1 research outputs found
Maritime targets detection from ground cameras exploiting semi-supervised machine learning
This paper presents a vision-based system for maritime surveillance, using moving PTZ cameras. The proposed
methodology fuses a visual attention method that exploits low-level image features appropriately selected
for maritime environment, with appropriate tracker. Such features require no assumptions about environmental
nor visual conditions. The offline initialization is based on large graph semi-supervised technique in
order to minimize user’s effort. System’s performance was evaluated with videos from cameras placed at Limassol
port and Venetian port of Chania. Results suggest high detection ability, despite dynamically changing
visual conditions and different kinds of vessels, all in real time.peer-reviewe