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 …

Fall event, as one of the greatest risks to the elderly, its detection has been a hot research
issue in the solitary scene in recent years. Nevertheless, most current researches are …

Foreground detection (FD) plays an important role in the domain of video surveillance for
highway. The design of advanced FD algorithms requires large-scale and diverse video …

Using dynamic surveillance cameras for security has significantly increased the privacy
concerns for captured individuals. Malicious users may misuse these videos by performing …

Low-rank plus sparse matrix decomposition (LSD) is an important problem in computer
vision and machine learning. It has been solved using convex relaxations of the matrix rank …

A roadside sensing unit can provide over-the-horizon perception information for
autonomous vehicles due to its high perception perspective. However, numerous …

Recently, some successful applications used by robust principal component analysis
(RPCA) have boosted the exploration of pattern recognition, especially for moving object …

Real-time moving object detection is challenging for moving cameras due to the moving
background. Many studies use homography matrix to compensate for global motion by …

The analysis of streaming PCA has gained significant traction through the analysis of an
early simple variant: Oja's algorithm, which implements online projected gradient descent for …