The problem of geometric alignment of two roughly pre-registered, partially overlapping, rigid, noisy 3D point sets is considered. A new natural and simple, robustified extension of the popular Iterative Closest Point (ICP) algorithm is presented, called the Trimmed ICP (TrICP). The new algorithm is based on the consistent use of the Least Trimmed Squares (LTS) approach in all phases of the operation. Convergence is proved and an efficient implementation is discussed. TrICP is fast, applicable to overlaps under 50%, robust to erroneous measurements and shape defects, and has easy-to-set parameters. ICP is a special case of TrICP when the overlap parameter is 100%. Results of testing the new algorithm are shown
A key challenge in reconstructing high-quality 3D scans is registering data from different viewpoint...
Abstract--We address the problem of accurate and efficient alignment of 3D point clouds captured by ...
Aligning point clouds forms the front end of many visual odometry, 3D reconstruction and SLAM system...
We address the problem of Euclidean alignment of two partially overlapping surfaces rep-resented by ...
AbstractThe registration of multi-view point sets is often used in surface reconstruction for comple...
<div><p>We present a probabilistic registration algorithm that robustly solves the problem of rigid-...
Robust registration of two 3-D point sets is a common problem in computer vision. The Iterative Clos...
We present an algorithm for the automatic alignment of two 3D shapes (data and model), without any a...
Abstract — This paper presents a method for pairwise 3D alignment which solves data association by m...
The iterative closest point algorithm is one of the most effi-cient algorithms for robust rigid regi...
This thesis concerns geometric surface registration, a vital part of automatic 3D model building. Th...
The aim of this thesis is to provide a robust and globally optimal method for rigid point set regist...
This thesis concerns geometric surface registration, a vital part of automatic 3D model building. Th...
Registration is a fundamental task in computer vision. The Iterative Closest Point (ICP) algorithm i...
Registration is a fundamental task in computer vision. The Iterative Closest Point (ICP) algorithm i...
A key challenge in reconstructing high-quality 3D scans is registering data from different viewpoint...
Abstract--We address the problem of accurate and efficient alignment of 3D point clouds captured by ...
Aligning point clouds forms the front end of many visual odometry, 3D reconstruction and SLAM system...
We address the problem of Euclidean alignment of two partially overlapping surfaces rep-resented by ...
AbstractThe registration of multi-view point sets is often used in surface reconstruction for comple...
<div><p>We present a probabilistic registration algorithm that robustly solves the problem of rigid-...
Robust registration of two 3-D point sets is a common problem in computer vision. The Iterative Clos...
We present an algorithm for the automatic alignment of two 3D shapes (data and model), without any a...
Abstract — This paper presents a method for pairwise 3D alignment which solves data association by m...
The iterative closest point algorithm is one of the most effi-cient algorithms for robust rigid regi...
This thesis concerns geometric surface registration, a vital part of automatic 3D model building. Th...
The aim of this thesis is to provide a robust and globally optimal method for rigid point set regist...
This thesis concerns geometric surface registration, a vital part of automatic 3D model building. Th...
Registration is a fundamental task in computer vision. The Iterative Closest Point (ICP) algorithm i...
Registration is a fundamental task in computer vision. The Iterative Closest Point (ICP) algorithm i...
A key challenge in reconstructing high-quality 3D scans is registering data from different viewpoint...
Abstract--We address the problem of accurate and efficient alignment of 3D point clouds captured by ...
Aligning point clouds forms the front end of many visual odometry, 3D reconstruction and SLAM system...