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Tracking and Analysis of Pedestrian’s Behavior in Public Places

Computers, Materials & Continua 2023年第1期74卷 841-853页

作者： Mahwish Pervaiz Mohammad Shorfuzzaman Abdulmajeed Alsufyani Ahmad Jalal Suliman A.Alsuhibany Jeongmin Park Department of Computer Science Bahria UniversityIslamabadPakistan Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Air UniversityIslamabadPakistan Department of Computer Science College of ComputerQassim UniversityBuraydah51452Saudi Arabia Department of Computer Engineering Tech University of Korea237 Sangidaehak-roSiheung-si15073Gyeonggi-doKorea

Crowd management becomes a global concern due to increased population in urban *** management of pedestrians leads to improved use of public *** of pedestrian’s is a major factor of crowd management in public *** are multiple applications available in this area but the challenge is open due to complexity of crowd and depends on the *** this paper,we have proposed a new method for pedestrian’s behavior *** filter has been used to detect pedestrian’s usingmovement based ***,we have performed occlusion detection and removal using region shrinking method to isolate occluded *** verification is performed on each human silhouette and wavelet analysis and particle gradient motion are extracted for each *** Wolf Optimizer(GWO)has been utilized to optimize feature set and then behavior classification has been performed using the Extreme Gradient(xg)boost *** has been evaluated using pedestrian’s data from avenue and UBI-Fight datasets,where both have different *** mean achieved accuracies are 91.3%and 85.14%over the Avenue and UBI-Fight datasets,*** results are more accurate as compared to other existing methods.

关键词： Crowd management kalman filter region shrinking xg-boost classifier

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