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A model change detection approach to dynamic scene modeling

By Seon Joo, Kim Gianfranco, Doretto Jens, Rittscher Peter, Tu Nils and Krahnstoever Marc Pollefeys


Abstract—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. Keywords-dynamic scene modeling, PTZ camera, focus-ofattention, background modeling, sequential generalized likelihood ratio, model change detection, linear dynamical systems, dynamic textures. I

Year: 2013
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