Satellite and Underwater Sonar Image Matching Using Deep Learning - Santos, Matheus; Giacomo, Giovanni; Drews, Paulo; Botelho, Silvia (Anais do Simpósio Brasileiro de Robótica e Simpósio Latino Americano de Robótica (SBR/LARS); 2019: Anais do VII Simpósio Brasileiro de Robótica e XVI Simpósio Latino Americano de Robótica, 2019)
Aerial images provide rich information about the Earth surface, while underwater perception is severely limited due to the physical characteristic of water. This work proposes a new problem domain where a matching process fuses aerial and underwater images. The proposal is designed to aid underwater navigation in partially structured environments such as marinas and harbors. A pipeline combining image processing techniques and Convolutional Neural Networks is presented. The method is validated in a real dataset with quantitative and qualitative results.