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With mountain imagery playing in the background, models at Milan Fashion Week appeared in variations on Norwegian patterned knitwear and printed chiffon shirts and dresses.
Simple background models assume static background images.
The program works for arbitrarily defined phases and background models.
We set up both background models with identical parameters except for the learning rate.
A study of some well-known background models can be found in [8 10] and references therein.
Non-parametric background models consider the statistical behaviour of image features to segment the foreground from the background.
Algorithms assuming multimodal background models face the situation where the background appearance oscillates between two or more color ranges.
Based on the spatiotemporal patches, called bricks, the background models are learned by an on-line subspace learning method.
The last known background value is initialized for each pixel after the initialization phase of the background models.
Figure 2 Conventional automatic FVC system based on Gaussian Mixture Model - Universal Background Models (GMM-UBMs), after [ 19 - 21 ].
Therefore, they used two background models with different learning rates, a short-term and a long-term background model.
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