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Analysis of Motion Detection using Social Force Model

Wan Nur Azhani, W. Samsudin and Kamarul Hawari, Ghazali and Mohd Falfazli, Mat Jusof (2013) Analysis of Motion Detection using Social Force Model. In: Proceeding of the International Conference on Artificial Intelligence and Computer Science 2013, 25-26 November 2013 , Bayview, Langkawi, Kedah. pp. 227-233..

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Crowd behaviour detection is becoming a significant research topic in surveillance system in public places. This paper presents a method for the detection of abnormality in crowded scenes based on Social Force Model. For this purpose, Horn-Schunck optical flow is used in order to find the flow vector for all video frames. Using the vectors from this method, the interaction forces for each particle in video frames is calculated based on Social Force Model algorithm. The abnormal and normal frames are then classified by using a bag of words approach, whereby the region of anomalies in the abnormal frames are localized using interaction forces obtained in the previous experiment.

Item Type: Conference or Workshop Item (Speech)
Additional Information: E-ISBN: 978-967-11768-3-2
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Faculty/Division: Faculty of Electrical & Electronic Engineering
Depositing User: Noorul Farina Arifin
Date Deposited: 14 Feb 2014 02:29
Last Modified: 14 Mar 2018 07:39
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