DOI: 10.5281/zenodo.2823963
title: Datasets and Supporting Materials for the IPIN 2018 Competition Track 3 (Smartphone-based, off-site)

description: This package contains the datasets and supplementary materials used in the IPIN 2018 Competition (Nantes, France). <strong>Contents:</strong> IPIN2018_CallForCompetition_v2.1: Call for competition including the technical annex describing the competition 01-Logfiles: This folder contains a subfolder with the 22 training logfiles, a subfolder with the 15 (13 + 2) 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. 03-Evaluation_alternative: This folder contains the alternative scripts used to calculate the competition metric, the 75th percentile on the 99 evaluation points. This version is compatible with MatLab and Octave and does not require any toolbox. In some cases, the differences in the reported errors might be around 10 cm with respect to the script used in the competition. 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. <strong>Please, cite the following works when using the datasets included in this package:</strong> Jimenez, A.R.; Mendoza-Silva, G.M.; Ortiz, M.; Perez-Navarro, A.; Perul, J.; Seco, F.; Torres-Sospedra, J. Datasets and Supporting Materials for the IPIN 2018 Competition Track 3 (Smartphone-based, off-site). http://dx.doi.org/10.5281/zenodo.2823964 Renaudin, V.; Ortiz, M.; Perul, J.; Torres-Sospedra, J.; Ramón Jimenez, A.; Pérez-Navarro, A.; Martín Mendoza-Silva, G.; Seco, F.; Landau, Y.; Marbel, R.; Ben-Moshe, B.; Zheng, X.; Ye, F.; Kuang, J.; Li, Y.; Niu, X.; Landa, V.; Hacohen, S.; Shvalb, N.; Lu, C.; Uchiyama, H.; Thomas, D.; Shimada, A.; Taniguchi, R.; Ding, Z.; Xu, F.; Kronenwett, N.; Vladimirov, B.; Lee, S.; Cho, E.; Jun, S.; Lee, C.; Park, S.; Lee, Y.; Rew, J.; Park, C.; Jeong, H.; Han, J.; Lee, K.; Zhang, W.; Li, X.; Wei, D.; Zhang, Y.; Park, S. Y.; Park, C. G.; Knauth, S.; Pipelidis, G.; Tsiamitros, N.; Lungenstrass, T.; Pablo Morales, J.; Trogh, J.; Plets, D.; Opiela, M.; Shih-Hau Fang Tsao, Y.; Chien, Y.-R.; Yang, S.-S.; Ye, S.-J.; Ali, M. U.; Hur, S.; and Park, Y. Evaluating Indoor Positioning Systems in a Shopping Mall: The Lessons Learned from the IPIN 2018 Competition IEEE Access Vol. 7, pp. 148594-148628, 2019. http://dx.doi.org/10.1109/ACCESS.2019.2944389 <strong>Additional information can be found at:</strong> http://evaal.aaloa.org/2018/call-for-competitions http://ipin-conference.org/2018/ipincompetition/ <strong>For any further questions about the database and this competition track, please contact: </strong> Joaquín Torres (jtorres@uji.es) Institute of New Imaging Technologies, Universitat Jaume I, Spain. Antonio R. Jiménez (antonio.jimenez@csic.es) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.
description: We would like to thank Atlantis le Centre for sponsoring the competition track with an award for the winning team and Viametris for producing the ground truth with their the mobile mapping technology. We are also grateful to Francesco Potortì, Sangjoon Park and the GEOLOC 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).