3D Scan Alignment Using ICP

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Presentation transcript:

3D Scan Alignment Using ICP

Problem Align two partially- overlapping meshes given initial guess for relative transform

Aligning 3D Data If correct correspondences are known, can find correct relative rotation/translation

Aligning 3D Data How to find correspondences: User input? Feature detection? Signatures? Alternative: assume closest points correspond

Aligning 3D Data … and iterate to find alignment Iterative Closest Points (ICP) [Besl & McKay 92] Converges if starting position “close enough“

ICP Variants Variants on the following stages of ICP have been proposed: Selecting source points (from one or both meshes) Matching to points in the other mesh Weighting the correspondences Rejecting certain (outlier) point pairs Assigning an error metric to the current transform Minimizing the error metric w.r.t. transformation

Performance of Variants Can analyze various aspects of performance: Speed Stability Tolerance of noise and/or outliers Maximum initial misalignment Comparisons of many variants in [Rusinkiewicz & Levoy, 3DIM 2001]

ICP Variants Selecting source points (from one or both meshes) Matching to points in the other mesh Weighting the correspondences Rejecting certain (outlier) point pairs Assigning an error metric to the current transform Minimizing the error metric w.r.t. transformation

Closest Compatible Point Closest point often a bad approximation to corresponding point Can improve matching effectiveness by restricting match to compatible points Compatibility of colors [Godin et al. 94] Compatibility of normals [Pulli 99] Other possibilities: curvatures, higher-order derivatives, and other local features

ICP Variants Selecting source points (from one or both meshes) Matching to points in the other mesh Weighting the correspondences Rejecting certain (outlier) point pairs Assigning an error metric to the current transform Minimizing the error metric w.r.t. transformation

Point-to-Plane Error Metric Using point-to-plane distance instead of point-to-point lets flat regions slide along each other [Chen & Medioni 91]

Demo