Chapter 32 - Surface registration by markers guided nonrigid iterative closest points algorithm

Abstract

The problem of matching irregular surfaces was tested with additional markers as landmarks for the extension of the nonrigid iterative closest points algorithm. The general idea of presented approach was to take into account knowledge about markers' positions not only in computing transformation phase but also in finding correspondence phase in every algorithm's iteration. Four variants of retrieving correspondence were implemented and compared: the Euclidean distance, normal vectors with initial rigid registration, static and dynamic markers vectors. To evaluate different manner of computing correspondence the average correspondence assignment error of points nearest to the markers and the number of correspondences for every target points were defined. The presented approach was evaluated using abdominal surfaces data set consisting of captured clouds of points during free breathing of six volunteers. The modifications significantly improved results. To make the proposed changes more universal k-nearest neighbor method and radius constraint could be used.