A Bayesian approach for tracking undersea narrow telecommunication cables
Alberto Ortiz, Javier Antich, Gabriel Oliver · 2009
The surveillance and inspection of underwater installations such as telecommunication cables are currently carried out by trained operators who, from the surface, guide a Remotely Operated Vehicle (ROV) with cameras mounted over it. This manual visual control is, however, a very tedious job that tends to fail if the operator looses concentration. This paper describes a tracking system for underwater narrow telecommunication cables whose main objective is to allow an Autonomous Underwater Vehicle (AUV) to video-document the whole length of a cable. The approach is based on Particle Filters (PF) because of their natural ability to model multi-dimensional multi-modal probability density functions, what allows handling in a more appropriate way the ambiguities which naturally arise from undersea environments. The paper also describes a set of features added to the standard structure of a PF, which successfully compensate some large errors in the cable pose estimation when the non-enhanced tracker is applied. Extensive experimental results over a test set of more than 10,000 frames, for which a ground truth has been manually generated, have shown the usefulness of the solution proposed. Besides, results for a set of six video sequences accounting for almost 150,000 frames and around one hour and a half of successful continuous video tracking are also discussed. All those images come from inspection runs captured by ROVs navigating over real telecommunication undersea cables.