Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit
Video surveillance systems play an important role in ensuring security indoors and outdoors and detecting suspicious persons due to the increasing violence and terrorist acts every year. In the proposed study, an artificial intelligence-based warning system has been developed, which enables the dete...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Bursa Technical University
2023-12-01
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| Series: | Journal of Innovative Science and Engineering |
| Subjects: | |
| Online Access: | http://jise.btu.edu.tr/tr/download/article-file/3354776 |
| _version_ | 1827396444450979840 |
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| author | Gizem ORTAÇ KOŞUN Seçkin YILMAZ Yusuf KAYIPMAZ Rüya ŞAMLI |
| author_facet | Gizem ORTAÇ KOŞUN Seçkin YILMAZ Yusuf KAYIPMAZ Rüya ŞAMLI |
| author_sort | Gizem ORTAÇ KOŞUN |
| collection | DOAJ |
| description | Video surveillance systems play an important role in ensuring security indoors and outdoors and detecting suspicious persons due to the increasing violence and terrorist acts every year. In the proposed study, an artificial intelligence-based warning system has been developed, which enables the detection of potential suspects who may carry out criminal or terrorist activities by
detecting anomalies in surveillance videos. In this developed system, an abnormality is detected by using the outfits of the people. The YOLOv7 object detection model is trained on our customized data sets, and suspicious person detection is made through outfit information. Especially in cases where biometric data is hidden, dress information makes it easier to obtain
information about people. For this reason, the knowledge of outfits is the main point of this study in the detection of suspicious persons. Thanks to this study, security guards will be able to focus on this suspicious person before they pre-empt any crime or terrorist activity. If there are other data confirming the suspicious situation as a result of this follow-up; security personnel will have
time to eliminate the crime or attack. The experimental results obtained have been promising in terms of the usability of a person's outfit anomalies to ensure public confidence or avoid risk to human life. Although there are various studies in the literature for the prevention of terrorist or criminal activities; there is no study in which people's outfit is used to identify suspects. |
| first_indexed | 2024-03-08T18:51:01Z |
| format | Article |
| id | doaj.art-7f881d9f3b974399a124c705e949229a |
| institution | Directory Open Access Journal |
| issn | 2602-4217 |
| language | English |
| last_indexed | 2024-03-08T18:51:01Z |
| publishDate | 2023-12-01 |
| publisher | Bursa Technical University |
| record_format | Article |
| series | Journal of Innovative Science and Engineering |
| spelling | doaj.art-7f881d9f3b974399a124c705e949229a2023-12-28T19:19:49ZengBursa Technical UniversityJournal of Innovative Science and Engineering2602-42172023-12-017216718210.38088/jise.1348213Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on OutfitGizem ORTAÇ KOŞUN0https://orcid.org/0000-0003-1228-9852Seçkin YILMAZ1https://orcid.org/0000-0001-6791-1536Yusuf KAYIPMAZ2https://orcid.org/0000-0002-4588-8715Rüya ŞAMLI3https://orcid.org/0000-0002-8723-1228ISTANBUL UNIVERSITYBursa Technical UniversityBursa Technical UniversityISTANBUL UNIVERSITYVideo surveillance systems play an important role in ensuring security indoors and outdoors and detecting suspicious persons due to the increasing violence and terrorist acts every year. In the proposed study, an artificial intelligence-based warning system has been developed, which enables the detection of potential suspects who may carry out criminal or terrorist activities by detecting anomalies in surveillance videos. In this developed system, an abnormality is detected by using the outfits of the people. The YOLOv7 object detection model is trained on our customized data sets, and suspicious person detection is made through outfit information. Especially in cases where biometric data is hidden, dress information makes it easier to obtain information about people. For this reason, the knowledge of outfits is the main point of this study in the detection of suspicious persons. Thanks to this study, security guards will be able to focus on this suspicious person before they pre-empt any crime or terrorist activity. If there are other data confirming the suspicious situation as a result of this follow-up; security personnel will have time to eliminate the crime or attack. The experimental results obtained have been promising in terms of the usability of a person's outfit anomalies to ensure public confidence or avoid risk to human life. Although there are various studies in the literature for the prevention of terrorist or criminal activities; there is no study in which people's outfit is used to identify suspects.http://jise.btu.edu.tr/tr/download/article-file/3354776forensic scienceanomaly detectionsoft biometricssurveillance video. |
| spellingShingle | Gizem ORTAÇ KOŞUN Seçkin YILMAZ Yusuf KAYIPMAZ Rüya ŞAMLI Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit Journal of Innovative Science and Engineering forensic science anomaly detection soft biometrics surveillance video. |
| title | Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit |
| title_full | Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit |
| title_fullStr | Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit |
| title_full_unstemmed | Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit |
| title_short | Preventing Crime and Terrorist Activities with a New Anomaly Detection Approach Based on Outfit |
| title_sort | preventing crime and terrorist activities with a new anomaly detection approach based on outfit |
| topic | forensic science anomaly detection soft biometrics surveillance video. |
| url | http://jise.btu.edu.tr/tr/download/article-file/3354776 |
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