Background subtraction in real applications: Challenges, current models and future directions
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 …
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 …
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 …
because workers are continuously exposed to injury from falls, slips, or trips or being struck …
Combination of video change detection algorithms by genetic programming
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 …
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
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 …
An evaluation of crowd counting methods, features and regression models
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 …
capture crowd properties. Regression is then employed to estimate the crowd size …
Compressed dynamic mode decomposition for background modeling
We introduce the method of compressed dynamic mode decomposition (cDMD) for
background modeling. The dynamic mode decomposition is a regression technique that …
background modeling. The dynamic mode decomposition is a regression technique that …
How far can you get by combining change detection algorithms?
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 …
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
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 …
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 …
paper proposes two hardware implementations of the OpenCV version of the Gaussian …