Iterative Closest Point
Encyclopedia
Iterative Closest Point is an algorithm
employed to minimize the difference between two clouds of points. ICP is often used to reconstruct 2D or 3D surfaces from different scans, to localize robots and achieve optimal path planning (especially when wheel odometry is unreliable due to slippery terrain), to co-register bone
models, etc.
The algorithm is conceptually simple and is commonly used in real-time. It iteratively revises the transformation (translation, rotation) needed to minimize the distance between the points of two raw scans.
Inputs: points from two raw scans, initial estimation of the transformation, criteria for stopping the iteration.
Output: refined transformation.
Essentially the algorithm steps are :
an open source mesh processing tool that includes a GNU General Public License
implementation of the ICP algorithm.
CloudCompare an open source point and model processing tool that includes an implementation of the ICP algorithm.
PCL (Point Cloud Library)
is an open-source framework for n-dimensional point clouds and 3D geometry processing. It includes several variants of the ICP algorithm.
Algorithm
In mathematics and computer science, an algorithm is an effective method expressed as a finite list of well-defined instructions for calculating a function. Algorithms are used for calculation, data processing, and automated reasoning...
employed to minimize the difference between two clouds of points. ICP is often used to reconstruct 2D or 3D surfaces from different scans, to localize robots and achieve optimal path planning (especially when wheel odometry is unreliable due to slippery terrain), to co-register bone
Bone
Bones are rigid organs that constitute part of the endoskeleton of vertebrates. They support, and protect the various organs of the body, produce red and white blood cells and store minerals. Bone tissue is a type of dense connective tissue...
models, etc.
The algorithm is conceptually simple and is commonly used in real-time. It iteratively revises the transformation (translation, rotation) needed to minimize the distance between the points of two raw scans.
Inputs: points from two raw scans, initial estimation of the transformation, criteria for stopping the iteration.
Output: refined transformation.
Essentially the algorithm steps are :
- Associate points by the nearest neighborNearest neighbor searchNearest neighbor search , also known as proximity search, similarity search or closest point search, is an optimization problem for finding closest points in metric spaces. The problem is: given a set S of points in a metric space M and a query point q ∈ M, find the closest point in S to q...
criteria. - Estimate transformation parameters using a mean squareMean squared errorIn statistics, the mean squared error of an estimator is one of many ways to quantify the difference between values implied by a kernel density estimator and the true values of the quantity being estimated. MSE is a risk function, corresponding to the expected value of the squared error loss or...
cost function. - Transform the points using the estimated parameters.
- IterateIterative methodIn computational mathematics, an iterative method is a mathematical procedure that generates a sequence of improving approximate solutions for a class of problems. A specific implementation of an iterative method, including the termination criteria, is an algorithm of the iterative method...
(re-associate the points and so on).
See also
MeshLabMeshLab
MeshLab, is a free 3D mesh processing software program; MeshLab, started in late 2005, is an open-source general-purpose system aimed to help the processing of the typical not-so-small unstructured 3D models that arise in the pipeline of processing of the data coming from 3D scanning...
an open source mesh processing tool that includes a GNU General Public License
GNU General Public License
The GNU General Public License is the most widely used free software license, originally written by Richard Stallman for the GNU Project....
implementation of the ICP algorithm.
CloudCompare an open source point and model processing tool that includes an implementation of the ICP algorithm.
PCL (Point Cloud Library)
PCL (Point Cloud Library)
PCL is a standalone open-source framework for n-dimensional point clouds and 3D geometry processing. The library contains algorithms for filtering, feature estimation, surface reconstruction, registration, model fitting, and segmentation. PCL is developed by a large consortium of researchers and...
is an open-source framework for n-dimensional point clouds and 3D geometry processing. It includes several variants of the ICP algorithm.