3 accepted papers
Obstacle detection by semantic segmentation shows a great promise for autonomous navigation in unmanned surface vehicles (USV). However, existing methods suffer from poor estimation of the water edge in presence of visual ambiguities, poor detection of small obstacles and high false-positive rate on…
The progress of obstacle detection via semantic segmentation on unmanned surface vehicles (USVs) has been significantly lagging behind the developments in the related field of autonomous cars. The reason is the lack of large curated training datasets from USV domain required for development of data-…
We propose a stereo-based obstacle detection approach for unmanned surface vehicles. Obstacle detection is cast as a scene semantic segmentation problem in which pixels are assigned a probability of belonging to water or non-water regions. We extend a single-view model to a stereo system by adding a…