Background subtraction in real applications: Challenges, current models and future directions

B Garcia-Garcia, T Bouwmans, AJR Silva - Computer Science Review, 2020 - Elsevier
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 …

Video analytics for visual surveillance and applications: An overview and survey

IE Olatunji, CH Cheng - … Learning Paradigms: Applications of Learning and …, 2019 - Springer
Owing to the massive amount of video data being generated as a result of high proliferation
of surveillance cameras, the manpower to monitor such system is relatively expensive …

Vision-based framework for intelligent monitoring of hardhat wearing on construction sites

BE Mneymneh, M Abbas, H Khoury - Journal of Computing in Civil …, 2019 - ascelibrary.org
The construction industry is still considered among the riskiest industries in the world
because workers are continuously exposed to injury from falls, slips, or trips or being struck …

Combination of video change detection algorithms by genetic programming

S Bianco, G Ciocca, R Schettini - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Within the field of computer vision, change detection algorithms aim at automatically
detecting significant changes occurring in a scene by analyzing the sequence of frames in a …

[图书][B] Background modeling and foreground detection for video surveillance

T Bouwmans, F Porikli, B Höferlin, A Vacavant - 2014 - books.google.com
Background modeling and foreground detection are important steps in video processing
used to detect robustly moving objects in challenging environments. This requires effective …

An evaluation of crowd counting methods, features and regression models

D Ryan, S Denman, S Sridharan, C Fookes - Computer Vision and Image …, 2015 - Elsevier
Existing crowd counting algorithms rely on holistic, local or histogram based features to
capture crowd properties. Regression is then employed to estimate the crowd size …

Compressed dynamic mode decomposition for background modeling

NB Erichson, SL Brunton, JN Kutz - Journal of Real-Time Image …, 2019 - Springer
We introduce the method of compressed dynamic mode decomposition (cDMD) for
background modeling. The dynamic mode decomposition is a regression technique that …

How far can you get by combining change detection algorithms?

S Bianco, G Ciocca, R Schettini - … , Catania, Italy, September 11-15, 2017 …, 2017 - Springer
Given the existence of many change detection algorithms, each with its own peculiarities
and strengths, we propose a combination strategy, that we termed IUTIS (In Unity There Is …

Fast background subtraction based on a multilayer codebook model for moving object detection

JM Guo, CH Hsia, YF Liu, MH Shih… - … on Circuits and …, 2013 - ieeexplore.ieee.org
Moving object detection is an important and fundamental step for intelligent video
surveillance systems because it provides a focus of attention for post-processing. A …

ASIC and FPGA implementation of the Gaussian mixture model algorithm for real-time segmentation of high definition video

M Genovese, E Napoli - IEEE transactions on very large scale …, 2013 - ieeexplore.ieee.org
Background identification is a common feature in many video processing systems. This
paper proposes two hardware implementations of the OpenCV version of the Gaussian …