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Dataset . 2019
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2019
License: CC BY
Data sources: Datacite
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Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site)

Authors: Antonio Ramón Jiménez Ruiz; Antoni Perez-Navarro; Antonino Crivello; Germán Martín Mendoza-Silva; Fernando Seco; Miguel Ortiz; Johan Perul; +1 Authors

Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site)

Abstract

This package contains the datasets and supplementary materials used in the IPIN 2019 Competition (Pisa, Italy). Contents: IPIN2019_Call4Competition: Call for competition and main rules IPIN2019_Track03_TechnicalAnnex: Technical annex describing the Track 3 of the competition. 01-Logfiles: This folder contains a subfolder with the 50 (40 + 10) training logfiles, a subfolder with the 9 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 vector maps and the visualization of the training routes. 03-Evaluation: This folder contains the scripts used to calculate the competition metric, the 75th percentile on the 99 evaluation points. The ground truth is also provided in MatLab format and 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. Please, cite the following works when using the datasets included in this package: Jiménez, A. R.; Perez-Navarro, A.; Crivello, A.; Mendoza-Silva, G.; Ortiz, M.; Perul, J.; Seco, F. and Torres-Sospedra, J. Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site), Zenodo 2019. http://dx.doi.org/10.5281/zenodo.3606765 Potorti, F.; Park, S.; Palumbo, F.; Girolami, M.; Barsocchi, P.; Lee, S.; Torres-Sospedra, J.; Jimenez Ruiz, A. R.; Perez-Navarro, A.; Mendoza-Silva, G. M.; Seco, F.; Ortiz, M.; Perul, J.; Renaudin, V.; Kang, H.; Park, S. Y.; Lee, J. H.; Park, C. G.; Ha, J.; Han, J.; Park, C.; KIM, K.; Lee, Y.; GYE, S.; Lee, K.; Kim, E.; Choi, J.-S.; Choi, Y.-S.; Talwar, S.; Cho, S. Y.; Ben-Moshe, B.; Sansano, E.; Chidlovskii, B.; Kronenwett, N.; Prophet, S.; Landay, Y.; Marbel, R.; Peng, A.; Wu, B.; MA, C.; Poslad, S.; Selviah, D.; Wu, W.; Ma, Z.; Zhang, W.; Wei, D.; Yuan, H.; Jiang, J.-B.; Liu, J.-W.; Su, K.-W.; Leu, J.-S.; Nishiguchi, K.; Bousselham, W.; Uchiyama, H.; Thomas, D.; Shimada, A.; Taniguchi, R.-I.; Cortés, V.; Lungenstrass, T.; Ashraf, I.; Lee, C.; Usman Ali, M.; Im, Y.; Kim, G.; Eom, J.; Hur, S.; Park, Y.; Opiela, M.; Moreira, A.; Nicolau, M. J.; Pendão, C.; Silva, I.; Meneses, F.; Costa, A.; Trogh, J.; Plets, D.; Chien, Y.-R.; Chang, T.-Y.; Fang, S.-H.; Tsao, Y. The IPIN 2019 Indoor Localisation Competition - Description and Results IEEE Access Vol. 8, pp. 206674-206718, 2020. https://doi.org/10.1109/ACCESS.2020.3037221 Additional information can be found at: http://evaal.aaloa.org/2019/call-for-competitions For any further questions about the database and this competition track, please contact: Joaquín Torres (jtorres@uji.es,torres@ubikgs.com) UBIK Geospatial Solutions S.L., SpainInstitute of New Imaging Technologies, Universitat Jaume I, Spain. Antonio R. Jiménez (antonio.jimenez@csic.es) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.

We would like to thank ISTI-CNR for sponsoring the competition track with an award for the winning team. 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: REPNIN+ network (TEC2017-90808-REDT), LORIS (TIN2012-38080-C04-04), TARSIUS (TIN2015-71564-C4-2-R, MINECO/FEDER), SmartLoc(CSIC-PIE Ref.201450E011), GEO-C (Project ID: 642332, H2020-MSCA-ITN-2014, Marie Sklodowska-Curie Action: Innovative Training Networks) and A-WEAR (Project ID: 813278, H2020-MSCA-ITN-2018, Marie Sklodowska-Curie Action: Innovative Training Networks).

Keywords

RF Fingerprinting, Sensor Fusion, Indoor Positioning, Particle filter, Kalman filter, Pedestrian Dead Reckoning, Competition datasets, Indoor Navigation, Map Matching

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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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