Motion estimation by iterative 2D features matching in range images

This article describes an iterative algorithm for relative motion estimation from 2D range images. The matching is achieved in the geometric feature domain represented by straight lines and ellipsoidal clusters. Using infinite length straight lines instead of line segments as features, the algorithm attempts to achieve robustness to partial occlusions. The motion estimates and the feature correspondence measures are determined in order to minimize a cost function. The performance of this algorithm was evaluated with experiments carried out in real cluttered indoor environments.