GithubHelp home page GithubHelp logo

wavelet303 / markerpose Goto Github PK

View Code? Open in Web Editor NEW

This project forked from jhacsonmeza/markerpose

0.0 1.0 0.0 6.31 MB

Python and C++ implementation of "MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation". Accepted at LXCV @ CVPR 2021.

CMake 2.25% C++ 58.74% Python 39.01%

markerpose's Introduction

MarkerPose: Robust real-time planar target tracking for accurate stereo pose estimation

This is a PyTorch and LibTorch implementation of MarkerPose: a robust, real-time pose estimation method based on a planar marker of three circles and a calibrated stereo vision system for high-accuracy pose estimation.

MarkerPose

MarkerPose method consists of three stages. In the first stage, marker points in a pixel-level accuracy, and their IDs are estimated with a SuperPoint-like network for both views. In the second stage, three square patches that contain each ellipse of the target are extracted centered in the rough 2D locations previously estimated. With EllipSegNet the contour of the ellipses is segmented for sub-pixel-level centroid estimation for the first and second view. Finally, in the last stage, with the sub-pixel matches of both views, triangulation is applied for 3D pose estimation. For more details see our paper.

robot_arms

Pose estimation example

To run the Python or C++ pose estimation examples, you need first to clone this repository and download the dataset. This dataset contains the stereo calibration parameters, stereo images, and pretrained weights for SuperPoint and EllipSegNet.

  • Clone this repo: git clone https://github.com/jhacsonmeza/MarkerPose
  • Download the dataset here.
  • Move the dataset/ folder to the cloned repo folder: mv path/to/dataset/ MarkerPose/.

The folder structure into MarkerPose/ directory should be:

MarkerPose
    ├── C++
    ├── dataset
    ├── figures
    └── Python

To know how to run the pose estimation examples, see the Python/ folder for the PyTorch version, and the C++/ folder the LibTorch version. Furthermore, the code for training SuperPoint and EllipSegNet is also available in both versions.

Citation

If you find this code useful, please consider citing:

@inproceedings{meza2021markerpose,
  title={MarkerPose: Robust Real-time Planar Target Tracking for Accurate Stereo Pose Estimation},
  author={Meza, Jhacson and Romero, Lenny A and Marrugo, Andres G},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  year={2021}
}

markerpose's People

Contributors

jhacsonmeza avatar

Watchers

James Cloos avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.