Livrables
Lens calibration from 3D Reconstruction
Implement lens calibration from 3D Reconstruction in openMVG
GPU optimised version of OpenCMPMVSImplement GPU optimised version of OpenCMPMVS
CamBox and MiniBoxRT Acquisition - Implementation of the CamBox and MiniBox
Improve SfM accuracy and precisionSetBox
SetBox - Implementation of the SetBox
File formats release implementations as open sourceRelease implementations as open source
SfM LiDAR integrationSfM: LiDAR integration
SfM integration for 360° cameras and camera rigsLADIO Application importers and exporters
Implement LADIO Application importers and exporters
Implement SfM Multibody into openMVGBackend Timeline Module
Implement Backend Timeline Module
OpenCMPMVSImplement OpenCMPMVS
Advanced OpenCMPMVS - Multibody and LiDARImplement advanced OpenCMPMVS - Multibody and LiDAR
Distributed NetworkImplementation of the Distributed Data Management system
Documentation of the deployed technical mechanisms
Report on Pilot ProductionFinal report
Final project report
Quarterly management reports 1 and 2Quarterly management reports 3 and 4
3D Reconstruction benchmarks with dataset
Deliver 3D Reconstruction benchmarks with dataset
Model & API definitionDocumentation of extensions for EBU CCDN, EBUCore and newly defined REST API
Quarterly management reports 5 and 6File and database formats for data storage
List of file formats to use unchanged and recommendation for filling gaps
The LADIO project participates in the pilot on open research data. In this task we will formulate a data management plan to make available data sets that can benefit the academic community and other users.
Publications
Auteurs:
Cenek Albl, Zuzana Kukelova, Andrew Fitzgibbon, Jan Heller, Matej Smid, Tomas Pajdla
Publié dans:
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Page(s) 5593-5602, ISBN 978-1-5386-0457-1
Éditeur:
IEEE
DOI:
10.1109/CVPR.2017.593
Auteurs:
Michal Polic, Tomas Pajdla
Publié dans:
Scandinavian Conference on Image Analysis, 2017, Page(s) 110-121, ISBN 978-3-319-59126-1
Éditeur:
Springer International Publishing
DOI:
10.1007/978-3-319-59126-1_10
Auteurs:
Hatem A. Rashwan, Sylvie Chambon, Pierre Gurdjos, Geraldine Morin, Vincent Charvillat
Publié dans:
2016 IEEE International Conference on Image Processing (ICIP), 2016, Page(s) 36-40, ISBN 978-1-4673-9961-6
Éditeur:
IEEE
DOI:
10.1109/ICIP.2016.7532314
Auteurs:
Torsten Sattler, Akihiko Torii, Josef Sivic, Marc Pollefeys, Hajime Taira, Masatoshi Okutomi, Tomas Pajdla
Publié dans:
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017, Page(s) 6175-6184, ISBN 978-1-5386-0457-1
Éditeur:
IEEE
DOI:
10.1109/CVPR.2017.654
Auteurs:
Rashwan, Hatem A.; Chambon, Sylvie; Morin, Geraldine; Gurdjos, Pierre; Charvillat, Vincent
Publié dans:
Eurographics Workshop on 3D Object Retrieval, 2017, ISBN 978-3-03868-030-7
Éditeur:
The Eurographics Association
DOI:
10.2312/3dor.20171062
Auteurs:
Takaharu Kato, Ikuko Shimizu, Tomas Pajdla
Publié dans:
IPSJ Transactions on Computer Vision and Applications, Numéro 9/1, 2017, ISSN 1882-6695
Éditeur:
Information Processing Society of Japan
DOI:
10.1186/s41074-017-0021-8
Auteurs:
Joe Kileel, Zuzana Kukelova, Tomas Pajdla, Bernd Sturmfels
Publié dans:
Foundations of Computational Mathematics, 2017, ISSN 1615-3375
Éditeur:
Springer Verlag
DOI:
10.1007/s10208-017-9361-0
Auteurs:
Akihiko Torii, Relja Arandjelovic, Josef Sivic, Masatoshi Okutomi, Tomas Pajdla
Publié dans:
IEEE Transactions on Pattern Analysis and Machine Intelligence, Numéro 40/2, 2018, Page(s) 257-271, ISSN 0162-8828
Éditeur:
Institute of Electrical and Electronics Engineers
DOI:
10.1109/TPAMI.2017.2667665
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