Two-stage violence detection using ViTPose and classification models at smart airports

Simple item page
dc.contributor.authorÜstek, İrem
dc.contributor.authorDesai, Jay
dc.contributor.authorLópez Torrecillas, Iván
dc.contributor.authorAbadou, Sofiane
dc.contributor.authorWang, Jinjie
dc.contributor.authorFever, Quentin
dc.contributor.authorKasthuri, Sandhya Rani
dc.contributor.authorXing, Yang
dc.contributor.authorGuo, Weisi
dc.contributor.authorTsourdos, Antonios
dc.date.accessioned2024-03-22T10:48:43Z
dc.date.available2024-03-22T10:48:43Z
dc.date.issued2024-03-01
dc.description.abstractThis study introduces an innovative violence detection framework tailored to the unique requirements of smart airports, where prompt responses to violent situations are crucial. The proposed framework harnesses the power of ViTPose for human pose estimation and employs a CNN-BiLSTM network to analyse spatial and temporal information within keypoints sequences, enabling the accurate classification of violent behaviour in real-time. Seamlessly integrated within the SAAB’s SAFE (Situational Awareness for Enhanced Security) framework, the solution underwent integrated testing to ensure robust performance in real-world scenarios. The AIRTLab dataset, characterized by its high video quality and relevance to surveillance scenarios, is utilized in this study to enhance the model's accuracy and mitigate false positives. As airports face increased foot traffic in the post-pandemic era, the implementation of AI-driven violence detection systems, such as the one proposed, is paramount for improving security, expediting response times, and promoting data-informed decision-making. The implementation of this framework not only diminishes the probability of violent events but also assists surveillance teams in effectively addressing potential threats, ultimately fostering a more secure and protected aviation sector. Codes are available at: https://github.com/Asami-1/GDP.en_UK
dc.identifier.citationÜstek İ, Desai J, Torrecillas IL, et al., (2024) Two-stage violence detection using ViTPose and classification models at smart airports. In: 2023 IEEE Smart World Congress (SWC), 28-31 August 2023, Portsmouth, UK, pp. 797-802en_UK
dc.identifier.eisbn979-8-3503-1980-4
dc.identifier.isbn979-8-3503-1981-1
dc.identifier.urihttps://doi.org/10.1109/SWC57546.2023.10448548
dc.identifier.urihttps://dspace.lib.cranfield.ac.uk/handle/1826/21076
dc.language.isoen_UKen_UK
dc.publisherIEEEen_UK
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectViolence detectionen_UK
dc.subjectsmart airporten_UK
dc.subjectintegrationen_UK
dc.subjectaviation sectoren_UK
dc.subjectViTPoseen_UK
dc.subjectpose estimationen_UK
dc.subjectCNN-BiLSTMen_UK
dc.titleTwo-stage violence detection using ViTPose and classification models at smart airportsen_UK
dc.typeConference paperen_UK
dcterms.dateAccepted2023-06-04

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Two-stage_violence_detection-Smart_airports-2024.pdf
Size:
555.12 KB
Format:
Adobe Portable Document Format
Description:
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.63 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

Staff publications (SATM)