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Clustering Based on Two Layers for Abnormal Event Detection in Video Surveillance

Clustering Based on Two Layers for Abnormal Event Detection in Video Surveillance

Emna Fendri, Najla Bouarada Ghrab, Mohamed Hammami
Copyright: © 2019 |Pages: 21
ISBN13: 9781522571131|ISBN10: 1522571132|EISBN13: 9781522571148
DOI: 10.4018/978-1-5225-7113-1.ch024
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MLA

Fendri, Emna, et al. "Clustering Based on Two Layers for Abnormal Event Detection in Video Surveillance." Censorship, Surveillance, and Privacy: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2019, pp. 433-453. https://doi.org/10.4018/978-1-5225-7113-1.ch024

APA

Fendri, E., Ghrab, N. B., & Hammami, M. (2019). Clustering Based on Two Layers for Abnormal Event Detection in Video Surveillance. In I. Management Association (Ed.), Censorship, Surveillance, and Privacy: Concepts, Methodologies, Tools, and Applications (pp. 433-453). IGI Global. https://doi.org/10.4018/978-1-5225-7113-1.ch024

Chicago

Fendri, Emna, Najla Bouarada Ghrab, and Mohamed Hammami. "Clustering Based on Two Layers for Abnormal Event Detection in Video Surveillance." In Censorship, Surveillance, and Privacy: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 433-453. Hershey, PA: IGI Global, 2019. https://doi.org/10.4018/978-1-5225-7113-1.ch024

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Abstract

Abnormal event detection has attracted great research attention in video surveillance. In this paper, the authors presented a robust method of trajectories clustering for abnormal event detection. This method is based on two layers and benefits from two well-known clustering algorithms: the agglomerative hierarchical clustering and the k-means clustering. Facing to the challenges related to the trajectories, e.g., different sizes, the authors introduce a preprocessing step to unify their sizes and reduce their dimensionality. The experimental results show the performance and accuracy of their proposed method.

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