Human activity recognition: Review, taxonomy and open challenges
Nowadays, Human Activity Recognition (HAR) is being widely used in a variety of domains,
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
and vision and sensor-based data enable cutting-edge technologies to detect, recognize …
A survey on deep learning-based real-time crowd anomaly detection for secure distributed video surveillance
K Rezaee, SM Rezakhani, MR Khosravi… - Personal and Ubiquitous …, 2024 - Springer
Fast and automated recognizing of abnormal behaviors in crowded scenes is significantly
effective in increasing public security. The traditional procedure of recognizing abnormalities …
effective in increasing public security. The traditional procedure of recognizing abnormalities …
Deep learning-based crowd scene analysis survey
Recently, our world witnessed major events that attracted a lot of attention towards the
importance of automatic crowd scene analysis. For example, the COVID-19 breakout and …
importance of automatic crowd scene analysis. For example, the COVID-19 breakout and …
Spatio-temporal graph-based CNNs for anomaly detection in weakly-labeled videos
H Mu, R Sun, M Wang, Z Chen - Information Processing & Management, 2022 - Elsevier
Abnormal event detection in videos plays an essential role for public security. However,
most weakly supervised learning methods ignore the relationship between the complicated …
most weakly supervised learning methods ignore the relationship between the complicated …
A psychologically inspired fuzzy cognitive deep learning framework to predict crowd behavior
EB Varghese, SM Thampi… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In an intelligent surveillance system, detecting and predicting diverse collective crowd
behaviors has emerged as a challenging problem for efficient crowd management. In real …
behaviors has emerged as a challenging problem for efficient crowd management. In real …
Deep NeuralNet for violence detection using motion features from dynamic images
A Jain, DK Vishwakarma - 2020 third international conference …, 2020 - ieeexplore.ieee.org
Violent Action Recognition has been a challenging topic in monitoring human activities,
especially in public premises. Deep neural nets and Transfer learning have proven highly …
especially in public premises. Deep neural nets and Transfer learning have proven highly …
Synthetic Data for Video Surveillance Applications of Computer Vision: A Review
In recent years, there has been a growing interest in synthetic data for several computer
vision applications, such as automotive, detection and tracking, surveillance, medical image …
vision applications, such as automotive, detection and tracking, surveillance, medical image …
A robust framework to generate surveillance video summaries using combination of zernike moments and r-transform and deep neural network
A huge number of cameras records scenes everywhere, generating enormous bulks of
videos. Processing these huge masses of videos and detection of abnormal object activities …
videos. Processing these huge masses of videos and detection of abnormal object activities …
Video based human crowd analysis using machine learning: a survey
World population has increased manifolds in the last ten years. With the increase in
population at this alarming rate, studying and understanding crowd patterns and their …
population at this alarming rate, studying and understanding crowd patterns and their …
A review of video-based human activity recognition: theory, methods and applications
Video-based human activity recognition (HAR) is an important task in many fields, such as
healthcare monitoring, video surveillance, and sports analysis. This review paper aims to …
healthcare monitoring, video surveillance, and sports analysis. This review paper aims to …