Computer vision applications based on videos often require the detection of moving objects
in their first step. Background subtraction is then applied in order to separate the background …

Data clustering is the process of identifying natural groupings or clusters within
multidimensional data based on some similarity measure. Clustering is a fundamental …

Background subtraction is a common computer vision task. We analyze the usual pixel-level
approach. We develop an efficient adaptive algorithm using Gaussian mixture probability …

We analyze the computer vision task of pixel-level background subtraction. We present
recursive equations that are used to constantly update the parameters of a Gaussian mixture …

This paper reports the results of a recently concluded R&D project, SCALS (Smart Cities
Adaptive Lighting System), which aimed at the development of all hardware/software …

Foreground detection methods can be applied to efficiently distinguish foreground objects
including moving or static objects from background which is very important in the application …

Background subtraction techniques are often treated as fundamental and significant ways to
analyze and understand video content. In this paper, we propose a weight-sample-based …

Ensemble learning models have been widely used for wind power forecasting to facilitate
efficient dispatching of power systems. However, traditional ensemble methods cannot …

Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …

This paper is concerned with an important issue in finite mixture modeling, the selection of
the number of mixing components. A new penalized likelihood method is proposed for finite …