Cargando…
Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices
As one of the most promising technologies for next-generation mobile platforms, Augmented Reality (AR) has the potential to radically change the way users interact with real environments enriched with various digital information. To achieve this potential, it is of fundamental importance to track an...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320911/ https://www.ncbi.nlm.nih.gov/pubmed/35891058 http://dx.doi.org/10.3390/s22145382 |
_version_ | 1784755908877746176 |
---|---|
author | Marino, Emanuele Bruno, Fabio Barbieri, Loris Lagudi, Antonio |
author_facet | Marino, Emanuele Bruno, Fabio Barbieri, Loris Lagudi, Antonio |
author_sort | Marino, Emanuele |
collection | PubMed |
description | As one of the most promising technologies for next-generation mobile platforms, Augmented Reality (AR) has the potential to radically change the way users interact with real environments enriched with various digital information. To achieve this potential, it is of fundamental importance to track and maintain accurate registration between real and computer-generated objects. Thus, it is crucially important to assess tracking capabilities. In this paper, we present a benchmark evaluation of the tracking performances of some of the most popular AR handheld devices, which can be regarded as a representative set of devices for sale in the global market. In particular, eight different next-gen devices including smartphones and tablets were considered. Experiments were conducted in a laboratory by adopting an external tracking system. The experimental methodology consisted of three main stages: calibration, data acquisition, and data evaluation. The results of the experimentation showed that the selected devices, in combination with the AR SDKs, have different tracking performances depending on the covered trajectory. |
format | Online Article Text |
id | pubmed-9320911 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93209112022-07-27 Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices Marino, Emanuele Bruno, Fabio Barbieri, Loris Lagudi, Antonio Sensors (Basel) Article As one of the most promising technologies for next-generation mobile platforms, Augmented Reality (AR) has the potential to radically change the way users interact with real environments enriched with various digital information. To achieve this potential, it is of fundamental importance to track and maintain accurate registration between real and computer-generated objects. Thus, it is crucially important to assess tracking capabilities. In this paper, we present a benchmark evaluation of the tracking performances of some of the most popular AR handheld devices, which can be regarded as a representative set of devices for sale in the global market. In particular, eight different next-gen devices including smartphones and tablets were considered. Experiments were conducted in a laboratory by adopting an external tracking system. The experimental methodology consisted of three main stages: calibration, data acquisition, and data evaluation. The results of the experimentation showed that the selected devices, in combination with the AR SDKs, have different tracking performances depending on the covered trajectory. MDPI 2022-07-19 /pmc/articles/PMC9320911/ /pubmed/35891058 http://dx.doi.org/10.3390/s22145382 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Marino, Emanuele Bruno, Fabio Barbieri, Loris Lagudi, Antonio Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title | Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title_full | Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title_fullStr | Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title_full_unstemmed | Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title_short | Benchmarking Built-In Tracking Systems for Indoor AR Applications on Popular Mobile Devices |
title_sort | benchmarking built-in tracking systems for indoor ar applications on popular mobile devices |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9320911/ https://www.ncbi.nlm.nih.gov/pubmed/35891058 http://dx.doi.org/10.3390/s22145382 |
work_keys_str_mv | AT marinoemanuele benchmarkingbuiltintrackingsystemsforindoorarapplicationsonpopularmobiledevices AT brunofabio benchmarkingbuiltintrackingsystemsforindoorarapplicationsonpopularmobiledevices AT barbieriloris benchmarkingbuiltintrackingsystemsforindoorarapplicationsonpopularmobiledevices AT lagudiantonio benchmarkingbuiltintrackingsystemsforindoorarapplicationsonpopularmobiledevices |