Learning Eye-in-Hand Camera Calibration from a Single Image

11/01/2021
by   Eugene Valassakis, et al.
0

Eye-in-hand camera calibration is a fundamental and long-studied problem in robotics. We present a study on using learning-based methods for solving this problem online from a single RGB image, whilst training our models with entirely synthetic data. We study three main approaches: one direct regression model that directly predicts the extrinsic matrix from an image, one sparse correspondence model that regresses 2D keypoints and then uses PnP, and one dense correspondence model that uses regressed depth and segmentation maps to enable ICP pose estimation. In our experiments, we benchmark these methods against each other and against well-established classical methods, to find the surprising result that direct regression outperforms other approaches, and we perform noise-sensitivity analysis to gain further insights into these results.

READ FULL TEXT

page 1

page 3

page 4

page 8

page 15

page 19

research
11/21/2019

Camera-to-Robot Pose Estimation from a Single Image

We present an approach for estimating the pose of a camera with respect ...
research
02/24/2021

GDR-Net: Geometry-Guided Direct Regression Network for Monocular 6D Object Pose Estimation

6D pose estimation from a single RGB image is a fundamental task in comp...
research
12/15/2022

Learning Markerless Robot-Depth Camera Calibration and End-Effector Pose Estimation

Traditional approaches to extrinsic calibration use fiducial markers and...
research
07/01/2022

Towards Two-view 6D Object Pose Estimation: A Comparative Study on Fusion Strategy

Current RGB-based 6D object pose estimation methods have achieved notice...
research
12/22/2020

A Structure-Aware Method for Direct Pose Estimation

Estimating camera pose from a single image is a fundamental problem in c...
research
04/27/2020

Continuous hand-eye calibration using 3D points

The recent development of calibration algorithms has been driven into tw...
research
03/30/2023

Deep Single Image Camera Calibration by Heatmap Regression to Recover Fisheye Images Under ManhattanWorld AssumptionWithout Ambiguity

In orthogonal world coordinates, a Manhattan world lying along cuboid bu...

Please sign up or login with your details

Forgot password? Click here to reset