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New Technique for Extraction Moving Object Based on Active Contours for Intelligent Visual Surveillance Applications

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With the increasing concerns about public and road safety, it has become crucial to have in place sophisticated visual surveillance systems that can detect and locate potentially dangerous situations. In fact, being able to accurately define an object’s pose or location in an image is one of the current challenging research topics and knows many applications. It can be used to monitor traffic, analyse crowd flux statistics and congestion, identify persons, and detect abnormal behaviours. Within this work, we develop an automatic approach that can localise moving objects robustly and accurately in surveillance scenes. The basic approach consists of two major parts: the motion detection and the object localisation based on the active contours technique. The proposed method has been tested on different real urban traffic videos, and the experiment results demonstrate that our algorithm can locate effectively and accurately the moving objects; optimise the results of the localized objects and also decrease the computations load.
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Visual Surveillance; Objects Detection; Objects Localisation; Variational Active Contours; Adaptive Local Energies; Adaptive Regularization

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