TELKOMNIKA Telecommunication, Computing, Electronics and Control
Abnormal activity detection in surveillance video scenes
Dublin Core
Title
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Abnormal activity detection in surveillance video scenes
Abnormal activity detection in surveillance video scenes
Subject
Anomaly detection, Motion object detection, Real-time processing, Tracking, Video surveillance
Description
Automated detection of abnormal activity assumes a significant task in
surveillance applications. This paper presents an intelligent framework video surveillance to detect abnormal human activity in an academic environment that takes into account the security and emergency aspects by focusing on three abnormal activities (falling, boxing and waving). This framework designed to consist of the two essential processes: the first one is a tracking system that can follow targets with identify sets of features to understand human activity and measure descriptive information of each target. The second one is a decision system that can realize if the activity of the target track is "normal or "abnormal” then energizing alarm when recognized abnormal activities.
surveillance applications. This paper presents an intelligent framework video surveillance to detect abnormal human activity in an academic environment that takes into account the security and emergency aspects by focusing on three abnormal activities (falling, boxing and waving). This framework designed to consist of the two essential processes: the first one is a tracking system that can follow targets with identify sets of features to understand human activity and measure descriptive information of each target. The second one is a decision system that can realize if the activity of the target track is "normal or "abnormal” then energizing alarm when recognized abnormal activities.
Creator
Jwan Jamal Ali, Narjis Mezaal Shati, Methaq Talib Gaata
Source
DOI: 10.12928/TELKOMNIKA.v18i5.16634
Publisher
Universitas Ahmad Dahlan
Date
October 2020
Contributor
Sri Wahyuni
Rights
ISSN: 1693-6930
Relation
http://journal.uad.ac.id/index.php/TELKOMNIKA
Format
PDF
Language
English
Type
Text
Coverage
TELKOMNIKA Telecommunication, Computing, Electronics and Control
Files
Collection
Citation
Jwan Jamal Ali, Narjis Mezaal Shati, Methaq Talib Gaata, “TELKOMNIKA Telecommunication, Computing, Electronics and Control
Abnormal activity detection in surveillance video scenes,” Repository Horizon University Indonesia, accessed October 31, 2025, https://repository.horizon.ac.id/items/show/4105.
Abnormal activity detection in surveillance video scenes,” Repository Horizon University Indonesia, accessed October 31, 2025, https://repository.horizon.ac.id/items/show/4105.