Going deeper with CNN in malicious crowd event classification
Terror attacks are often targeted towards the civilians gathered in one location (eg, Boston
Marathon bombing). Distinguishing such'malicious' scenes from the'normal'ones, which are …
Marathon bombing). Distinguishing such'malicious' scenes from the'normal'ones, which are …
Exploitation of semantic keywords for malicious event classification
Learning an event classifier is challenging when the scenes are semantically different but
visually similar. However, as humans, we typically handle such tasks painlessly by adding …
visually similar. However, as humans, we typically handle such tasks painlessly by adding …
A novel multi-scale violence and public gathering dataset for crowd behavior classification
A Elzein, E Basaran, YD Yang… - Frontiers in Computer …, 2024 - frontiersin.org
Dependable utilization of computer vision applications, such as smart surveillance, requires
training deep learning networks on datasets that sufficiently represent the classes of interest …
training deep learning networks on datasets that sufficiently represent the classes of interest …
Real-time crowd behavior recognition in surveillance videos based on deep learning methods
F Rezaei, M Yazdi - Journal of Real-Time Image Processing, 2021 - Springer
Automatic video surveillance in public crowded places has been an active research area for
security purposes. Traditional approaches try to solve the crowd behavior recognition task …
security purposes. Traditional approaches try to solve the crowd behavior recognition task …
Abnormal event recognition in crowd environments
Recently, there has been a surge of interest in the computer vision community on automated
crowd scene analysis; as a result, crowd behavior detection and recognition are topics of …
crowd scene analysis; as a result, crowd behavior detection and recognition are topics of …
Abnormal behavior learning based on edge computing toward a crowd monitoring system
Abnormal behavior poses a great threat to social security and stability. The resulting
violence or crime leads to terrible consequences. How to utilize reasonable means to predict …
violence or crime leads to terrible consequences. How to utilize reasonable means to predict …
Conditional autoregressive-tunicate swarm algorithm based generative adversarial network for violent crowd behavior recognition
Violent crowd behavior detection has gained significant attention in the computer vision
system. Diverse crowd behavior detection approaches are introduced to detect violent …
system. Diverse crowd behavior detection approaches are introduced to detect violent …
A very deep two-stream network for crowd type recognition
X Wei, J Du, Z Xue, M Liang, Y Geng, X Xu, JM Lee - Neurocomputing, 2020 - Elsevier
Crowd type identification is a crucial task in the emergency alert. In this paper, to solve
accurate identification of crowd type, the crowd type description triad C-BMO< Behavior …
accurate identification of crowd type, the crowd type description triad C-BMO< Behavior …
Crowd video event classification using convolutional neural network
SJ Shri, S Jothilakshmi - Computer Communications, 2019 - Elsevier
Abstract Crowd Event Classification in videos is an important and challenging task in
computer vision based systems. The Crowd Event Classification system recognizes a large …
computer vision based systems. The Crowd Event Classification system recognizes a large …
DOD-CNN: Doubly-injecting object information for event recognition
Recognizing an event in an image can be enhanced by detecting relevant objects in two
ways: 1) indirectly utilizing object detection information within the unified architecture or 2) …
ways: 1) indirectly utilizing object detection information within the unified architecture or 2) …