This page lists the available tutorials for libpointmatcher. The Beginner Section is aimed at the more casual user and contains high-level information on the various steps of point cloud registration. The Advanced Section is targeted at those with existing experience with point cloud registration and proficiency in C++ development. Those who wish to contribute to libpointmatcher can follow the guidelines in the Developer section.
- What is libpointmatcher about?
- What can I do with libpointmatcher?
- Ubuntu: How to compile libpointmatcher
- Windows: How to compile libpointmatcher
- Mac OS X: How to compile libpointmatcher
- What the different data filters do?
- Example: Applying a chain of data filters
- Example: An introduction to ICP
- The ICP chain configuration and its variants
- Configuring libpointmatcher using YAML
- Supported file types and importing/exporting point clouds
- How to link a project to libpointmatcher?
- How to use libpointmatcher in ROS?
- How are point clouds represented?
- Example: Writing a program which performs ICP
- How to move a point cloud using a rigid transformation?
- Example: Configure an ICP solution without yaml
- Measuring Hausdorff distance, Haussdorff quantile and mean residual error? See this discussion for code examples.
- How to compute the residual error with
ErrorMinimizer::getResidualError(...)See the example code provided here. - How to I build a global map from a sequence of scans? See the example align_sequence.cpp.
- How to minimize the error with translation, rotation and scale? See this example.
- How to do a nearest neighbor search between two point clouds without an ICP object? See the comments here.
- How to construct a
DataPointsfrom my own point cloud? See the unit test onDatapointshere.
Note: if you don't find what you need, don't hesitate to propose or participate to new tutorials.
