Moving object detection is vitally used in video surveillance applications. Traditional
Gaussian mixture model (GMM) based background subtraction (BGS) methods are usually …

Gaussian mixture models (GMM) is a widely used approach for background modeling.
However, computational barriers have limited its usage in real-time video processing …

The background subtraction (BS) method is one of the most commonly used components in
the detection of moving objects in computer vision systems, in which moving objects in …

Moving object detection is critical task in video analytics. Gaussian Mixture Model (GMM)
based background subtraction is widely popular technique for moving object detection due …

Gaussian Mixture Model background subtraction (GMM) method is nowadays used in many
moving object detection applications. This common approach is performed statistically on …

Gaussian mixture models (GMM) is used to represent the dynamic background in a
surveillance video to detect the moving objects automatically. All the existing GMM based …

Moving object detection is an important feature for video surveillance based applications.
Many background subtraction methods are available for object detection. Gaussian mixture …

Foreground object detection in video is a fundamental step for automated video surveillance
system and many computer vision applications. Mostly moving foreground object is detected …

Detection of moving objects is an important and difficult task in video surveillance systems.
Background subtraction using Gaussian Mixture Model (GMM) is a widely used approach for …

Background subtraction is an essential technique for moving object segmentation in vision
surveillance system. To acquire an exact background, Gaussian mixture modeling (GMM) is …