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b The result for background modeling.
In [104], an algorithm for background modeling based on spatiotemporal patches especially suited for night outdoor scenes is presented.
Our MISCORE is free from: (i) any assumption on model dependency; and (ii) the use of Markov chain model for background modeling.
Also, multi-Gaussian models are used for background modeling [23].
The use of two or more cameras for background modeling serves to overcome these problems.
Frame-based methods consider spatial configurations as a significant cue for background modeling, such as eigen-background model [4].
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Our proposed approach for background modelling for videos has some similarities with the NL-means algorithm described in [14].
We propose a method for background modelling for videos that are (semi- periodic; i.e. thosemi- periodicme or all of the background in each frame is repeated in at least a few other frames in the video.e
In [13], a non-parametric model is proposed for background modelling, where a kernel-based function is employed to represent the colour distribution of each background pixel.
Besides, the control data is important for background model validation.
For background models estimated from other species, similar results are to be expected.
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