Multi Camera Calibration

Overview

Multi Camera Calibration

  1. 'modules/camera_calibration/app/camera_calibration.cpp' is for calculating extrinsic parameter of each individual cameras.
  2. 'modules/camera_calibration/app/HandEyeCalibration.cpp' is the implmentation of multi-camera hand-eye calibration algorithm.

Usage

  1. Pre-calibrate the intrinsic parameters of each camera with arbitary open-sourced methods, e.g. rosrun camera_calibration cameracalibrator.py ...
  2. Use modified config file (e.g parameter/AGV_calib/extrinsic_17023550.xml), change the input path, pattern size, number of corners, number of images to be extrinsically calibrated and intrinsics. Select the options of using pre-computed camera model or not, and moving cameras or calibration target.
  3. Run: ./camera_calibration settingFilePath SavePath, rename the TrajectoryByCV.txt as you wish.
  4. Formulate the captured trajectory from tracking system as timestamp tx ty tz qx qy qz qw into file TrajectoryByGT.txt:
     double timestamp; // second
     double tx ty tz; // give the position
     double qx qy qz qw; // give the orientation in quaternion format
    
  5. Modify the config file (e.g parameter/multi_extrinsic_handeye.yaml).
     int NumOfMeasures; // How many measurements will be used for calibration
     bool UseMultiCam; // Use our proposed method or existing single hand-eye/robot-world algorithms
     bool HandeyeSolver; // Type of Solver: Shah[0] Li[1]
    
  6. Run: ./handeye_camera_calibration settingFilePath GTFilePath_1 TrajectoryFile_1 GTFilePath_2 TrajectoryFile_2 ...

Video

[Experiments Video](coming soon)

References

[1] Yifu Wang*, Wenqing Jiang*, Kun Huang, S oren Schwertfeger and Laurent Kneip. "Accurate calibration ofmulti-perspective cameras from a generalization of the hand-eye constraint" , 2022 IEEE International conference on robotics and automation (ICRA).

You might also like...
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)
S2-BNN: Bridging the Gap Between Self-Supervised Real and 1-bit Neural Networks via Guided Distribution Calibration (CVPR 2021)

S2-BNN (Self-supervised Binary Neural Networks Using Distillation Loss) This is the official pytorch implementation of our paper: "S2-BNN: Bridging th

the code for paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration"

EOW-Softmax This code is for the paper "Energy-Based Open-World Uncertainty Modeling for Confidence Calibration". Accepted by ICCV21. Usage Commnd exa

A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization
A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

Website, Tutorials, and Docs    Uncertainty Toolbox A python toolbox for predictive uncertainty quantification, calibration, metrics, and visualizatio

We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.
We utilize deep reinforcement learning to obtain favorable trajectories for visual-inertial system calibration.

Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning Update: The lastest code will be updated in this branch. Pleas

Improving Calibration for Long-Tailed Recognition (CVPR2021)
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

Source code of NeurIPS 2021 Paper ''Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration''

CaGCN This repo is for source code of NeurIPS 2021 paper "Be Confident! Towards Trustworthy Graph Neural Networks via Confidence Calibration". Paper L

CSAC - Collaborative Semantic Aggregation and Calibration for Separated Domain Generalization
CSAC - Collaborative Semantic Aggregation and Calibration for Separated Domain Generalization

CSAC Introduction This repository contains the implementation code for paper: Co

[CVPR 2022] Official code for the paper:
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"

MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved

Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process

Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is established, which is named opensa (openspectrum analysis).

Owner
null
Automatic Calibration for Non-repetitive Scanning Solid-State LiDAR and Camera Systems

ACSC Automatic extrinsic calibration for non-repetitive scanning solid-state LiDAR and camera systems. System Architecture 1. Dependency Tested with U

KINO 192 Dec 13, 2022
CTRL-C: Camera calibration TRansformer with Line-Classification

CTRL-C: Camera calibration TRansformer with Line-Classification This repository contains the official code and pretrained models for CTRL-C (Camera ca

null 57 Nov 14, 2022
Omnidirectional camera calibration in python

Omnidirectional Camera Calibration Key features pure python initial solution based on A Toolbox for Easily Calibrating Omnidirectional Cameras (Davide

Thomas Pönitz 12 Nov 22, 2022
Camera-caps - Examine the camera capabilities for V4l2 cameras

camera-caps This is a graphical user interface over the v4l2-ctl command line to

Jetsonhacks 25 Dec 26, 2022
PoseViz – Multi-person, multi-camera 3D human pose visualization tool built using Mayavi.

PoseViz – 3D Human Pose Visualizer Multi-person, multi-camera 3D human pose visualization tool built using Mayavi. As used in MeTRAbs visualizations.

István Sárándi 79 Dec 30, 2022
The comma.ai Calibration Challenge!

Welcome to the comma.ai Calibration Challenge! Your goal is to predict the direction of travel (in camera frame) from provided dashcam video. This rep

comma.ai 697 Jan 5, 2023
The official repo of the CVPR2021 oral paper: Representative Batch Normalization with Feature Calibration

Representative Batch Normalization (RBN) with Feature Calibration The official implementation of the CVPR2021 oral paper: Representative Batch Normali

Open source projects of ShangHua-Gao 76 Nov 9, 2022
Improving Calibration for Long-Tailed Recognition (CVPR2021)

MiSLAS Improving Calibration for Long-Tailed Recognition Authors: Zhisheng Zhong, Jiequan Cui, Shu Liu, Jiaya Jia [arXiv] [slide] [BibTeX] Introductio

Jia Research Lab 116 Dec 20, 2022
Improving Calibration for Long-Tailed Recognition (CVPR2021)

Improving Calibration for Long-Tailed Recognition (CVPR2021)

Jia Research Lab 19 Apr 28, 2021
Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021

SNN_Calibration Pytorch Implementation of Spiking Neural Networks Calibration, ICML 2021 Feature Comparison of SNN calibration: Features SNN Direct Tr

Yuhang Li 60 Dec 27, 2022