University of Padua

A dataset for hand-eye calibration evaluation

Koide, Kenji and Menegatti, Emanuele (2019) A dataset for hand-eye calibration evaluation. [Data Collection]

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Collection description

Description: This dataset aims to assess the accuracy of hand-eye calibration methods (i.e., estimation of the transformation between a robot end effector frame and a camera mounted on it). It contains two sets of images and corresponding robot hand poses. The first one (calib_test) contains images of a calibration pattern to estimate the hand-eye transformation. The second one (spirit_reconst) contains images of a pattern to be 3D reconstructed and manually annotated 2D feature points on the images. By performing multi-view 3D reconstruction on the second set and checking the flatness of the reconstructed points, the calibration accuracy can be assessed. The dimension of the calibration pattern in this dataset is 32 mm. Paper: Kenji Koide and Emanuele Menegatti, General Hand-Eye Calibration based on Reprojection Error Minimization, IEEE Robotics and Automation Letters/ICRA2019

DOI: 10.25430/
Keywords: Hand-eye calibration
Subjects: Physical:Sciences and Engineering > Computer Science and Informatics: Informatics and information systems, computer science, scientific computing, intelligent systems > Computer graphics, computer vision, multi media, computer games
Department: Departments > Dipartimento di Ingegneria dell'Informazione (DEI)
Depositing User: Kenji Koide
Date Deposited: 29 Apr 2019 11:49
Last Modified: 25 Jun 2019 12:24
Type of data: Image
Research funder: EU Horizon2020
Research project title: SPIRIT
Grant number: 779431
Collection period:
Resource language: English
Metadata language: English
Publisher: Research Data Unipd
Related publications:
Date: 18 April 2019
Copyright holders: The Author

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