Visual Place Recognition for Harbour Infrastructures Inspection

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2023

Autores

Gaspar, AR (Autor) Outra; Nunes, A (Autor) Outra; Aníbal Castilho Coimbra de Matos (Autor) FEUP

Ata de Conferência Internacional

Título: OCEANS 2023 - LIMERICK

OCEANS Conference

Limerick, IRELAND, JUN 05-08, 2023

Indexação

ISI Web of Knowledge - 0 Citações

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00Z-5T1

DOI: 10.1109/oceanslimerick52467.2023.10244576

Abstract (EN): The harbour infrastructures have some structures that still need regular inspection. However, the nature of this environment presents a number of challenges when it comes to determining an accurate vehicle position and consequently performing successful image similarity detection. In addition, the underwater environment is highly dynamic, making place recognition harder because the appearance of a place can change over time. In these close-range operations, the visual sensors have a major impact. There are some factors that degrade the quality of the captured images, but image preprocessing steps are increasingly used. Therefore, in this paper, a purely visual similarity detection with enhancement technique is proposed to overcome the inherent perceptual problems in a port scenario. Considering the lack of available data in this context and to facilitate the variation of environmental parameters, a harbour scenario was simulated using the Stonefish simulator. The experiments were performed on some predefined trajectories containing the poor visibility conditions typical of these scenarios. The place recognition approach improves the performance by up to 10% compared to the results obtained with captured images. In general, it provides a good balance in coping with turbidity and light incidence at low computational cost and achieves a performance of about 80%.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

Nº de páginas: 9