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The CodeBook is one of the popular real-time background models for moving object detection in a video. However, for some of the complex scenes, it does not achieve satisfactory results due to the lack of an automatic parameters estimation mechanism. In this paper, we present an improved CodeBook model, which is robust in sudden illumination changes and quasi-periodic motions. The major contributions...
The Mixture of Gaussians (MoG) background subtraction model is one of the most popular methods for segmenting moving objects in videos. However, to achieve satisfactory background subtraction results, its parameters need to be hand-tuned specifically for each scenario. This becomes a major obstacle for this model to be employed in real-time applications. This paper proposes a self-adaptive method...
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