Fast and Accurate Shape-Based Registration

geometric constraint analysis, geometric constraint synthesis Dedicated to Lou and Sybil for starting me on this journey, and to Nanny Frieda for reminding me to enjoy the ride. In many areas of science, engineering, medicine, and especially in the field of robotics, there is a need to establish a spatial mapping between two or more 3-dimensional (3-D) shape representations of an object. The registration problem is concerned with finding a spatial transformation which best aligns two object representations. Once this mapping is established, a variety of tasks can be performed using the aligned object representations including modelbased localization, 3-D object recognition, real-time pose tracking and multi-modality sensor fusion. The research goals of this dissertation are the design, implementation and validation of fast and accurate methods for performing 3-D shape-based registration. Fast registration is achieved via speed enhancements to an existing registration method (the iterative closest point algorithm). The implemented enhancements increase registration speeds by a factor o