Global Non-Rigid Alignment. Benedict J. Brown Katholieke Universiteit Leuven

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1 Global Non-Rigid Alignment Benedict J. Brown Katholieke Universiteit Leuven

2 3-D Scanning Pipeline Acquisition Scanners acquire data from a single viewpoint

3 3-D Scanning Pipeline Acquisition Alignment

4 3-D Scanning Pipeline Acquisition Alignment Merging

5 Iterative Closest Points [Besl92] To fit two meshes, need correspondence between points Assume points correspond to closest points on other mesh Compute best fit on a subset of all points

6 Iterative Closest Points [Besl92] To fit two meshes, need correspondence between points Assume points correspond to closest points on other mesh Compute best fit on a subset of all points If starting point was good, result should be better

7 Iterative Closest Points [Besl92] To fit two meshes, need correspondence between points Assume points correspond to closest points on other mesh Compute best fit on a subset of all points If starting point was good, result should be better Iterate until fit converges to minimum error

8 Range Scanning: Calibration Error [Levoy00] Courtesy Paul Debevec

9 Range Scanning: Calibration Error [Levoy00] Courtesy Paul Debevec 0 mm 2 mm

10 Range Scanning: Calibration Error [Levoy00] Courtesy Paul Debevec Mechanical Distortion 0 mm 2 mm

11 Goal: Multi-Scan Non-Rigid Alignment We desire an algorithm that will: Prevent artifacts in merging

12 Goal: Multi-Scan Non-Rigid Alignment We desire an algorithm that will: Prevent artifacts in merging Distribute error evenly

13 Goal: Multi-Scan Non-Rigid Alignment We desire an algorithm that will: Prevent artifacts in merging Distribute error evenly Preserve detail without introducing new warp

14 Goal: Multi-Scan Non-Rigid Alignment We desire an algorithm that will: Prevent artifacts in merging Distribute error evenly Preserve detail without introducing new warp Be practical, efficient, and parallelizable for large datasets David's head comprises 1400 scans and 230 million vertices

15 Global Alignment Pipeline Pairwise Correspondences

16 Global Alignment Pipeline Pairwise Correspondences

17 Global Alignment Pipeline Pairwise Correspondences

18 Global Alignment Pipeline Pairwise Correspondences Global Feature Positioning

19 Global Alignment Pipeline Pairwise Correspondences Global Feature Positioning

20 Global Alignment Pipeline Pairwise Correspondences Global Feature Positioning Optimize Global Positions

21 Global Alignment Pipeline Pairwise Correspondences Global Feature Positioning Optimize Global Positions Warp Scans

22 Results: David's Head 1400 range scans 230 million points Correspondences 78 hours CPU time 1.5 hours wall time Positioning and Alignment 30 minutes CPU time

23 Results: David's Head Rigid Non-Rigid

24 Results: David's Head Rigid Non-Rigid

25 Results: David's Head Rigid Non-Rigid

26 Results: Awakening Rigid 1836 scans, 390 million vertices Correspondences: 51.5 CPU hours Alignment: 1 CPU hour

27 Results: Awakening Non-Rigid 1836 scans, 390 million vertices Correspondences: 51.5 CPU hours Alignment: 1 CPU hour

28 Results: Forma Urbis Romae #033 Rigid 140 scans, 71 million vertices; Correspondences: 48 hours; Alignment: 27 minutes

29 Results: Forma Urbis Romae #033 Rigid 140 scans, 71 million vertices; Correspondences: 48 hours; Alignment: 27 minutes

30 Results: Forma Urbis Romae #033 Non-Rigid 140 scans, 71 million vertices; Correspondences: 48 hours; Alignment: 27 minutes

31 Results: Forma Urbis Romae #033 Rigid 140 scans, 71 million vertices; Correspondences: 48 hours; Alignment: 27 minutes

32 Results: Forma Urbis Romae #033 Non-Rigid 140 scans, 71 million vertices; Correspondences: 48 hours; Alignment: 27 minutes

33 Summary Consistently align all pairs of scans to each other Scalability: never more than two scans in memory Compensates for calibration error and slight deformations Supports rigid alignment too: just restrict to rigid transforms Code:

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