Limit Characterization for Visual Place Recognition in Underwater Scenes

• Type: Article in International Conference Proceedings Book
• Date: 2023

Authors

Gaspar, AR (Author) Other; Nunes, A (Author) Other; Aníbal Castilho Coimbra de Matos (Author) FEUP

Conference proceedings International

Title: Lecture Notes in Networks and Systems

Pages: 65-77

5th Iberian Robotics Conference, ROBOT 2022

23 November 2022 through 25 November 2022

Indexing

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Other information

Authenticus ID: P-00X-KEG

DOI: 10.1007/978-3-031-21065-5_6

Abstract (EN): The underwater environment has some structures that still need regular inspection. However, the nature of this environment presents a number of challenges in achieving accurate vehicle position and consequently successful image similarity detection. Although there are some factors - water turbidity or light attenuation - that degrade the quality of the captured images, visual sensors have shown a strong impact on mission scenarios - close range operations. Therefore, the purpose of this paper is to study whether these data are capable of addressing the aforementioned underwater challenges on their own. Considering the lack of available data in this context, a typical underwater scenario was recreated using the Stonefish simulator. Experiments were conducted on two predefined trajectories containing appearance scene changes. The loop closure situations provided by the bag-of-words (BoW) approach are correctly detected, but it is sensitive to some severe conditions.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 13