Visible to the public Dynamic clustering for event detection and anomaly identification in video surveillance

TitleDynamic clustering for event detection and anomaly identification in video surveillance
Publication TypeConference Paper
Year of Publication2017
AuthorsRupasinghe, R. A. A., Padmasiri, D. A., Senanayake, S. G. M. P., Godaliyadda, G. M. R. I., Ekanayake, M. P. B., Wijayakulasooriya, J. V.
Conference Name2017 IEEE International Conference on Industrial and Information Systems (ICIIS)
KeywordsAnomaly Identification, anomaly identification results, Anomaly Plane, Clustering algorithms, dynamic clustering, event detection, feature extraction, Heuristic algorithms, Human Behavior, human behavioral patterns, learning (artificial intelligence), life video surveillance, Normal Plane, object detection, Pattern recognition, pubcrawl, Resiliency, Roads, Scalability, spectral clustering, Time variant events, Trajectory, video signal processing, video surveillance, video surveillance event

This work introduces concepts and algorithms along with a case study validating them, to enhance the event detection, pattern recognition and anomaly identification results in real life video surveillance. The motivation for the work underlies in the observation that human behavioral patterns in general continuously evolve and adapt with time, rather than being static. First, limitations in existing work with respect to this phenomena are identified. Accordingly, the notion and algorithms of Dynamic Clustering are introduced in order to overcome these drawbacks. Correspondingly, we propose the concept of maintaining two separate sets of data in parallel, namely the Normal Plane and the Anomaly Plane, to successfully achieve the task of learning continuously. The practicability of the proposed algorithms in a real life scenario is demonstrated through a case study. From the analysis presented in this work, it is evident that a more comprehensive analysis, closely following human perception can be accomplished by incorporating the proposed notions and algorithms in a video surveillance event.

Citation Keyrupasinghe_dynamic_2017