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Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Datasets and Supporting Materials for the IPIN 2024 Competition Track 3 (Smartphone-based, off-site)

Authors: Torres Sospedra, Joaquin; Crivello, Antonino; Stahlke, Maximilian; Potortì, Francesco; Ortiz, Miguel; Li, Ziyou; Perez-Navarro, Antoni; +1 Authors

Datasets and Supporting Materials for the IPIN 2024 Competition Track 3 (Smartphone-based, off-site)

Abstract

This package contains the datasets and supplementary materials used in the IPIN 2024 Competition. Contents Track-3_TA-2024.pdf: Technical annex describing the competition (Version 1) 01 Logfiles: This folder contains a subfolder with the 54 training trials, a subfolder with the 4 testing trials (validation), and a subfolder with the 2 blind scoring trials (test) 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 we used to calculate the competition metric, the 75th percentile on the 69 evaluation points. It requires the Matlab Mapping Toolbox. We also provide the ground truth as 2 CSV files. It contains samples of reported estimations and the corresponding results. We provide additional information on the competition at: https://competition.ipin-conference.org/2024/call-for-competition Citation Policy Please cite the following works when using the datasets included in this package: Torres-Sospedra, J.; et al. Datasets and Supporting Materials for the IPIN 2024Competition Track 3 (Smartphone-based, off-site), Zenodo 2024http://dx.doi.org/10.5281/zenodo.13931119 Check the updated citation policy at: http://dx.doi.org/10.5281/zenodo.13931119 Contact For any further questions about the database and this competition track, please contact: Joaquín Torres-Sospedra Departament d'Informatica, Universitat de València, 46100 Burjassot, SpainValgrAI - Valencian Graduate School and Research Network of Artificial Intelligence, Camí de Vera s/n, 46022 Valencia, SpainJoaquin.Torres@uv.es - info@jtorr.es Antonio R. Jiménez Centre of Automation and Robotics (CAR)-CSIC/UPM, Spain antonio.jimenez@csic.es Antoni Pérez-NavarroFaculty of Computer Sciences, Multimedia and Telecommunication, Universitat Oberta de Catalunya, Barcelona, Spainaperezn@uoc.edu Acknowledgements We thank Maximilian Stahlke and Christopher Mutschler at Fraunhofer ISS, as well as Miguel Ortiz and Ziyou Li at Université Gustave Eiffel, for their invaluable support in collecting the datasets. And last but certainly not least, Antonino Crivello and Francesco Potortì for their huge effort in georeferencing the competition venue and evaluation points. We extend our appreciation to the staff at the Museum for Industrial Culture (Museum Industriekultur) for their unwavering patience and invaluable support throughout our collection days. We are also grateful to Francesco Potortì, the ISTI-CNR team (Paolo, Michele & Filippo), and the Fraunhofer IIS team (Chris, Tobi, Max, ...) for their invaluable commitment to organizing and promoting the IPIN competition. This work and competition are part of the IPIN 2023 Conference in Nuremberg (Germany) and the IPIN 2024 Conference in Hong Kong. Parts of this work received the financial support received from projects and grants: POSITIONATE (CIDEXG/2023/17, Conselleria d’Educació, Universitats i Ocupació, Generalitat Valenciana) ORIENTATE (H2020-MSCA-IF-2020, Grant Agreement 101023072) GeoLibero (from CYTED) INDRI (MICINN, ref. PID2021-122642OB-C42, PID2021-122642OB-C43, PID2021-122642OB-C44, MCIU/AEI/FEDER UE) MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE) TARSIUS (TIN2015-71564-C4-2-R, MINECO/FEDER) SmartLoc(CSIC-PIE Ref.201450E011) LORIS (TIN2012-38080-C04-04)

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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