Evaluating pcl/registration
This is a collection of ideas on how to build an evaluation framework of pcl/registration.
Data generation
synthetic data
real word data (how to get ground truth?) - Kinect - PR2 laser scanner - SICK laser data - small range 3D scanner - mid range 3D scanner (Faro) - high end 3D scanner (Riegl, Velodyne)
Point Types - 2D(?) - 3D - RGB
dynamics - static scans - scanning while driving (e.g. robots)
size - room - building - outdoor (street)
Architecture
some lib for polygonal data
modeling different sensors
modeling noise
add a trajectory file
output a pile of .pcd files
integrate command line tools from PCL grandfather
Evaluating different algorithms
ICP
how does the algorithm cope with outliers
how are the point pairs evaluated:
does it use normal or RGB information
does it weight the pairs differently
which kind of point pairs are used:
one-to-one
one-to-many
many-to-many