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 …

To address the challenges of change detection in the wild, we present a novel background
subtraction algorithm based on parallel vision and Bayesian generative adversarial …

Moving object detection is the foundation of research in many computer vision fields. In
recent decades, a number of detection methods have been proposed. Relevant surveys …

Background subtraction is a crucial stage in many visual surveillance systems. The prime
objective of any such system is to detect local changes, and the system could be utilized to …

Background modeling is a major prerequisite for a variety of multimedia applications like
video surveillance, traffic monitoring, etc. Numerous approaches have been proposed for …

In this paper 1, we investigate cross-scene video foreground segmentation via supervised
and unsupervised model communication. Traditional unsupervised background subtraction …

Background modeling is a crucial step in various computer vision applications such as video
surveillance, object tracking, and moving object detection. Classifying image pixels as …

Moving foreground detection is a very important step for many applications such as human
behavior analysis for visual surveillance, model-based action recognition, road traffic …

Foreground segmentation is an essential processing phase in several change detection-
based applications. Classical foreground segmentation is highly dependent on the accuracy …

Background subtraction is an important step involved in solving computer vision problems.
This paper proposes a novel background subtraction method with fully residual …