Conventional neural networks have been demonstrated to be a powerful framework for
background subtraction in video acquired by static cameras. Indeed, the well-known Self …

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 …

Background modeling for foreground detection is often used in different applications to
model the background and then detect the moving objects in the scene like in video …

Automatic video analysis from urban surveillance cameras is a fast-emerging field based on
computer vision techniques. We present here a comprehensive review of the state-of-the-art …

As technology continues to develop, computer vision (CV) applications are becoming
increasingly widespread in the intelligent transportation systems (ITS) context. These …

Mixture of Gaussians is a widely used approach for background modeling to detect moving
objects from static cameras. Numerous improvements of the original method developed by …

Background modeling is currently used to detect moving objects in video acquired from
static cameras. Numerous statistical methods have been developed over the recent years …

During about 30 years, a lot of research teams have worked on the big challenge of
detection of moving objects in various challenging environments. First applications concern …

Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …

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