{ "ok": true, "doi": "10.46243/jst.2024.v9.i4.pp131-135", "doi_display": "10.46243/jst.2024.v9.i4.pp131-135", "doi_url": "https://doi.org/10.46243/jst.2024.v9.i4.pp131-135", "state": "registered", "url": "https://www.jst.org.in/index.php/pub/article/view/1012", "title": "REALTIMEVIOLENCEDETECTION", "version": 2, "registered_via": "crossref", "prefix": { "prefix": "10.46243", "status": "live" }, "registrant": { "name": "Longman Publishers", "kind": "publisher", "country": "India" }, "reserved_at": null, "registered_at": "2026-09-29 22:00:32", "updated_at": "2026-09-29 23:59:52", "withdrawn_at": null, "withdrawn_reason": null, "record": { "format": "smartscholars-doi-metadata/1.0", "doi": "10.46243/jst.2024.v9.i4.pp131-135", "referent": "Creation", "type": "JournalArticle", "structural_type": "Digital", "modes": [ "Visual" ], "characters": [ "Language" ], "titles": [ { "value": "REALTIMEVIOLENCEDETECTION", "type": "PrincipalTitle", "lang": "en" } ], "identifiers": [ { "type": "DOI", "value": "10.46243/jst.2024.v9.i4.pp131-135" } ], "agents": [ { "role": "author", "name": { "given": "", "family": "KarthikRKrishna" }, "sequence": "first" }, { "role": "author", "name": { "given": "", "family": "VishakSS" }, "sequence": "additional" }, { "role": "author", "name": { "given": "", "family": "VyshnaviCV" }, "sequence": "additional" }, { "role": "publisher", "name": { "org": "Longman Publishers" } } ], "dates": { "published": "2024-04-29", "date_type": "PublicationDate", "online": "2024-04-29" }, "language": "en", "container": { "type": "Journal", "titles": [ { "value": "Journal of Science & Technology", "type": "PrincipalTitle" } ], "identifiers": [ { "type": "ISSN", "value": "2456-5660", "medium": "electronic" } ], "volume": "09", "issue": "04", "pages": { "first": "131", "last": "135" } }, "links": [ { "url": "https://www.jst.org.in/index.php/pub/article/view/1012", "return_type": "text/html", "primary": true }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1012/904", "purpose": "text-mining", "return_type": "application/pdf" }, { "url": "https://www.jst.org.in/index.php/pub/article/download/1012/1355", "purpose": "text-mining", "return_type": "application/xml" }, { "url": "https://jst.org.in/index.php/pub/article/view/1012/904", "purpose": "similarity-checking" } ], "abstract": { "value": "Real-timeviolencedetectionhasbecomeincreasinglyessentialintoday'ssecurityandsurveillancesystems.Thispaperproposesanovelapproachutilizingadvancedcomputervisiontechniquesandmachinelearningalgorithmsforthereal-timedetectionofviolentbehaviorinvideostreams.Byextractingkey features such as motion patterns, body poses, and spatial relationships, coupled with deep learningmodels for classification, our system achieves high accuracy and efficiency in identifying violent acts asthey occur. The proposed framework offers promising potential for enhancing public safety, facilitatingtimelyinterventions,andmitigatingpotentialthreatsinvariousreal-worldscenarios.", "lang": "en" }, "license": { "url": "https://creativecommons.org/licenses/by/4.0/", "start": "2024-04-29", "applies_to": "vor" }, "references": [ { "key": "ref1", "doi": "10.1109/cvprw.2012.6239348", "unstructured": "T. Hassner, Y. Itcher, and O. Kliper-Gross, ‘‘Violent flows: Real-time detection of violent crowd behavior,’’ in Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit. Workshops,pp. 1–6" }, { "key": "ref2", "doi": "10.3390/s19112472", "unstructured": "F. U. M. Ullah, A. Ullah, K. Muhammad, I. U. Haq, and S. W. Baik, ‘‘Violence detection using spatiotemporal features with 3D convolutional neural network,’’ Sensors, vol. 19, no. 11, p. 2472" }, { "key": "ref3", "doi": "10.1080/08839514.2020.1723876", "unstructured": "S. Accattoli, P. Sernani, N. Falcionelli, D. N. Mekuria, and A. F. Dragoni, ‘‘Violence detection in videos by combining 3D convolutional neural networks and support vector machines,’’ Appl. Artif. Intell., vol. 34, no. 4, pp. 329–344" }, { "key": "ref4", "doi": "10.1007/978-3-642-23678-5_39", "unstructured": "E. B. Nievas, O. D. Suarez, G. B. García, and R. Sukthankar, ‘‘Violence detection in video using computer vision techniques,’’ in Computer Analysis of Images and Patterns, P. Real, D. Diaz-Pernil, H. Molina-Abril, A. Berciano, and W. Kropatsch, Eds. Berlin, Germany: Springer, pp. 332–339" }, { "key": "ref5", "doi": "10.1109/access.2019.2932114", "unstructured": "M. Ramzan, A. Abid, H. U. Khan, S. M. Awan, A.Ismail, M. Ahmed, M. Ilyas, and A. Mahmood, ‘‘A review on state of-the-art violence detection techniques,’’ IEEE Access, vol. 7, pp. 107560–107575" }, { "key": "ref6", "doi": "10.1109/access.2019.2906275", "unstructured": "W. Song, D. Zhang, X. Zhao, J. Yu, R. Zheng, and A. Wang, ‘‘A novel violent video detection scheme based on modified 3D convolutional neuralnetworks,’’ IEEE Access, vol. 7, pp. 39172–39179" }, { "key": "ref7", "doi": "10.1371/journal.pone.0120448", "unstructured": "I. Serrano Gracia, O. Deniz Suarez, G. Bueno Garcia, and T.-K. Kim, ‘‘Fast fight detection,’’ PLoSONE, vol. 10, no. 4, Art. no. e0120448" }, { "key": "ref8", "doi": "10.1109/avss.2017.8078468", "unstructured": "S. Sudhakaran and O. Lanz, ‘‘Learning to detect violent videos using convolutional long shortterm memory,’’ in Proc. 14th IEEE Int. Conf. Adv. Video Signal Based Surveill. 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