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 …

Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …

The video-based separation of foreground (FG) and background (BG) has been widely
studied due to its vital role in many applications, including intelligent transportation and …

This paper advocates a novel video saliency detection method based on the spatial-
temporal saliency fusion and low-rank coherency guided saliency diffusion. In sharp contrast …

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 …

Within the field of computer vision, change detection algorithms aim at automatically
detecting significant changes occurring in a scene by analyzing the sequence of frames in a …

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 …

In this paper, we present a complete change detection system named multimode
background subtraction. The universal nature of system allows it to robustly handle multitude …

Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …

Background subtraction is often used as the first step in video analysis and smart
surveillance applications. However, the issue of inconsistent performance across different …