Background Modelling in the Maritime Domain
Domenico D. Bloisi, Andrea Pennisi, Luca Iocchi · 2013
Maritime environment represents a challenging scenario for automatic video surveillance, due to the complexity of the observed scene: waves on the water surface, boat wakes, and weather issues contribute to generate a highly dynamic background. Moreover, gradual and sudden illumination changes (e.g., clouds), motion changes (e.g., camera jitter), and reflections can provoke false detections. An appropriate background model has to deal with all the above mentioned issues. However, using a predefined distribution (e.g., Gaussian) for the creation of the background model can result ineffective, due to the need of modelling nonregular patterns. In this paper, a method for creating a “discretization” of an unknown distribution that can model the highly dynamic background characteristic of the maritime domain is described. A quantitative evaluation carried out on a publicly available dataset of videos and images called MAR Maritime Activity Recognition dataset, containing data recorded in different maritime scenarios, with varying light and weather conditions, demonstrates the effectiveness of the approach.