Automatic Scene Understanding in the Underwater Environment
- Day - Time: 17 October 2014, h.11:00
- Place: Area della Ricerca CNR di Pisa - Room: C-29
A marine survey is typically performed by multi-sensor platforms capturing data (e.g. optical and acoustic) during experimental missions and implementing suitable data analysis algorithms. These implemented procedures endow the platform with the skill of understanding the environment without human supervision.
In this framework a main goal of the R&D activity carried out consists in the recognition, possibly in real-time, of objects located in the sensed environment.
To this aim the different signals coming from sensors typically installed onboard of oceanographic devices, like autonomous underwater vehicles or remotely operated vehicles, need to be integrated with high level machine learning processes, in order to carry out data understanding. Concerning that, some of the most relevant issues involve i) the recognition of meaningful patterns in the signals, ii) the use of computer vision algorithms to reconstruct the 3D morphology of the scene, iii) the creation of maps of the scene and iv) the improvement of the recognition performance by integrating all the available information.
The described topics are borrowed from the oceanic engineering field but represent an appealing tool also for different marine operators. As an example underwater archaeologists are interested in multi-sensor platforms exploitation in order to map and safeguard wrecks and manmade objects, scattered on the oceans' seabeds.