Computer Vision for Weapon Detection in Educational Environments: A Systematic Literature Review
Resumo
This study presents a systematic review of the literature on the use of computer vision algorithms for weapon detection in educational environments. Through the analysis of 13 selected studies from an initial corpus of 10,519 articles, the results demonstrate that models based on Convolutional Neural Networks, particularly variants of YOLO, are predominantly used due to their high accuracy and real-time efficiency. This work highlights the need for technological advancements to address challenges such as the variability of weapon types and the diverse school scenarios. Furthermore, the practical implications of these technologies in enhancing school security and the importance of ethical and privacy considerations are discussed. The review also reveals significant gaps in current research, such as the lack of studies focused on specific educational environments and the need for more representative and diverse datasets.
Palavras-chave:
deep learning, computer vision, gun detection, educational environments
Referências
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Ali AlZaabi, Manar Abi Talib, Ali Bou Nassif, Ali Sajwani, and Omar Einea. 2020. A Systematic Literature Review on Machine Learning in Object Detection Security. In 2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA). 136–139. DOI: 10.1109/ICCCA49541.2020.9250836
Nishit Anand and Rupesh Kumar Koshariya. 2022. SaveLives - A Real-Time Threat Detection System. In 2022 1st International Conference on Informatics (ICI). IEEE, Noida, India, 114–119. DOI: 10.1109/ICI53355.2022.9786892
D.H. Ballard and C.M. Brown. 1982. Computer Vision. Prentice-Hall. [link]
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Angela Carrera-Rivera, William Ochoa, Felix Larrinaga, and Ganix Lasa. 2022. How-to conduct a systematic literature review: A quick guide for computer science research. MethodsX 9 (2022), 101895. DOI: 10.1016/j.mex.2022.101895
A. Egiazarov, F. Zennaro, and V. Mavroeidis. 2020. Firearm Detection viaConvolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions. In 2020 IEEE International Conference on Big Data (Big Data). IEEE Computer Society, Los Alamitos, CA, USA, 1796–1804. DOI: 10.1109/BigData50022.2020.9377745
U. G, I. Sudha, V. Lakshmanan, F. Shadrach, P. Krishnammal, and N. T. J. 2023. Crime Scene Object Detection from Surveillance Video by using Tiny YOLO Algorithm. In 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE Computer Society, Los Alamitos, CA, USA, 654–659. DOI: 10.1109/ICPCSN58827.2023.00114
Rakesh Garg and Someet Singh. 2021. Intelligent Video Surveillance Based on YOLO: A Comparative Study. In 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3). 1–6. DOI: 10.1109/ICAC353642.2021.9697321
Tufail Sajjad Shah Hashmi, Nazeef Ul Haq, Muhammad Moazam Fraz, and Muhammad Shahzad. 2021. Application of Deep Learning for Weapons Detection in Surveillance Videos. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2). 1–6. DOI: 10.1109/ICoDT252288.2021.9441523
Hao Huang, Haihua Xu, Xianhui Wang, and Wushour Silamu. 2015. Maximum F1score discriminative training criterion for automatic mispronunciation detection. IEEE/ACM Transactions on Audio, Speech, and Language Processing 23, 4 (2015), 787–797.
Collins Ineneji and Mehmet Kusaf. 2019. Hybrid weapon detection algorithm, using material test and fuzzy logic system. Computers & Electrical Engineering 78 (Sept. 2019), 437–448. DOI: 10.1016/j.compeleceng.2019.08.005
P Isaac Ritharson, G Madhavan, M. Rajeswari, and D. Brindha. 2022. Prevention of School Shooting using Neural Networks and Computer Vision. In 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT). IEEE, Kannur, India, 1703–1709. DOI: 10.1109/ICICICT54557.2022.9917656
B. Kitchenham and S. Charters. 2007. Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001. Keele University and Durham University Joint Report.
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature 521, 7553 (2015), 436–444.
JunYi Lim, Md Istiaque Al Jobayer, Vishnu Monn Baskaran, Joanne Mun-Yee Lim, John See, and Koksheik Wong. 2021. Deep multi-level feature pyramids: Application for non-canonical firearm detection in video surveillance. Eng. Appl. Artif. Intell. 97 (2021), 104094. DOI: 10.1016/j.engappai.2020.104094
David Lyon. 2018. The Culture of Surveillance: Watching as a Way of Life.
V.P. Manikandan and U. Rahamathunnisa. 2022. A neural network aided attuned scheme for gun detection in video surveillance images. Image and Vision Computing 120 (April 2022), 104406. DOI: 10.1016/j.imavis.2022.104406
Maurício Marengoni and Stringhini Stringhini. 2009. Tutorial: Introdução à visão computacional usando opencv. Revista de Informática Teórica e Aplicada 16, 1 (2009), 125–160.
T. M. Mitchell. 1997. Does Machine Learning Really Work? AI Magazine 18 , 3 (1997), 11–20. [link]
David Martin W. Powers. 2011. Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies 2, 1 (2011), 37–63.
Maverick Poma Rosales, Ciro Rodriguez, Yuri Pomachagua, and Carlos Navarro. 2021. Firearm Detection in Images of Video Surveillance Cameras with Convolutional Neural Networks. In 2021 13th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, Lima, Peru, 61–65. DOI: 10.1109/CICN51697.2021.9574690
Jesus Ruiz-Santaquiteria, Alberto Velasco-Mata, Noelia Vallez, Oscar Deniz, and Gloria Bueno. 2023. Improving handgun detection through a combination of visual features and body pose-based data. Pattern Recognition 136 (April 2023) , 109252. DOI: 10.1016/j.patcog.2022.109252
Tomás Santos, Hélder Oliveira, and António Cunha. 2024. Systematic review on weapon detection in surveillance footage through deep learning. Computer Science Review 51 (2024), 100612. DOI: 10.1016/j.cosrev.2023.100612
Thiago Teixeira Santos, Jayme Garcia Arnal Barbedo, Sônia Ternes, J Camargo Neto, Luciano Vieira Koenigkan, and Kleber Xavier Sampaio de Souza. 2020. Visão computacional aplicada na agricultura. (2020).
Pramila P. Shinde and Seema Shah. 2018. A Review of Machine Learning and Deep Learning Applications. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). 1–6. DOI: 10.1109/ICCUBEA.2018.8697857
Andy P Siddaway, A. Wood, and L. Hedges. 2019. How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, MetaAnalyses, and Meta-Syntheses. Annual review of psychology 70 (2019), 747–770. DOI: 10.1146/annurev-psych-010418-102803
H. Sivakumar, V. Arvind.R, P. V, and G. Balamurugan. 2023. Novel Deep Learning Pipeline for Automatic Weapon Detection. In 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). IEEE Computer Society, Los Alamitos, CA, USA, 1–5. DOI: 10.1109/CSDE59766.2023.10487762
Noelia Vallez, Alberto Velasco-Mata, Juan Jose Corroto, and Oscar Deniz. 2019. Weapon Detection for Particular Scenarios Using Deep Learning. In Pattern Recognition and Image Analysis, Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro (Eds.). Springer International Publishing, Cham, 371–382.
Noelia Vallez, Alberto Velasco-Mata, Juan Jose Corroto, and Oscar Deniz. 2019. Weapon Detection for Particular Scenarios Using Deep Learning. In Pattern Recognition and Image Analysis, Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro (Eds.). Vol. 11868. Springer International Publishing, Cham, 371–382. Series Title: Lecture Notes in Computer Science. DOI: 10.1007/978-3-030-31321-0_32
Alberto Velasco-Mata, Jesus Ruiz-Santaquiteria, Noelia Vallez, and Oscar Deniz. 2021. Using human pose information for handgun detection. Neural Computing and Applications 33, 24 (Dec. 2021), 17273–17286. DOI: 10.1007/s00521-021-06317-8
Pavinder Yadav, Nidhi Gupta, and Pawan Kumar Sharma. 2024. Robust weapon detection in dark environments using Yolov7-DarkVision. Digital Signal Processing 145 (Feb. 2024), 104342. DOI: 10.1016/j.dsp.2023.104342
Ali AlZaabi, Manar Abi Talib, Ali Bou Nassif, Ali Sajwani, and Omar Einea. 2020. A Systematic Literature Review on Machine Learning in Object Detection Security. In 2020 IEEE 5th International Conference on Computing Communication and Automation (ICCCA). 136–139. DOI: 10.1109/ICCCA49541.2020.9250836
Nishit Anand and Rupesh Kumar Koshariya. 2022. SaveLives - A Real-Time Threat Detection System. In 2022 1st International Conference on Informatics (ICI). IEEE, Noida, India, 114–119. DOI: 10.1109/ICI53355.2022.9786892
D.H. Ballard and C.M. Brown. 1982. Computer Vision. Prentice-Hall. [link]
Muhammad Tahir Bhatti, Muhammad Gufran Khan, Masood Aslam, and Muhammad Junaid Fiaz. 2021. Weapon Detection in Real-Time CCTV Videos Using Deep Learning. IEEE Access 9 (2021), 34366–34382. DOI: 10.1109/ACCESS.20213059170
Angela Carrera-Rivera, William Ochoa, Felix Larrinaga, and Ganix Lasa. 2022. How-to conduct a systematic literature review: A quick guide for computer science research. MethodsX 9 (2022), 101895. DOI: 10.1016/j.mex.2022.101895
A. Egiazarov, F. Zennaro, and V. Mavroeidis. 2020. Firearm Detection viaConvolutional Neural Networks: Comparing a Semantic Segmentation Model Against End-to-End Solutions. In 2020 IEEE International Conference on Big Data (Big Data). IEEE Computer Society, Los Alamitos, CA, USA, 1796–1804. DOI: 10.1109/BigData50022.2020.9377745
U. G, I. Sudha, V. Lakshmanan, F. Shadrach, P. Krishnammal, and N. T. J. 2023. Crime Scene Object Detection from Surveillance Video by using Tiny YOLO Algorithm. In 2023 3rd International Conference on Pervasive Computing and Social Networking (ICPCSN). IEEE Computer Society, Los Alamitos, CA, USA, 654–659. DOI: 10.1109/ICPCSN58827.2023.00114
Rakesh Garg and Someet Singh. 2021. Intelligent Video Surveillance Based on YOLO: A Comparative Study. In 2021 International Conference on Advances in Computing, Communication, and Control (ICAC3). 1–6. DOI: 10.1109/ICAC353642.2021.9697321
Tufail Sajjad Shah Hashmi, Nazeef Ul Haq, Muhammad Moazam Fraz, and Muhammad Shahzad. 2021. Application of Deep Learning for Weapons Detection in Surveillance Videos. In 2021 International Conference on Digital Futures and Transformative Technologies (ICoDT2). 1–6. DOI: 10.1109/ICoDT252288.2021.9441523
Hao Huang, Haihua Xu, Xianhui Wang, and Wushour Silamu. 2015. Maximum F1score discriminative training criterion for automatic mispronunciation detection. IEEE/ACM Transactions on Audio, Speech, and Language Processing 23, 4 (2015), 787–797.
Collins Ineneji and Mehmet Kusaf. 2019. Hybrid weapon detection algorithm, using material test and fuzzy logic system. Computers & Electrical Engineering 78 (Sept. 2019), 437–448. DOI: 10.1016/j.compeleceng.2019.08.005
P Isaac Ritharson, G Madhavan, M. Rajeswari, and D. Brindha. 2022. Prevention of School Shooting using Neural Networks and Computer Vision. In 2022 Third International Conference on Intelligent Computing Instrumentation and Control Technologies (ICICICT). IEEE, Kannur, India, 1703–1709. DOI: 10.1109/ICICICT54557.2022.9917656
B. Kitchenham and S. Charters. 2007. Guidelines for performing systematic literature reviews in software engineering. Technical Report EBSE 2007-001. Keele University and Durham University Joint Report.
Yann LeCun, Yoshua Bengio, and Geoffrey Hinton. 2015. Deep learning. nature 521, 7553 (2015), 436–444.
JunYi Lim, Md Istiaque Al Jobayer, Vishnu Monn Baskaran, Joanne Mun-Yee Lim, John See, and Koksheik Wong. 2021. Deep multi-level feature pyramids: Application for non-canonical firearm detection in video surveillance. Eng. Appl. Artif. Intell. 97 (2021), 104094. DOI: 10.1016/j.engappai.2020.104094
David Lyon. 2018. The Culture of Surveillance: Watching as a Way of Life.
V.P. Manikandan and U. Rahamathunnisa. 2022. A neural network aided attuned scheme for gun detection in video surveillance images. Image and Vision Computing 120 (April 2022), 104406. DOI: 10.1016/j.imavis.2022.104406
Maurício Marengoni and Stringhini Stringhini. 2009. Tutorial: Introdução à visão computacional usando opencv. Revista de Informática Teórica e Aplicada 16, 1 (2009), 125–160.
T. M. Mitchell. 1997. Does Machine Learning Really Work? AI Magazine 18 , 3 (1997), 11–20. [link]
David Martin W. Powers. 2011. Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies 2, 1 (2011), 37–63.
Maverick Poma Rosales, Ciro Rodriguez, Yuri Pomachagua, and Carlos Navarro. 2021. Firearm Detection in Images of Video Surveillance Cameras with Convolutional Neural Networks. In 2021 13th International Conference on Computational Intelligence and Communication Networks (CICN). IEEE, Lima, Peru, 61–65. DOI: 10.1109/CICN51697.2021.9574690
Jesus Ruiz-Santaquiteria, Alberto Velasco-Mata, Noelia Vallez, Oscar Deniz, and Gloria Bueno. 2023. Improving handgun detection through a combination of visual features and body pose-based data. Pattern Recognition 136 (April 2023) , 109252. DOI: 10.1016/j.patcog.2022.109252
Tomás Santos, Hélder Oliveira, and António Cunha. 2024. Systematic review on weapon detection in surveillance footage through deep learning. Computer Science Review 51 (2024), 100612. DOI: 10.1016/j.cosrev.2023.100612
Thiago Teixeira Santos, Jayme Garcia Arnal Barbedo, Sônia Ternes, J Camargo Neto, Luciano Vieira Koenigkan, and Kleber Xavier Sampaio de Souza. 2020. Visão computacional aplicada na agricultura. (2020).
Pramila P. Shinde and Seema Shah. 2018. A Review of Machine Learning and Deep Learning Applications. In 2018 Fourth International Conference on Computing Communication Control and Automation (ICCUBEA). 1–6. DOI: 10.1109/ICCUBEA.2018.8697857
Andy P Siddaway, A. Wood, and L. Hedges. 2019. How to Do a Systematic Review: A Best Practice Guide for Conducting and Reporting Narrative Reviews, MetaAnalyses, and Meta-Syntheses. Annual review of psychology 70 (2019), 747–770. DOI: 10.1146/annurev-psych-010418-102803
H. Sivakumar, V. Arvind.R, P. V, and G. Balamurugan. 2023. Novel Deep Learning Pipeline for Automatic Weapon Detection. In 2023 IEEE Asia-Pacific Conference on Computer Science and Data Engineering (CSDE). IEEE Computer Society, Los Alamitos, CA, USA, 1–5. DOI: 10.1109/CSDE59766.2023.10487762
Noelia Vallez, Alberto Velasco-Mata, Juan Jose Corroto, and Oscar Deniz. 2019. Weapon Detection for Particular Scenarios Using Deep Learning. In Pattern Recognition and Image Analysis, Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro (Eds.). Springer International Publishing, Cham, 371–382.
Noelia Vallez, Alberto Velasco-Mata, Juan Jose Corroto, and Oscar Deniz. 2019. Weapon Detection for Particular Scenarios Using Deep Learning. In Pattern Recognition and Image Analysis, Aythami Morales, Julian Fierrez, José Salvador Sánchez, and Bernardete Ribeiro (Eds.). Vol. 11868. Springer International Publishing, Cham, 371–382. Series Title: Lecture Notes in Computer Science. DOI: 10.1007/978-3-030-31321-0_32
Alberto Velasco-Mata, Jesus Ruiz-Santaquiteria, Noelia Vallez, and Oscar Deniz. 2021. Using human pose information for handgun detection. Neural Computing and Applications 33, 24 (Dec. 2021), 17273–17286. DOI: 10.1007/s00521-021-06317-8
Pavinder Yadav, Nidhi Gupta, and Pawan Kumar Sharma. 2024. Robust weapon detection in dark environments using Yolov7-DarkVision. Digital Signal Processing 145 (Feb. 2024), 104342. DOI: 10.1016/j.dsp.2023.104342
Publicado
14/10/2024
Como Citar
LIMA, Maurício Rodrigues; FERREIRA, Deller James; DIAS, Elisângela Silva; MOTA, Marcos Reges; CHAGAS, Ana Luísa de Bastos; LOBO, Pedro Lemes Sixel.
Computer Vision for Weapon Detection in Educational Environments: A Systematic Literature Review. In: WORKSHOP DE REVISÕES SISTEMÁTICAS DE LITERATURA EM SISTEMAS MULTIMÍDIAS E WEB - SIMPÓSIO BRASILEIRO DE SISTEMAS MULTIMÍDIA E WEB (WEBMEDIA), 30. , 2024, Juiz de Fora/MG.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 121-128.
ISSN 2596-1683.
DOI: https://doi.org/10.5753/webmedia_estendido.2024.243946.
