A method for spatial registration of 3D surfaces was developed for range data acquired by a multi-sensor optical surface scanner. Registration of 3D shapes is important for change detection and inspection. The requirement for an automatic and robust registration method stems from the need to compare digitized human anatomy surfaces obtained over extended periods of time. A typical example is comparison of pre-operative, postoperative, and recovered facial morphology of a face-lift patient. An iterative algorithm that handles six degrees of freedom (three rotations, and three translations) and does not require point to point correspondence of surfaces was developed. The method assumes that the surfaces are in near registration, otherwise, with surfaces having spherical symmetry, many iterations may be required before a successful outcome is achieved. Coarse registration can be obtained by visual transformations or by use of a principal axis transformation. First, points are identified on the second surface that lie on surface normals of points on the first surface. A divide and conquer technique is used to accelerate this process. Any points on the first surface that do not yield points on the second surface are ignored. The two sets of corresponding points (one set on each surface patch) is used in a least squares estimation scheme to minimize their distance. The estimate yields a transformation vector (consisting of rotations and translations) used to resample the second surface patch into a common coordinate system. This iterative process continues until the errors reduce below a set threshold or convergence is reached. Error statistics are reported. Testing and validation of the algorithm shows the method is feasible and efficient.
|Number of pages||12|
|Journal||Proceedings of SPIE - The International Society for Optical Engineering|
|State||Published - Oct 6 1994|
|Event||Sensor Fusion VII 1994 - Boston, United States|
Duration: Oct 31 1994 → Nov 4 1994
- Range Sensing
- Shape Registration