Detecting abnormal events in traffic video surveillance using superorientation optical flow feature-Reference-Cited by-同舟云学术

Detecting abnormal events in traffic video surveillance using superorientation optical flow feature

Published:2020-06-08 Issue:9 Volume:14 Page:1881-1891
ISSN:1751-9667
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Athanesious Joshan¹,Srinivasan Vasuhi¹,Vijayakumar Vaidehi²,Christobel Shiny³,Sethuraman Sibi Chakkaravarthy⁴

Affiliation:

1. Department of Electronics EngineeringMadras Institute of TechnologyChromepetn, ChennaiIndia

2. Mother Teresa Woman's UniversityKodaikanalIndia

3. Department of Electronics and Communication EngineeringSri Ramakrishna Institute of TechnologyCoimbatoreIndia

4. School of Computer Science and Engineering, Vellore Institute of Technology – Andhra Pradesh (VIT‐AP) UniversityAmaravatiIndia

Funder

Australian Cancer Research Foundation

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/iet-ipr.2019.0549

Reference26 articles.

1. Abnormal event detection and localization in traffic videos based on group sparse topical coding;Parvin A.;IET Image Process.,2016

2. Trajectory based abnormal event detection in video traffic surveillance using general potential data field with spectral clustering;Athanesious J.;Multimed. Tools Appl.,2019

3. Anomaly detection

4. KumaranS.K. DebiP.D. andRoyP.P.: ‘Anomaly detection in road traffic using visual surveillance: a survey’ arXiv preprint arXiv:1901.08292 2019

5. 2015 Int. Conf. on Advanced Computing (ICoAC) Chennai R. Ranjith J. Athanesious V. Vaidehi Anomaly detection using DBSCAN clustering technique for traffic video surveillance 1 6

Cited by 17 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Deep Learning Algorithms for Traffic Forecasting: A Comprehensive Review and Comparison with Classical Ones;Journal of Advanced Transportation;2024-01

2. Autotrack: a framework for query-based vehicle tracking and retrieval from CCTV footages using machine learning at the edge;International Journal of Information Technology;2023-08-24

3. Video anomaly detection system using deep convolutional and recurrent models;Results in Engineering;2023-06

4. A Novel Unsupervised Video Anomaly Detection Framework Based on Optical Flow Reconstruction and Erased Frame Prediction;Sensors;2023-05-17

5. ConvGRU-CNN: Spatiotemporal Deep Learning for Real-World Anomaly Detection in Video Surveillance System;International Journal of Interactive Multimedia and Artificial Intelligence;2023