dc.contributor.author | Mendoza-Silva, Germán Martín | |
dc.contributor.author | Torres-Sospedra, Joaquín | |
dc.contributor.author | Potortì, Francesco | |
dc.contributor.author | Moreira, Adriano | |
dc.contributor.author | Knauth, Stefan | |
dc.contributor.author | Berkvens, Rafael | |
dc.contributor.author | Huerta, Joaquin | |
dc.date.accessioned | 2021-01-22T12:23:57Z | |
dc.date.available | 2021-01-22T12:23:57Z | |
dc.date.issued | 2020-09-04 | |
dc.identifier.citation | MENDOZA-SILVA, Germán Martín, et al. Beyond Euclidean Distance for Error Measurement in Pedestrian Indoor Location. IEEE Transactions on Instrumentation and Measurement, 2020, vol. 70, p. 1-11. | ca_CA |
dc.identifier.issn | 0018-9456 | |
dc.identifier.uri | http://hdl.handle.net/10234/191365 | |
dc.description.abstract | Indoor positioning systems (IPSs) suffer from a
lack of standard evaluation procedures enabling credible comparisons: this is one of the main challenges hindering their
widespread market adoption. Traditionally, accuracy evaluation
is based on positioning errors defined as the Euclidean distance
between the true positions and the estimated positions. While
Euclidean is simple, it ignores obstacles and floor transitions.
In this article, we describe procedures that measure a positioning error defined as the length of the pedestrian path
that connects the estimated position to the true position. The
procedures apply pathfinding on floor maps using visibility
graphs (VGs) or navigational meshes (NMs) for vector maps and
fast marching (FM) for raster maps. Multifloor and multibuilding
paths use the information on vertical in-building communication
ways and outdoor paths. The proposed measurement procedures
are applied to position estimates provided by the IPSs that
participated in the EvAAL-ETRI 2015 competition. Procedures
are compared in terms of pedestrian path realism, indoor model
complexity, path computation time, and error magnitudes. The
VGs algorithm computes shortest distance paths; NMs produce
very similar paths with significantly shorter computation time;
and FM computes longer, more natural-looking paths at the
expense of longer computation time and memory size. The 75th
percentile of the measured error differs among the methods from
2.2 to 3.7 m across the evaluation sets. | ca_CA |
dc.format.extent | 11 p. | ca_CA |
dc.format.mimetype | application/pdf | ca_CA |
dc.language.iso | eng | ca_CA |
dc.publisher | Institute of Electrical and Electronics Engineers | ca_CA |
dc.relation.isPartOf | IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 70, 2021 | ca_CA |
dc.rights | Copyright (c) 2020 IEEE. Personal use is permitted. For any other purposes, permission must be obtained from the IEEE by emailing pubs-permissions@ieee.org | ca_CA |
dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | * |
dc.subject | error measurement | ca_CA |
dc.subject | indoor pathfinding | ca_CA |
dc.subject | indoor positioning system (IPS) evaluation | ca_CA |
dc.subject | Wi-Fi fingerprinting | ca_CA |
dc.title | Beyond Euclidean Distance for Error Measurement in Pedestrian Indoor Location | ca_CA |
dc.type | info:eu-repo/semantics/article | ca_CA |
dc.identifier.doi | https://doi.org/10.1109/TIM.2020.3021514 | |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | ca_CA |
dc.relation.publisherVersion | https://ieeexplore.ieee.org/document/9186638 | ca_CA |
dc.type.version | info:eu-repo/semantics/publishedVersion | ca_CA |