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 …

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 …

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 …

Moving object detection is a fundamental step in various computer vision applications.
Robust principal component analysis (RPCA)-based methods have often been employed for …

Background estimation and foreground segmentation are important steps in many high-level
vision tasks. Many existing methods estimate background as a low-rank component and …

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 …

The paper provides a specific perspective view on background subtraction for moving object
detection, as a building block for many computer vision applications, being the first relevant …

We face the problem of gait recognition by using a robust deep learning model based on
graphs. The proposed graph based learning approach, named Time based Graph Long …