EURASIP Journal on Advances in Signal Processing · 2010 · 47 citations · 16 references
ComputingOcean EngineeringComputer VisionMachine VisionRemote SensingBackground ReductionNaval WarfareObject DetectionObject RecognitionRemote Sensing Image AnalysisUnderwater PerceptionBackground SubtractionMaritime Hazard DetectionMine DetectionPhysical PropertiesShipborne Remote SensingSpatial Background ModelingSpectral Background SubtractionUnderwater Image Processing
Ship-based automatic detection of small floating objects on an agitated sea surface remains a hard problem. Our main concern is the detection of floating mines, which proved a real threat to shipping in confined waterways during the first Gulf War, but applications include salvaging, search-and-rescue operation, perimeter, or harbour defense. Detection in infrared (IR) is challenging because a rough sea is seen as a dynamic background of moving objects with size order, shape, and temperature similar to those of the floating mine. In this paper we have applied a selection of background subtraction algorithms to the problem, and we show that the recent algorithms such as ViBe and behaviour subtraction, which take into account spatial and temporal correlations within the dynamic scene, significantly outperform the more conventional parametric techniques, with only little prior assumptions about the physical properties of the scene.
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Proceedings of IEEE Conference on Computer Vision and Pattern Recognition
1993 · 14.3K citations
Adaptive background mixture models for real-time tracking
Chris Stauffer, W. Eric L. Grimson · 2003 · 6.9K citations