Suspicious loitering detection from annotated CCTV feed using CEP based approach

Rabiah Adawiyah Shahad, and Mohd Faisal Ibrahim, and Lim, Ezra Kai Xian and Aini Hussain, and Mohamad Hanif Md Saad, (2018) Suspicious loitering detection from annotated CCTV feed using CEP based approach. Jurnal Kejuruteraan, 30 (1). pp. 83-91. ISSN 0128-0198


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Smart Surveillance System is a critical system that enables automated detection of anomalous activities from live CCTV feed. The main challenge that needs to be addressed by the Smart Surveillance System is the ability to understand and detect the activities that are currently occurring within the CCTV feed. Suspicious loitering is considered one of the anomalous activities that precede unwanted events, such as break-ins, burglary, and robbery. In this research, the Complex Event Processing (CEP) approach was selected as the system development approach for developing a Smart Surveillance System. Four types of similarity search-based event detectors, namely the Multi-Layered Event Detector for General Application (MEGA), Temporally Constrained Template Match Detector (TCD), Sliding Window Detector (SWD), and Weighted Sliding Window Detector (WSWD) were tested and evaluated to determine the best suspicious loitering event detector to be used in the Smart Surveillance System. The input data to the detectors comprised manually annotated real CCTV feed which was subjected to three noise conditions: (i) no-noise (0% noise) annotation, (ii) 25% noisy annotation and (iii) 46.8% noisy annotation. The 46.8% noisy annotation is assumed to reflect the real ambient operating condition of the Smart Surveillance System; while the no-noise condition was assumed to reflect the perfect CCTV feed acquisition and annotation process. The performance of the detectors was measured in terms of sensitivity, specificity, detection accuracy, and the area under the Receiver’s Operating Curve (ROC). The results obtained showed that MEGA is the best overall detector for suspicious loitering detection in ambient operating conditions with detection accuracy of 97.20% and area under ROC curve of 0.6117.

Item Type:Article
Keywords:Event detection; Smart surveillance system; Complex event processing
Journal:Jurnal Kejuruteraan
ID Code:12635
Deposited By: ms aida -
Deposited On:08 Mar 2019 03:58
Last Modified:12 Mar 2019 10:25

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