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 subtraction is an effective method of choice when it comes to detection of
moving objects in videos and has been recognized as a breakthrough for the wide range of …

Background subtraction (BS) is a crucial step in many computer vision systems, as it is first
applied to detect moving objects within a video stream. Many algorithms have been …

Background subtraction is an active research topic due to its great utility on many video
analysis applications. In this work, a new approach for background subtraction employing an …

In this work, to effectively detect moving objects in a fixed camera scene, we propose a novel
background subtraction framework employing diverse cues: pixel texture, pixel color and …

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

Background subtraction is one of the key techniques for automatic video analysis, especially
in the domain of video surveillance. Although its importance, evaluations of recent …

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 …

Moving object detection is a critical task for many computer vision applications: the objective
is the classification of the pixels in the video sequence into either foreground or background …

The availability of an initial background model that describes the scene without foreground
objects is the prerequisite for a wide range of applications, ranging from video surveillance …