Traditional and recent approaches in background modeling for foreground detection: An overview
T Bouwmans - Computer science review, 2014 - Elsevier
Background modeling for foreground detection is often used in different applications to
model the background and then detect the moving objects in the scene like in video …
model the background and then detect the moving objects in the scene like in video …
On the role and the importance of features for background modeling and foreground detection
Background modeling has emerged as a popular foreground detection technique for various
applications in video surveillance. Background modeling methods have become increasing …
applications in video surveillance. Background modeling methods have become increasing …
Moving object detection in complex scene using spatiotemporal structured-sparse RPCA
Moving object detection is a fundamental step in various computer vision applications.
Robust principal component analysis (RPCA)-based methods have often been employed for …
Robust principal component analysis (RPCA)-based methods have often been employed for …
Spatiotemporal GMM for background subtraction with superpixel hierarchy
We propose a background subtraction algorithm using hierarchical superpixel
segmentation, spanning trees and optical flow. First, we generate superpixel segmentation …
segmentation, spanning trees and optical flow. First, we generate superpixel segmentation …
Product technical life prediction based on multi-modes and fractional Lévy stable motion
Some equipment degradation processes have long-range dependence (LRD) and multi-
modes characteristics. The multi-modes are caused by changes of the external environment …
modes characteristics. The multi-modes are caused by changes of the external environment …
[HTML][HTML] Comprehensive review of models and methods for inferences in bio-chemical reaction networks
The key processes in biological and chemical systems are described by networks of
chemical reactions. From molecular biology to biotechnology applications, computational …
chemical reactions. From molecular biology to biotechnology applications, computational …
[PDF][PDF] Background subtraction for visual surveillance: A fuzzy approach
T Bouwmans - Handbook on soft computing for video surveillance, 2012 - researchgate.net
Background Subtraction for Visual Surveillance Page 1 5 Background Subtraction for Visual
Surveillance: A Fuzzy Approach Thierry Bouwmans University of La Rochelle, La Rochelle …
Surveillance: A Fuzzy Approach Thierry Bouwmans University of La Rochelle, La Rochelle …
Fractional Lévy stable motion: Finite difference iterative forecasting model
In this study we use the fractional Lévy stable motion (fLsm) to establish a finite iterative
forecasting model with Long Range Dependent (LRD) characteristics. The LRD forecasting …
forecasting model with Long Range Dependent (LRD) characteristics. The LRD forecasting …
Expectation–Maximization algorithm for finite mixture of α-stable distributions
Abstract A Gaussian Mixture Model (GMM) is a parametric probability density function built
as a weighted sum of Gaussian distributions. Gaussian mixtures are used for modelling the …
as a weighted sum of Gaussian distributions. Gaussian mixtures are used for modelling the …
An end-to-end deep learning approach for extracting stochastic dynamical systems with α-stable Lévy noise
Recently, extracting data-driven governing laws of dynamical systems through deep
learning frameworks has gained much attention in various fields. Moreover, a growing …
learning frameworks has gained much attention in various fields. Moreover, a growing …