A model change detection approach to dynamic scene modeling

AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance(2009)

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摘要
In this work we propose a dynamic scene model to provide information about the presence of salient motion in the scene, and that could be used for focusing the attention of a pan/tilt/zoom camera, or for background modeling purposes. Rather than proposing a set of saliency detectors, we define what we mean by salient motion, and propose a precise model for it. Detecting salient motion becomes equivalent to detecting a model change. We derive optimal online procedures to solve this problem, which enable a very fast implementation. Promising results show that our model can effectively detect salient motion even in severely cluttered scenes, and while a camera is panning and tilting.
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关键词
salient motion detection,model change detection approach,model change detection,linear dynamical systems,ptz camera,traffic data extraction,traffic lights control,dynamic textures,pan-tilt-zoom camera,salient scene motion,object detection,increasing demand,focus-of-attention,dynamic scene modeling,background modeling,new framework,population evacuation,traffic issue,sequential generalized likelihood ratio,image motion analysis,mathematical model,noise measurement,change detection,noise,computational modeling,dynamics,linear dynamical system
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