Registration is the problem of bringing together two or more 3D shapes, either of the same object or of two different but similar objects. This chapter first introduces the classical Iterative Closest Point (ICP) algorithm which represents the gold standard registration method. Current limitations of ICP are addressed, and the most popular variants of ICP are described to improve the basic implementation in several ways. Challenging registration scenarios are analyzed, and a taxonomy of recent and promising alternative registration techniques is introduced. Four case studies are then described with an increasing level of difficulty. The first case study describes a simple but effective technique to detect outliers. The second case study uses the Levenberg–Marquardt (LM) optimization procedure to solve standard pairwise registration. The third case study focuses on the challenging problem of deformable object registration. The fourth case study introduces an ICP method for preoperative data registration in laparoscopy. Finally, open issues and directions for future work are discussed, and conclusions are drawn.
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