[HTML][HTML] Crowd anomaly detection in video frames using fine-tuned AlexNet model
This study proposed an AlexNet-based crowd anomaly detection model in the video (image
frames). The proposed model was comprised of four convolution layers (CLs) and three …
frames). The proposed model was comprised of four convolution layers (CLs) and three …
[HTML][HTML] A hybrid deep learning and visualization framework for pushing behavior detection in pedestrian dynamics
Crowded event entrances could threaten the comfort and safety of pedestrians, especially
when some pedestrians push others or use gaps in crowds to gain faster access to an event …
when some pedestrians push others or use gaps in crowds to gain faster access to an event …
Texture classification-based feature processing for violence-based anomaly detection in crowded environments
Anomaly detection from video surveillance inputs helps to improve security in crowded
places and outdoors. The captured image is analyzed to identify human faces, objects, and …
places and outdoors. The captured image is analyzed to identify human faces, objects, and …
[HTML][HTML] Crowd density level estimation and anomaly detection using multicolumn multistage bilinear convolution attention network (MCMS-BCNN-Attention)
E Ekanayake, Y Lei, C Li - Applied Sciences, 2022 - mdpi.com
The detection of crowd density levels and anomalies is a hot topic in video surveillance.
Especially in human-centric action and activity-based movements. In some respects, the …
Especially in human-centric action and activity-based movements. In some respects, the …
Anomalous event detection and localization in dense crowd scenes
Recognizing and localizing anomalous events in crowd scenes is a challenging problem
that has attracted the attention of researchers in computer vision. Surveillance cameras …
that has attracted the attention of researchers in computer vision. Surveillance cameras …
Deep crowd anomaly detection: state-of-the-art, challenges, and future research directions
MH Sharif, L Jiao, CW Omlin - arXiv preprint arXiv:2210.13927, 2022 - arxiv.org
Crowd anomaly detection is one of the most popular topics in computer vision in the context
of smart cities. A plethora of deep learning methods have been proposed that generally …
of smart cities. A plethora of deep learning methods have been proposed that generally …
A data-driven approach for road accident detection in surveillance videos
The use of machine learning and computer vision techniques for detecting road accidents is
a challenging task due to the limited availability of accident data for training. Staging fake …
a challenging task due to the limited availability of accident data for training. Staging fake …
[PDF][PDF] An integrated multi-level feature fusion framework for crowd behaviour prediction and analysis
MY Murthygowda, RG Krishnegowda… - Indonesian Journal of …, 2023 - academia.edu
The uncontrolled outburst in population has led to crowd gatherings in various public places
causing panic and disaster in certain unpleasant and extreme conditions. A study on the …
causing panic and disaster in certain unpleasant and extreme conditions. A study on the …
A cloud-based deep learning framework for early detection of pushing at crowded event entrances
Crowding at the entrances of large events may lead to critical and life-threatening situations,
particularly when people start pushing each other to reach the event faster. Automatic and …
particularly when people start pushing each other to reach the event faster. Automatic and …
IA-SSLM: irregularity-aware semi-supervised deep learning model for analyzing unusual events in crowds
AS Aljaloud, H Ullah - IEEE Access, 2021 - ieeexplore.ieee.org
Analyzing unusual events is significantly important for video surveillance to ensure people
safety. These events are characterized by irregular patterns that do not conform to the …
safety. These events are characterized by irregular patterns that do not conform to the …