An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2021 - ieeexplore.ieee.org
Visual change detection, aiming at segmentation of video frames into foreground and
background regions, is one of the elementary tasks in computer vision and video analytics …
background regions, is one of the elementary tasks in computer vision and video analytics …
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 …
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 …
Using artificial anomalies to detect unknown and known network intrusions
Intrusion detection systems (IDSs) must be capable of detecting new and unknown attacks,
or anomalies. We study the problem of building detection models for both pure anomaly …
or anomalies. We study the problem of building detection models for both pure anomaly …
Scene independency matters: An empirical study of scene dependent and scene independent evaluation for CNN-based change detection
M Mandal, SK Vipparthi - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Visual change detection in video is one of the essential tasks in computer vision
applications. Recently, a number of supervised deep learning methods have achieved top …
applications. Recently, a number of supervised deep learning methods have achieved top …
Deep background modeling using fully convolutional network
L Yang, J Li, Y Luo, Y Zhao… - IEEE Transactions on …, 2017 - ieeexplore.ieee.org
Background modeling plays an important role for video surveillance, object tracking, and
object counting. In this paper, we propose a novel deep background modeling approach …
object counting. In this paper, we propose a novel deep background modeling approach …
Exploring image generation for UAV change detection
Change detection (CD) is becoming indispensable for unmanned aerial vehicles (| UAVs),
especially in the domain of water landing, rescue and search. However, even the most …
especially in the domain of water landing, rescue and search. However, even the most …
: A Robust Change Detection Method for Intelligent Visual Surveillance
In this paper, we propose a robust change detection method for intelligent visual
surveillance. This method, named M 4 CD, includes three major steps. First, a sample-based …
surveillance. This method, named M 4 CD, includes three major steps. First, a sample-based …
A multi-view learning approach to foreground detection for traffic surveillance applications
This paper proposes an effective multi-view learning approach to foreground detection for
traffic surveillance applications. This approach involves three main steps. First, a reference …
traffic surveillance applications. This approach involves three main steps. First, a reference …
Multi-scale anisotropic Gaussian kernels for image edge detection
In this paper, a new edge detection method is proposed where multi-scale anisotropic
Gaussian kernels (AGKs) are used to obtain an edge map from an input image. The main …
Gaussian kernels (AGKs) are used to obtain an edge map from an input image. The main …