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Machine Vision and Applications
Erschienen in: Machine Vision and Applications 5/2014

01.07.2014 | Special Issue Paper

Background modeling in the maritime domain

verfasst von: Domenico D. Bloisi, Andrea Pennisi, Luca Iocchi

Erschienen in: Machine Vision and Applications | Ausgabe 5/2014

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Abstract

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, an appropriate background model has to deal with gradual and sudden illumination changes, camera jitter, shadows, and reflections that can provoke false detections. Using a predefined distribution (e.g., Gaussian) for generating the background model can result ineffective, due to the need of modeling non-regular patterns. In this paper, a method for creating a “discretization” of an unknown distribution that can model highly dynamic background such as water is described. A quantitative evaluation carried out on two publicly available datasets of videos and images, containing data recorded in different maritime scenarios, with varying light and weather conditions, demonstrates the effectiveness of the approach.
Vorheriger Artikel Scene appearance model based on spatial prediction
Nächster Artikel Dynamic image mosaic via SIFT and dynamic programming

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Fußnoten
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Metadaten
Titel
Background modeling in the maritime domain
verfasst von
Domenico D. Bloisi
Andrea Pennisi
Luca Iocchi
Publikationsdatum
01.07.2014
Verlag
Springer Berlin Heidelberg
Erschienen in
Machine Vision and Applications / Ausgabe 5/2014
Print ISSN: 0932-8092
Elektronische ISSN: 1432-1769
DOI
https://doi.org/10.1007/s00138-013-0554-5

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