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 …

Abnormal behavior recognition for intelligent video surveillance systems: A review

AB Mabrouk, E Zagrouba - Expert Systems with Applications, 2018 - Elsevier
With the increasing number of surveillance cameras in both indoor and outdoor locations,
there is a grown demand for an intelligent system that detects abnormal events. Although …

Weakly supervised temporal sentence grounding with gaussian-based contrastive proposal learning

M Zheng, Y Huang, Q Chen… - Proceedings of the …, 2022 - openaccess.thecvf.com
Temporal sentence grounding aims to detect the most salient moment corresponding to the
natural language query from untrimmed videos. As labeling the temporal boundaries is labor …

Adaptive focus for efficient video recognition

Y Wang, Z Chen, H Jiang, S Song… - proceedings of the …, 2021 - openaccess.thecvf.com
In this paper, we explore the spatial redundancy in video recognition with the aim to improve
the computational efficiency. It is observed that the most informative region in each frame of …

A survey of appearance models in visual object tracking

X Li, W Hu, C Shen, Z Zhang, A Dick… - ACM transactions on …, 2013 - dl.acm.org
Visual object tracking is a significant computer vision task which can be applied to many
domains, such as visual surveillance, human computer interaction, and video compression …

Multi-level attention networks for visual question answering

D Yu, J Fu, T Mei, Y Rui - Proceedings of the IEEE …, 2017 - openaccess.thecvf.com
Inspired by the recent success of text-based question answering, visual question answering
(VQA) is proposed to automatically answer natural language questions with the reference to …

Sum-product networks: A new deep architecture

H Poon, P Domingos - 2011 IEEE International Conference on …, 2011 - ieeexplore.ieee.org
The key limiting factor in graphical model inference and learning is the complexity of the
partition function. We thus ask the question: what are the most general conditions under …

[HTML][HTML] An analysis of convolutional long short-term memory recurrent neural networks for gesture recognition

E Tsironi, P Barros, C Weber, S Wermter - Neurocomputing, 2017 - Elsevier
In this research, we analyze a Convolutional Long Short-Term Memory Recurrent Neural
Network (CNNLSTM) in the context of gesture recognition. CNNLSTMs are able to …

Learning patterns of activity using real-time tracking

C Stauffer, WEL Grimson - IEEE Transactions on pattern …, 2000 - ieeexplore.ieee.org
Our goal is to develop a visual monitoring system that passively observes moving objects in
a site and learns patterns of activity from those observations. For extended sites, the system …

A survey of advances in vision-based human motion capture and analysis

TB Moeslund, A Hilton, V Krüger - Computer vision and image …, 2006 - Elsevier
This survey reviews advances in human motion capture and analysis from 2000 to 2006,
following a previous survey of papers up to 2000 [TB Moeslund, E. Granum, A survey of …