Utilize este identificador para referenciar este registo:
https://hdl.handle.net/1822/73422
Título: | Polarization-coded material classification in automotive LIDAR aiming at safer autonomous driving implementations |
Autor(es): | Nunes-Pereira, E. J. Peixoto, H. Teixeira, J. Simões, João Henrique Vivas Santos |
Data: | 2020 |
Editora: | Optical Society of America |
Revista: | Applied Optics |
Resumo(s): | LIDAR sensors are one of the key enabling technologies for the wide acceptance of autonomous driving implementations. Target identification is a requisite in image processing, informing decision making in complex scenarios. The polarization from the backscattered signal provides an unambiguous signature for common metallic car paints and can serve as one-point measurement for target classification. This provides additional redundant information for sensor fusion and greatly alleviates hardware requirements for intensive morphological image processing. Industry decision makers should consider polarization-coded LIDAR implementations. Governmental policy makers should consider maximizing the potential for polarization-coded material classification by enforcing appropriate regulatory legislation. Both initiatives will contribute to faster (safer, cheaper, and more widely available) advanced driver-assistance systems and autonomous functions. Polarization-coded material classification in automotive applications stems from the characteristic signature of the source of LIDAR backscattering: specular components preserve the degree of polarization while diffuse contributions are predominantly depolarizing. (C) 2020 Optical Society of America |
Tipo: | Artigo |
URI: | https://hdl.handle.net/1822/73422 |
DOI: | 10.1364/AO.375704 |
ISSN: | 1559-128X |
Versão da editora: | https://www.osapublishing.org/ao/abstract.cfm?uri=ao-59-8-2530 |
Arbitragem científica: | yes |
Acesso: | Acesso restrito UMinho |
Aparece nas coleções: | CDF - FAMO - Artigos/Papers (with refereeing) |
Ficheiros deste registo:
Ficheiro | Descrição | Tamanho | Formato | |
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Appl_Opt_Polarization-Coded_Identification_LIDAR_Rev.pdf Acesso restrito! | 1,4 MB | Adobe PDF | Ver/Abrir |