification of conjugate points Proposed approach

8. Worked cases

9. Worked cases

10. HDS2500 FOV 40ox40o spot size = 6mm position accuracy = ±6mm (50m range) Equipment used

11. Key Idea Y Y ω Z Z X X Y Z X Acquisition scenario

12. Key Idea Y Y Y Y Z ω ω X Z X Z Z X X Acquisition scenario Acquired data Proposed approach

13. Initial state Front view Side view

14. Result of ICP combined with the proposed method Front view Front view Side view

15. Data imported: 2 scans acquired either by rotating the scan head vertically (ω angle) or horizontally (φ angle) Process: 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 Proposed algorithm

16. If the unknown rotation is ω The ω is given an initial value 0 that is increased by 5g in every loop For every ω value, a rotation matrix is calculated and applied to the point-cloud that needs to be registered After the transformation, the area of overlap between the reference and the moving scan is calculated and a rectangular grid is defined Sampling process 1/2

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 Once the comparison measure reaches a minimum, the process is repeated at the respective interval with a step of 1g When another minimum is detected, the final value is derived by a simple interpolation Sampling process 2/2

18. 2 scans acquired by different ω angle 5 targets used to evaluate the results Algorithm implemented in Matlab Calculation of the unknown transform in Cyclone and in Matlab Method Validation

19. Initial State

20. Target distances as calculated for the original scans

21. Results of the sampling process

22. Results after the approximate alignment

23. Results after the approximate alignment

24. Result of ICP after the application of the proposed algorithm

25. Results of ICP after the application of the proposed algorithm

26. Application of the method for the monument of Zalongon 9 set-ups 14 scans in total 4 scans with no tagets Back 3 set-ups 4 scans (2 single and a scan-pair) Front 6 set-ups 10 scans (3 single, 2 scan-pairs and a scan-triplet)

27. Accuracy evaluation for 2 scan-pairs

28. Accuracy evaluation for a scan-triplet

29. Registration results

30. 3D surface model

31. With minor modifications, it is as easily applied for horizontal rotations Applicable also for sequences of scans acquired under the described conditions Provides a solution in cases of serious space limitations A non-elaborate and effective solution for all of those who have invested on similar equipment Merits of the proposed approach

32. Thank you for your attention!