Abstract Moving Object Segmentation (MOS) is an important topic in computer vision. MOS
becomes a challenging problem in the presence of dynamic background and moving …

Moving object segmentation (MOS) is the process of identifying dynamic objects from video
frames, such as moving vehicles or pedestrians, while discarding the background. It plays …

This article presents a new deep-learning architecture based on an encoder-decoder
framework that retains contrast while performing background subtraction (BS) on thermal …

Detecting foreground objects in video separation tasks is a challenging endeavor in
complex environments. This paper presents a deep neural network architecture considering …

We present two deep unfolding neural networks for the simultaneous tasks of background
subtraction and foreground detection in video. Unlike conventional neural networks based …

Our paper presents robust approaches for all moving object detection processes. First of all,
we propose an automatic and non-parametric method in the segmentation phase based on …

Foreground detection is an essential step in computer vision and video processing. Accurate
foreground object extraction is crucial for subsequent high‐level tasks such as target …

The growing concern over high-profile violence has led to a widespread adoption of
intelligent smart video surveillance systems in educational institutions. However, accurately …

In this paper, we present JanusNet, an efficient CNN model that can perform online
background subtraction and robustly detect moving targets using resource-constrained …

Foliage penetration is an unsolved important part of border surveillance of remote areas
between regular border crossing points. Detecting penetrating objects (eg, persons and …