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Hierarchical background model.
The most common ones are adaptive Gaussian mixture [2 10], non-parametric background [11 17], temporal differencing [18 20], warping background [21] and hierarchical background [22] models.
Some variations are computationally intensive Hierarchical background model [22, 66 68] High Low to moderate Make use of both block-based and pixel-based approaches.
Chen et al. [6] suggested a hierarchical background model based on the fact that the background images consist of different objects whose conditions may change frequently.
Chen et al. [22] proposed a hierarchical background model, which is based on region segmentation and pixel descriptors to detect and track foreground.
To address these issues, a hierarchical background modeling and subtraction [3] and a self-adaptive background matching method [4] have been proposed.
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Background: Hierarchical Bayesian methods have been used in previous papers to estimate national mean effects of air pollutants on daily deaths in time-series analyses.
For example, a study of a multinational pharmaceutical company revealed that leaders in its U.S. subsidiary's networks were skewed to "familiar" faces: people from similar functional backgrounds, hierarchical levels, and cultural and gender groups.
Background: Descriptive hierarchical Poisson models and population-genetic coalescent mixture models are used to describe the observed variation in single-nucleotide polymorphism (SNP) density from samples of size two across the human genome.
This represents a significantly greater overlap than expected by chance (one-tailed Fisher Exact test, p = 0.0009), and suggests that these 501 transcripts are consistently regulated regardless of differences in genetic background (though hierarchical clustering still demonstrates that individuals cluster based on colony-level differences; data not shown).
Both solvers operate on different Cartesian hierarchical meshes sharing a common background grid level through which they are connected.
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