Change detection based on remote sensing (RS) data is an important method of detecting
changes on the Earth's surface and has a wide range of applications in urban planning …

Robust and efficient vehicle detection is an important task of environment perception of
intelligent vehicles, which directly affects the behavior decision-making and motion planning …

Given a monocular video, segmenting and decoupling dynamic objects while recovering the
static environment is a widely studied problem in machine intelligence. Existing solutions …

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 …

Principal component analysis (PCA) is one of the most widely used dimension reduction
techniques. A related easier problem is termed subspace learning or subspace estimation …

In this work, we present a novel background subtraction from video sequences algorithm
that uses a deep Convolutional Neural Network (CNN) to perform the segmentation. With …

Several methods have been proposed to solve moving objects segmentation problem
accurately in different scenes. However, many of them lack the ability of handling various …

Foreground/background segmentation via change detection in video sequences is often
used as a stepping stone in high-level analytics and applications. Despite the wide variety of …

With the increasing number of machine learning methods used for segmenting images and
analyzing videos, there has been a growing need for large datasets with pixel accurate …