Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/91528
Registo completo
Campo DC | Valor | Idioma |
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dc.contributor.author | Roriz, Ricardo João Rei | por |
dc.contributor.author | Silva, Heitor | por |
dc.contributor.author | Dias, Francisco | por |
dc.contributor.author | Gomes, Tiago Manuel Ribeiro | por |
dc.date.accessioned | 2024-05-24T14:48:00Z | - |
dc.date.available | 2024-05-24T14:48:00Z | - |
dc.date.issued | 2024-05-17 | - |
dc.identifier.citation | Roriz, R.; Silva, H.; Dias, F.; Gomes, T. A Survey on Data Compression Techniques for Automotive LiDAR Point Clouds. Sensors 2024, 24, 3185. https://doi.org/10.3390/s24103185 | por |
dc.identifier.issn | 1424-8220 | - |
dc.identifier.uri | https://hdl.handle.net/1822/91528 | - |
dc.description.abstract | In the evolving landscape of autonomous driving technology, Light Detection and Ranging (LiDAR) sensors have emerged as a pivotal instrument for enhancing environmental perception. They can offer precise, high-resolution, real-time 3D representations around a vehicle, and the ability for long-range measurements under low-light conditions. However, these advantages come at the cost of the large volume of data generated by the sensor, leading to several challenges in transmission, processing, and storage operations, which can be currently mitigated by employing data compression techniques to the point cloud. This article presents a survey of existing methods used to compress point cloud data for automotive LiDAR sensors. It presents a comprehensive taxonomy that categorizes these approaches into four main groups, comparing and discussing them across several important metrics. | por |
dc.description.sponsorship | This work has been supported by FCT— Fundação para a Ciência e Tecnologia within the R&D Units Project Scope UIDB/00319/2020 and Grant 2021.06782.BD. | por |
dc.language.iso | eng | por |
dc.publisher | Multidisciplinary Digital Publishing Institute (MDPI) | por |
dc.relation | info:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F00319%2F2020/PT | por |
dc.relation | info:eu-repo/grantAgreement/FCT/POR_NORTE/2021.06782.BD/PT | por |
dc.rights | openAccess | por |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | por |
dc.subject | Survey | por |
dc.subject | Data compression | por |
dc.subject | LiDAR | por |
dc.subject | Perception system | por |
dc.subject | Autonomous driving | por |
dc.title | A survey on data compression techniques for automotive LiDAR point clouds | por |
dc.type | article | por |
dc.peerreviewed | yes | por |
dc.relation.publisherversion | https://www.mdpi.com/1424-8220/24/10/3185 | por |
oaire.citationStartPage | 1 | por |
oaire.citationEndPage | 31 | por |
oaire.citationIssue | 10 | por |
oaire.citationVolume | 24 | por |
dc.identifier.doi | 10.3390/s24103185 | por |
dc.subject.fos | Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informática | por |
sdum.journal | Sensors | por |
oaire.version | VoR | por |
dc.identifier.articlenumber | 3185 | por |
dc.subject.ods | Indústria, inovação e infraestruturas | por |
Aparece nas coleções: | CAlg - Artigos em revistas internacionais / Papers in international journals |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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sensors-24-03185.pdf | 4,76 MB | Adobe PDF | Ver/Abrir |
Este trabalho está licenciado sob uma Licença Creative Commons