—We consider 3D brain structures as continuous parameterized surfaces and present a metric for their comparisons that is invariant to the way they are parameterized. Past compari...
Sebastian Kurtek, Eric Klassen, Zhaohua Ding, Sand...
We present a novel approach for unsupervised discovery of repetitive objects from 3D point clouds. Our method assumes that objects are geometrically consistent, and uses multiple o...
— Scan matching techniques have been widely used to compute the displacement of robots. This estimate is part of many algorithms addressing navigation and mapping. This paper add...
This paper investigates the use of Euclidean invariant features in a generalization of iterative closest point registration of range images. Pointwisecorrespondences are chosen as...
We consider the ICP (iterative closest point) algorithm, which may in general be used for moving `active' elements such as curves and surfaces towards geometric objects whose...
The ICP (Iterative Closest Point) algorithm is widely used for geometric alignment of three-dimensional models when an initial estimate of the relative pose is known. Many variant...
A novel solution is presented to the Nearest Neighbor Problem that is specifically tailored for determining correspondences within the Iterative Closest Point Algorithm. The refer...
This paper presents a powerful variant of the ICP (Iterative Closest Point) algorithm for registering range images using a probability field. The probability field (p-field) repre...
Abstract—This work presents a method for the registration of threedimensional (3-D) shapes. The method is based on the iterative closest point (ICP) algorithm and improves it thr...
The need to register data is abundant in applications such as: world modeling, part inspection and manufacturing, object recognition, pose estimation, robotic navigation, and reve...