@article{AarsĂSther_Moan_2010, author = {AarsĂSther, Karl Gunnar and Moan, Torgeir}, title = {Computer Vision and Ship Traffic Analysis: Inferring Maneuver Patterns From the Automatic Identification System}, journal = {TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation}, volume = {4}, number = {3}, pages = {303-308}, year = {2010}, url = {./Article_Computer_Vision_and_Ship_Traffic_AarsĂSther,15,235.html}, abstract = {The Automatic Identification System has proven itself as a valuable source for ship traffic information. Its introduction has reversed the previous situation with scarcity of precise data from ship traffic and has instead posed the reverse challenge of coping with an overabundance of data. The number of time series available for ship manoeuvring analysis has increased from tens, or hundreds, to several thousands. Sifting through this data manually, either to find the salient features of traffic, or to provide statistical distributions of decision variables is an extremely time consuming procedure. In this paper we present the results of applying computer vision techniques to this problem and show how it is possible to automatically separate AIS data in order to obtain traffic statistics and prevailing features down to the scale of individual manoeuvres and how this procedure enables the production of a simplified model of ship traffic.}, issn = {2083-6473}, publisher = {Gdynia Maritime University, Faculty of Navigation}, keywords = {Ship Traffic Analysis, Computer Vision, Automatic Identification System (AIS), Inferring Maneuver Patterns, Manoeuvring, Marine Traffic Control, Matlab, Navigational Aids} }