Dataset Open Access

Datasets and Supporting Materials for the IPIN 2016 Competition Track 3 (Smartphone-based, off-site)

Antonio Ramón Jimenez Ruiz; Germán Martín Mendoza-Silva; Raul Montoliu; Fernando Seco; Joaquín Torres-Sospedra

Citation Style Language JSON Export

  "publisher": "Zenodo", 
  "DOI": "10.5281/zenodo.2791530", 
  "title": "Datasets and Supporting Materials for the IPIN 2016 Competition Track 3 (Smartphone-based, off-site)", 
  "issued": {
    "date-parts": [
  "abstract": "<p>This package contains the datasets and supplementary materials&nbsp;used in the IPIN 2016 Competition (Alcal&aacute;, Spain).</p>\n\n<p><strong>Contents:</strong></p>\n\n<ol>\n\t<li>Track3_LogfileDescription_and_SupplementaryMaterial.pdf:&nbsp;Description of the logfiles and supplemental materials.</li>\n\t<li>Track3_TechnicalAnnex.pdf:&nbsp;Technical annex describing the competition&nbsp;</li>\n\t<li>01-Logfiles:&nbsp;This folder contains a subfolder with the 17 training logfiles&nbsp;and a subfolder with the 9 blind evaluation logfiles as provided&nbsp;to competitors.</li>\n\t<li>02-Supplementary_Materials:&nbsp;This folder contains the Matlab/octave parser, the raster maps&nbsp;and the visualization of the training routes.</li>\n\t<li>03-Evaluation:&nbsp;This folder contains the scripts used to calculate the competition&nbsp;metric, the 75th percentile on the 578 evaluation points. The ground&nbsp;truth is also provided in MatLab format and as a&nbsp;CSV file. Since the&nbsp;results must be provided with a 2Hz freq. starting from apptimestamp 0,&nbsp;the GT includes the closest timestamp matching the timing provided&nbsp;by competitors.</li>\n</ol>\n\n<p><strong>Please, cite the following works when using the&nbsp;datasets included in this package:</strong></p>\n\n<ul>\n\t<li>Torres-Sospedra, J.; Jim&eacute;nez, A.; Knauth, A.; Moreira, A.; Beer, Y.; Fetzer, T.;&nbsp;Ta, V.-C.; Montoliu, R.; Seco, F.; Mendoza, G.; Belmonte, O.; Koukofikis,&nbsp;A.; Nicolau, M.J.; Costa, A.; Meneses, F.; Ebner, F.; Deinzer, F.; Vaufreydaz, D.;&nbsp;Dao, T.-K.; and Castelli, E.&nbsp;The Smartphone-based Off-Line Indoor Location&nbsp;Competition at IPIN 2016: Analysis and Future work Sensors Vol. 17(3), 2017.&nbsp;<a href=\"\"></a></li>\n\t<li>Jimenez, A.R.; Mendoza-Silva, G.M.; Montoliu, R.; Seco, F.; Torres-Sospedra, J.&nbsp;Datasets and Supporting Materials for the IPIN 2016 Competition Track 3 (Smartphone-based, off-site).&nbsp;<a href=\"\"></a></li>\n</ul>\n\n<p><strong>Additional information can be found at:</strong></p>\n\n<ul>\n\t<li><a href=\"\"></a></li>\n\t<li><a href=\"\"></a>&nbsp; &nbsp;&nbsp;</li>\n</ul>\n\n<p><strong>For any further questions about the database and this competition track, please contact:&nbsp;</strong></p>\n\n<ul>\n\t<li>Joaqu&iacute;n Torres (<a href=\"\"></a>) Institute of New Imaging Technologies, Universitat Jaume I, Spain.&nbsp;</li>\n\t<li>Antonio R. Jim&eacute;nez (<a href=\"\"></a>) Center of Automation and Robotics (CAR)-CSIC/UPM, Spain.&nbsp;</li>\n</ul>\n\n<p>&nbsp; &nbsp;&nbsp;</p>", 
  "author": [
      "family": "Antonio Ram\u00f3n Jimenez Ruiz"
      "family": "Germ\u00e1n Mart\u00edn Mendoza-Silva"
      "family": "Raul Montoliu"
      "family": "Fernando Seco"
      "family": "Joaqu\u00edn Torres-Sospedra"
  "note": "We would like to thank Tecnalia Research &amp; Innovation Foundation for sponsoring\u00a0the competition track with an award for the winning team. We are also grateful\u00a0to Francesco Potort\u00ec, Sangjoon Park, Jes\u00fas Ure\u00f1a and Kyle O'Keefe for their invaluable help in promoting the IPIN competition and conference. Parts of this work was carried out with the financial support received from projects and grants: LORIS (TIN2012-38080-C04-04), TARSIUS (TIN2015-71564-C4-2-R (MINECO/FEDER)),\u00a0SmartLoc (CSIC-PIE Ref.201450E011), \"Metodolog\u00edas avanzadas para el dise\u00f1o,\u00a0desarrollo, evaluaci\u00f3n e integraci\u00f3n de algoritmos de localizaci\u00f3n en interiores\" (TIN2015-70202-P), REPNIN network (TEC2015-71426-REDT) and the Jos\u00e9 Castillejo mobility grant (CAS16/00072).", 
  "version": "1.0", 
  "type": "dataset", 
  "id": "2791530"
All versions This version
Views 546546
Downloads 148148
Data volume 21.8 GB21.8 GB
Unique views 482482
Unique downloads 110110


Cite as