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Helmholtz Stereopsis Synthetic Dataset

Roubtsova, Nadejda and Guillemaut, Jean-Yves Helmholtz Stereopsis Synthetic Dataset [Dataset]

Full text not available from this repository.
Item Type: Dataset
Subjects : 3D Computer Vision
Divisions : Faculty of Engineering and Physical Sciences
Principal Investigator :
Principal InvestigatorEmail
Description : The dataset consists of synthetic images for three test objects intended to be used as a benchmark for reconstruction via Helmholtz Stereopsis. This also includes ground truth data for quantitative evaluation.
Publication Year of Data : 2017
Creation Dates : 2016
Funder : EPSRC
DOI : 10.15126/surreydata.00841369
Grant Title : Shape and Reflectance Acquisition of Complex Dynamic Scenes
Access Statement : The authors confirm that the dataset generated as part of this research is freely available under the terms and conditions detailed in the license agreement enclosed in the research data repository. By accessing and/or using the data you are agreeing to following terms and conditions: 1. All original imagery and associated data provided may be used for non-commercial research purposes only. 2. The source of the datasets must be acknowledged in all publications in which it is used. This should be done by referencing the dataset's DOI, the dataset webpage and the corresponding publication: N. Roubtsova and J.-Y. Guillemaut, "Bayesian Helmholtz Stereopsis with Integrability Prior", IEEE Transactions on Pattern Analysis and Machine Intelligence, 2017. 3. The data may not be redistributed. 3D meshes of Pear and Bunny were used with permission of the third-party creators: Pear was created by Rob Kalnins as part of WYSIWYG NPR project; Bunny is the Stanford Bunny from the Stanford 3D scanning repository, Stanford University Computer Graphics Laboratory, Both models are said to be allowed for use in non-commercial research. It is however your responsibility to obtain details of licence agreement information concerning these models from the creators' websites or by contacting them directly should you wish to use the models.
Copyright License : Copyright: Attribution-Non-Commercial-No-Redistribution
Data Access Contact :
Data Access ContactEmail
External Data Location :
Depositing User : Alice Motes
Date Deposited : 13 Jun 2017 14:31
Last Modified : 11 Dec 2018 11:23

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