Code of "An Efficient Rotation and Translation Decoupled Initialization from Large Field of View Depth Images"
- Please see the documentation and dependencies of this module in the "doc/" folder, by opening the index.html in your brownser
- Open Matlab and select your current working directory as the one with the "main.m" function, open this function and run it.
- The salience function uses a compiled mex file for selecting the most informative information for the translation estimation. The code was compiled in Ubuntu 16.04 and should run in a similar PC architecture. If not, please compile the file "mex_saliency_geometry.cpp".
This is an example for computing the pose initialization from normals using wide FOV sensors as in the IROS 2017 Paper:
- An Efficient Rotation and Translation Decoupled Initialization from Large Field of View Depth Images R Martins, E Fernandez-Moral, P Rives IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS'17
If this code is useful for you, please cite our paper in your research as:
@inproceedings{martins17,
author = {Renato Martins and
Eduardo Fernandez{-}Moral and
Patrick Rives},
title = {An efficient rotation and translation decoupled initialization from
large field of view depth images},
booktitle = {{IEEE/RSJ} International Conference on Intelligent Robots and
Systems, {IROS}, Vancouver, Canada},
year = {2017}
}