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Registration Tutorials
======================
The PCL Registration API
~~~~~~~~~~~~~~~~~~~~~~~~
In this document, we describe the point cloud registration API and its modules: the estimation and rejection of point correspondences, and the estimation of rigid transformations.
* `Original <http://pointclouds.org/documentation/tutorials/registration_api.php#registration-api>`_ \
* TestCode : None
How to use iterative closest point
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This tutorial gives an example of how to use the iterative closest point algorithm to see if one PointCloud is just a rigid transformation of another PointCloud.
* `Original <http://pointclouds.org/documentation/tutorials/iterative_closest_point.php#iterative-closest-point>`_ \
* TestCode : examples/official/Registration/iterative_closest_point.py
How to incrementally register pairs of clouds
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This document demonstrates using the Iterative Closest Point algorithm in order to incrementally register a series of point clouds two by two.
* `Original <http://pointclouds.org/documentation/tutorials/pairwise_incremental_registration.php#pairwise-incremental-registration>`_ \
* TestCode : None
Interactive Iterative Closest Point
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This tutorial will teach you how to build an interactive ICP program
* `Original <http://pointclouds.org/documentation/tutorials/interactive_icp.php#interactive-icp>`_ \
* TestCode : None
How to use Normal Distributions Transform
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This document demonstrates using the Normal Distributions Transform algorithm to register two large point clouds.
* `Original <http://pointclouds.org/documentation/tutorials/normal_distributions_transform.php#normal-distributions-transform>`_ \
* TestCode : examples/official/Registration/normal_distributions_transform.py
In-hand scanner for small objects
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
This document shows how to use the In-hand scanner applications to obtain colored models of small objects with RGB-D cameras.
* `Original <http://pointclouds.org/documentation/tutorials/in_hand_scanner.php#in-hand-scanner>`_ \
* TestCode : None
Robust pose estimation of rigid objects
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
In this tutorial, we show how to find the alignment pose of a rigid object in a scene with clutter and occlusions.
* `Original <http://pointclouds.org/documentation/tutorials/alignment_prerejective.php#alignment-prerejective>`_ \
* TestCode : examples/official/Registration/alignment_prerejective.py
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