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 segmentation (MOS), aiming at segmenting moving objects from video
frames, is an important and challenging task in computer vision and with various …

Background modeling and subtraction based on change detection are the first step in many
high-level computer vision applications. Many background subtraction methods have been …

Accurate and fast extraction of foreground objects is a key prerequisite for a wide range of
computer vision applications, such as object tracking and recognition. Thus, many …

The complementary nature of color and depth synchronized information acquired by low
cost RGBD sensors poses new challenges and design opportunities in several applications …

The detection of moving objects is one of the key problems in the field of computer vision. It
is very important to detect moving objects accurately and rapidly for automatic driving. In this …

Background subtraction is a significant component of computer vision systems. It is widely
used in video surveillance, object tracking, anomaly detection, etc. A new data source for …

Video object segmentation is a fundamental step in many advanced vision applications.
Most existing algorithms are based on handcrafted features such as HOG, super-pixel …

This study presents a foreground detection method capable of robustly estimating the
background under the presence of dynamic effects. The key contribution of this study is the …

The facial recognition process is normally used to verify and identify individuals, especially
during the process of analyzing facial biometrics. The face detection algorithm automatically …