Mohammed Alarfaj1, Mahwish Pervaiz2, Yazeed Yasin Ghadi3, Tamara al Shloul4, Suliman A. Alsuhibany5, Ahmad Jalal6, Jeongmin Park7,*
Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 2655-2671, 2023, DOI:10.32604/iasc.2023.027205
Abstract With the dramatic increase in video surveillance applications and public safety measures, the need for an accurate and effective system for abnormal/suspicious activity classification also increases. Although it has multiple applications, the problem is very challenging. In this paper, a novel approach for detecting normal/abnormal activity has been proposed. We used the Gaussian Mixture Model (GMM) and Kalman filter to detect and track the objects, respectively. After that, we performed shadow removal to segment an object and its shadow. After object segmentation we performed occlusion detection method to detect occlusion between multiple human silhouettes and we implemented a novel method… More >
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