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CORDIS

An AR cloud and digital twins solution for industry and construction 4.0

Livrables

Dissemination, Awareness raising and Communication Plan – Final version

An updated version the “D6.1 Dissemination, Awareness raising and Communication Plan – Initial version”.

Dissemination, Awareness raising and Communication Plan – Initial version

A report that will describe the strategy, plan and actions to be taken in the framework of ARtwin with respect to dissemination, awareness raising and communication.

Results of dissemination and communication activities - Final version

Final reporting on the ARtwin dissemination and communication activities

ARtwin requirements specification

A report that will outline the requirements that will drive the architecture specification, the map pivot format specification, the service implementation, the platform development and the implementation of the use cases.

Report on ARtwin generic developments

A report (including blueprints) that will define the generic developments of the platform from three different views (contractual, edition, operational).

Evaluation report of in the field experimentation of the use cases

A report that contains the evaluation of in the field experimentation of the pilot use cases

Results of dissemination and communication activities – Initial version

Reporting on the ARtwin dissemination and communication activities.

Report on ARtwin specific developments

A report including blue prints that will define the specific developments of the platform regarding the three different views contractual edition operational

Map pivot format specification

A report that will specify the pivot format of the map that will be used to develop the respective services provided by the platform.

Preliminary platform specification

A report that will define the architecture of the platform and its supported components.

NGPaas/SolAR wrapper to deploy SolAR components in NGPaaS micro services

The software component required to deploy SolAR components in NGPaaS micro services.

Publications

AR Cloud: Towards Augmented Reality at the scale of a factory

Auteurs: Jérôme Royan; Nam-Duong Duong; Nischita Sudharsan; Andreas Hutter
Publié dans: EUCNC 2022, 2022
Éditeur: EUCNC 2022
DOI: 10.5281/zenodo.7551489

TRPLP – Trifocal Relative Pose From Lines at Points

Auteurs: Ricardo Fabbri, Timothy Duff, Hongyi Fan, Margaret H. Regan, David da Costa de Pinho, Elias Tsigaridas, Charles W. Wampler, Jonathan D. Hauenstein, Peter J. Giblin, Benjamin Kimia, Anton Leykin, Tomas Pajdla
Publié dans: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Page(s) 12070-12080, ISBN 978-1-7281-7168-5
Éditeur: IEEE
DOI: 10.1109/cvpr42600.2020.01209

Making Affine Correspondences Work in Camera Geometry Computation

Auteurs: Barath, Daniel; Polic, Michal; Förstner, Wolfgang; Sattler, Torsten; Pajdla, Tomas; Kukelova, Zuzana
Publié dans: Computer Vision – ECCV 2020 ISBN: 9783030586201, Numéro 1, 2020
Éditeur: Springer International Publishing
DOI: 10.5281/zenodo.4333706

Learning to solve hard minimal problems

Auteurs: Hruby, P., Duff, T., Leykin, A., & Pajdla, T.
Publié dans: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022, Page(s) pp. 5522-5532
Éditeur: 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
DOI: 10.1109/cvpr52688.2022.00545

Point-line Minimal Problems under Partial Visibility in Three Views

Auteurs: Timothy Duff, Kathlén Kohn, Anton Leykin, Tomas Pajdla
Publié dans: CVPR 2020, 2020
Éditeur: CVPR 2020

Motion Segmentation with Pairwise Matches and Unknown Number of Motions

Auteurs: Federica Arrigoni,Luca Magri,Tomas Pajdla
Publié dans: 2020 25th International Conference on Pattern Recognition (ICPR), 2021
Éditeur: 2020 25th International Conference on Pattern Recognition (ICPR)
DOI: 10.1109/icpr48806.2021.9413142

Enabling Customizable Workflows for Industrial AR Applications

Auteurs: Valeriya Lehrbaum, Asa MacWilliams, Joseph Newman, Nischita Sudharsan, Seongjin Bien, Konstantin Karas, Chloe Eghtebas, Sandro Weber, Gudrun Klinker
Publié dans: 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Singapore, 2022, Page(s) p. 622-630
Éditeur: 2022 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), Singapore
DOI: 10.1109/ismar55827.2022.00079

A Large Scale Homography Benchmark

Auteurs: Daniel Barath, Dmytro Mishkin, Michal Polic, Wolfgang Förstner, Jiri Matas
Publié dans: 2023
Éditeur: Under review for CVPR 2023

AR Cloud: Towards Collaborative Augmented Reality at a Large-Scale

Auteurs: Nam-Duong Duong; Christophe Cutullic; Jean-Marie Hénaff; Jérôme Royan
Publié dans: ISMAR 2022, 2022
Éditeur: ISMAR 2022
DOI: 10.5281/zenodo.7551471

PL$$_$$P - Point-Line Minimal Problems Under Partial Visibility in Three Views

Auteurs: Timothy Duff; Kathlén Kohn; Anton Leykin; Tomas Pajdla
Publié dans: Computer Vision – ECCV 2020 ISBN: 9783030585730, 2020
Éditeur: ECCV 2020
DOI: 10.5281/zenodo.4335174

D-InLoc++: Indoor Localization in DynamicEnvironments

Auteurs: M. Dubenova, A. Zderadickova, O. Kafka, T. Pajdla, M. Polic
Publié dans: ndres, B., Bernard, F., Cremers, D., Frintrop, S., Goldlücke, B., Ihrke, I. (eds) Pattern Recognition. DAGM GCPR 2022. Lecture Notes in Computer Science, Numéro 13485, 2022
Éditeur: https://doi.org/10.1007/978-3-031-16788-1_16
DOI: 10.48550/arxiv.2209.10185

Uncertainty Based Camera Model Selection

Auteurs: Michal Polic, Stanislav Steidl, Cenek Albl, Zuzana Kukelova, Tomas Pajdla
Publié dans: 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, Page(s) 5990-5999, ISBN 978-1-7281-7168-5
Éditeur: IEEE
DOI: 10.1109/cvpr42600.2020.00603

On the Usage of the Trifocal Tensor in Motion Segmentation

Auteurs: Federica Arrigoni, Luca Magri, Tomas Pajdla
Publié dans: Computer Vision – ECCV 2020 - 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XX, Numéro 12365, 2020, Page(s) 514-530, ISBN 978-3-030-58564-8
Éditeur: Springer International Publishing
DOI: 10.1007/978-3-030-58565-5_31

Improving Image Pair Selection for Large Scale Structure fromMotion by Introducing Modified Simpson Coefficient

Auteurs: T. Kato, I. Shimizu, T. Pajdla
Publié dans: IEICE TRANSACTIONS on Information and Systems, Numéro Vol.E105-D No.9, 2022, Page(s) pp.1590-1599, ISSN 1745-1361
Éditeur: The Institute of Electronics, Information and Communication Engineers
DOI: 10.1587/transinf.2021edp7244

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