Deep neural network concepts for background subtraction: A systematic review and comparative evaluation
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 …
background subtraction in video acquired by static cameras. Indeed, the well-known Self …
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 …
Decomposition into low-rank plus additive matrices for background/foreground separation: A review for a comparative evaluation with a large-scale dataset
Background/foreground separation is the first step in video surveillance system to detect
moving objects. Recent research on problem formulations based on decomposition into low …
moving objects. Recent research on problem formulations based on decomposition into low …
Background subtraction for moving object detection: explorations of recent developments and challenges
R Kalsotra, S Arora - The Visual Computer, 2022 - Springer
Background subtraction, although being a very well-established field, has required
significant research efforts to tackle unsolved challenges and to accelerate the progress …
significant research efforts to tackle unsolved challenges and to accelerate the progress …
[图书][B] Background modeling and foreground detection for video surveillance
Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …
used to detect robustly moving objects in challenging environments. This requires effective …
Online robust dictionary learning
Online dictionary learning is particularly useful for processing large-scale and dynamic data
in computer vision. It, however, faces the major difficulty to incorporate robust functions …
in computer vision. It, however, faces the major difficulty to incorporate robust functions …
Biobench: A benchmark suite of bioinformatics applications
K Albayraktaroglu, A Jaleel, X Wu… - … Analysis of Systems …, 2005 - ieeexplore.ieee.org
Recent advances in bioinformatics and the significant increase in computational power
available to researchers have made it possible to make better use of the vast amounts of …
available to researchers have made it possible to make better use of the vast amounts of …
A novel video dataset for change detection benchmarking
Change detection is one of the most commonly encountered low-level tasks in computer
vision and video processing. A plethora of algorithms have been developed to date, yet no …
vision and video processing. A plethora of algorithms have been developed to date, yet no …
Comparative study of motion detection methods for video surveillance systems
K Sehairi, F Chouireb, J Meunier - Journal of Electronic …, 2017 - spiedigitallibrary.org
The objective of this study is to compare several change detection methods for a monostatic
camera and identify the best method for different complex environments and backgrounds in …
camera and identify the best method for different complex environments and backgrounds in …
Fusion-based foreground enhancement for background subtraction using multivariate multi-model Gaussian distribution
These days, detection of visual attention regions (VAR) such as moving objects have
become an essential pre-processing stage in many computer vision applications. In this …
become an essential pre-processing stage in many computer vision applications. In this …