10.5281/zenodo.4314992
https://zenodo.org/records/4314992
oai:zenodo.org:4314992
Joaquín Torres-Sospedra
Joaquín Torres-Sospedra
UBIK Geospatial Solutions
Darwin Quezada Gaibor
Darwin Quezada Gaibor
Universitat Jaume I; Tampere University
Antonio R. Jiménez
Antonio R. Jiménez
Consejo Superior de Investigaciones Científicas
Antoni Pérez-Navarro
Antoni Pérez-Navarro
Universitat Oberta de Catalunya
Fernando Seco
Fernando Seco
Consejo Superior de Investigaciones Científicas
Datasets and Supporting Materials for the IPIN 2020 Competition Track 3 (Smartphone-based, off-site)
Zenodo
2020
Indoor Positioning; IPIN Competition
2020-12-10
10.5281/zenodo.4314991
https://zenodo.org/communities/a_wear
https://zenodo.org/communities/eu
https://zenodo.org/communities/ipin
1.0
Creative Commons Attribution 4.0 International
This package contains the datasets and supplementary materials used in the IPIN 2020 Competition.
Contents:
IPIN2020_Track03_TechnicalAnnex_V1-01.pdf: Technical annex describing the competition
01-Logfiles: This folder contains a subfolder with the 78 training logfiles, 72 of them single floor, 4 in bookshelves areas and 2 of them in floor-transition zones, a subfolder with the 13 validation logfiles, and a subfolder with the 1 blind evaluation logfile as provided to competitors.
02-Supplementary_Materials: This folder contains the matlab/octave parser, the raster maps, the files for the matlab tools and the trajectory visualization.
03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on the 82 evaluation points. It requires the Matlab Mapping Toolbox. The ground truth is also provided as a CSV file. Since the results must be provided with a 2Hz freq. starting from apptimestamp 0, the GT includes the closest timestamp matching the timing provided by competitors. It contains a sample of reported estimations and the corresponding results. Additionally, we provide a second script to provide a more detailed report on the results file (requires export_fig folder to run).
Please, cite the following works when using the datasets included in this package:
Torres-Sospedra, J.; Quezada-Gaibor, D.; Jimenez, A.R.; Perez-Navarro, A.; Seco, F.; Datasets and Supporting Materials for the IPIN 2020 Competition Track 3 (Smartphone-based, off-site). http://dx.doi.org/10.5281/zenodo.4314992
Potortì, F.; Torres-Sospedra, J.; Quezada-Gaibor, D.; Jiménez, A.R.; Seco, F.; Pérez-Navarro, A.; Ortiz, M.; Zhu, N.; Renaudin, V.; Ichikari, R.; Shimomura, R.; Ohta, N.; Nagae, S.; Kurata, T.; Wei, D.; Ji, X.; Zhang, W.; Kram, S.; Stahlke, M.; Mutschler, C.; Crivello, A.; Barsocchi, P.; Girolami, M.; Palumbo, F.; Chen, R.; Wu, Y.; Li, W.; Yu, Y.; Xu, S.; Huang, L.; Liu, T.; Kuang, J.; Niu, X.; Yoshida, T.; Nagata, Y.; Fukushima, Y.; Fukatani, N.; Hayashida, N.; Asai, Y.; Urano, K.; Ge, W.; Lee, N.T.; Fang, S.H.; Jie, Y.C.; Young, S.R.; Chien, Y.R.; Yu, C.C.; Ma, C.; Wu, B.; Zhang, W.; Wang, Y.; Fan, Y.; Poslad, S.; Selviah, D.R.; Wang, W.; Yuan, H.; Yonamoto, Y.; Yamaguchi, M.; Kaichi, T.; Zhou, B.; Liu, X.; Gu, Z.; Yang, C.; Wu, Z.; Xie, D.; Huang, C.; Zheng, L.; Peng, A.; Jin, G.; Wang, Q.; Luo, H.; Xiong, H.; Bao, L.; Zhang, P.; Zhao, F.; Yu, C.A.; Hung, C.H.; Antsfeld, L.; Chidlovskii, B.; Jiang, H.; Xia, M.; Yan, D.; Li, Y.; Dong, Y.; Silva, I.; Pendão, C.; Meneses, F.; Nicolau, M.J.; Costa, A.; Moreira, A.; Cock, C.D.; Plets, D.; Opiela, M.; Džama, J.; Zhang, L.; Li, H.; Chen, B.; Liu, Y.; Yean, S.; Lim, B.Z.; Teo, W.J.; Lee, B.S.; Oh, H.L. Off-line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences from IPIN 2020 Competition IEEE Sensors Journal, Early Access (in press), 2021. https://doi.org/10.1109/JSEN.2021.3083149
We would like to thank ISTI-CNR for managing the Virtual competition and find sponsors for the winner's award. We are also grateful to Francesco Potortì, Sangjoon Park and the ISTI-CNR team for their invaluable help in organizing and promoting the IPIN competition and conference. Parts of this work were carried out with the financial support received from projects and grants:
- A-WEAR (H2020-MSCA-ITN-2018, Grant Agreement 813278)
- INSIGNIA (PTQ2018-009981)
- REPNIN+ network (TEC2017-90808-REDT)
- LORIS (TIN2012-38080-C04-04)
- SmartLoc(CSIC-PIE Ref.201450E011)
- TARSIUS (TIN2015-71564-C4-2-R, MINECO/FEDER)
- MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE)
European Commission
10.13039/501100000780
813278
A network for dynamic WEarable Applications with pRivacy constraints