Skip to content
No description, website, or topics provided.
MATLAB
Branch: master
Clone or download

Latest commit

Fetching latest commit…
Cannot retrieve the latest commit at this time.

Files

Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
circle examples Jan 7, 2020
se2
se3
sphere
torus
util
LICENSE
README.md Update README.md Jan 21, 2020
init.m

README.md

c-sensor-registration

This repository contains examples of sensor registration using different manifolds and Lie groups. For the RGB-D visual odometry case, i.e., R^3 and SE(3), see: Continuous Direct Sparse Visual Odometry from RGB-D Images.

Continuous sensor registration is a new mathematical framework that enables nonparametric joint semantic/appearance and geometric representation of continuous functions using data. The joint semantic and geometric embedding is modeled by representing the processes in a reproducing kernel Hilbert space. The framework allows the functions to be defined on arbitrary smooth manifolds where the action of a Lie group is used to align them. The continuous functions allow the registration to be independent of a specific signal resolution and the framework is fully analytical with a closed-form derivation of the Riemannian gradient and Hessian.

Citations

  • William Clark, Maani Ghaffari, Anthony Bloch. "Nonparametric Continuous Sensor Registration." arXiv preprint arXiv:2001.04286, 2020. https://arxiv.org/abs/2001.04286
@article{clark2020nonparametric,
  title={Nonparametric Continuous Sensor Registration},
  author={Clark, William and Ghaffari, Maani and Bloch, Anthony},
  journal={arXiv preprint arXiv:2001.04286},
  year={2020}
}
You can’t perform that action at this time.