Mahwish Pervaiz¹, Mohammad Shorfuzzaman², Abdulmajeed Alsufyani², Ahmad Jalal³, Suliman A. Alsuhibany⁴, Jeongmin Park^5,*

CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 841-853, 2023, DOI:10.32604/cmc.2023.029629

Abstract Crowd management becomes a global concern due to increased population in urban areas. Better management of pedestrians leads to improved use of public places. Behavior of pedestrian’s is a major factor of crowd management in public places. There are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the environment. In this paper, we have proposed a new method for pedestrian’s behavior detection. Kalman filter has been used to detect pedestrian’s using movement based approach. Next, we have performed occlusion detection and removal using region shrinking method to isolate occluded… More >

Mohammed Alarfaj¹, Mahwish Pervaiz², Yazeed Yasin Ghadi³, Tamara al Shloul⁴, Suliman A. Alsuhibany⁵, Ahmad Jalal⁶, Jeongmin Park^7,*

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 >