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 …
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 …
An empirical review of deep learning frameworks for change detection: Model design, experimental frameworks, challenges and research needs
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 …
Deep learning model for real-time image compression in Internet of Underwater Things (IoUT)
Recently, the advancements of Internet-of-Things (IoT) have expanded its application in
underwater environment which leads to the development of a new field of Internet of …
underwater environment which leads to the development of a new field of Internet of …
Finely-grained annotated datasets for image-based plant phenoty**
Image-based approaches to plant phenoty** are gaining momentum providing fertile
ground for several interesting vision tasks where fine-grained categorization is necessary …
ground for several interesting vision tasks where fine-grained categorization is necessary …
Background subtraction for moving object detection: explorations of recent developments and challenges
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 …
Detection of marine animals in a new underwater dataset with varying visibility
The increasing demand for marine monitoring calls for robust automated systems to support
researchers in gathering information from marine ecosystems. This includes computer vision …
researchers in gathering information from marine ecosystems. This includes computer vision …
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 …
Challenges for future robotic sorters of mixed industrial waste: A survey
To achieve recycling of mixed industrial waste toward an advanced sustainable society,
waste sorting automation through robots is crucial and urgent. For this purpose, a robot is …
waste sorting automation through robots is crucial and urgent. For this purpose, a robot is …
Accelerating species recognition and labelling of fish from underwater video with machine-assisted deep learning
D Marrable, K Barker, S Tippaya, M Wyatt… - Frontiers in Marine …, 2022 - frontiersin.org
Machine-assisted object detection and classification of fish species from Baited Remote
Underwater Video Station (BRUVS) surveys using deep learning algorithms presents an …
Underwater Video Station (BRUVS) surveys using deep learning algorithms presents an …