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Crowd Counting for Static Images: A Survey of Methodology

Crowd Counting for Static Images: A Survey of Methodology

作     者:Ying Luo Jinhu Lu Baochang Zhang 

作者单位:School of Automation Science and Electrical EngineeringBeihang University Shenyuan Honors CollegeBeihang University School of Automation Science and Electrical EngineeringState Key Laboratory of Software Development Environmentand Beijing Advanced Innovation Center for Big Data and Brain ComputingBeihang University 

会议名称:《第三十九届中国控制会议》

会议日期:2020年

学科分类:08[工学] 080203[工学-机械设计及理论] 0802[工学-机械工程] 

关 键 词:Crowd counting crowd analysis pattern recognition computer vision 

摘      要:Crowd counting for static images is one of the typical application fields of image processing. it is essential to direct crowd analysis for public security purposes under the background of a rapidly growing social environment. Crowd counting for static images involves crucial challenges such as occlusions, scale variations, scene perspective distortions and diverse crowd distributions. It has now become an independent research hotspot. This paper investigates the literature of crowd counting tasks, summarizes the evolution of counting approaches, compares and analyzes traditional methods and current trends of CNN estimation-based counting, and then evaluates common datasets for crowd counting tasks. Conclusions concerning summarizations and prospects are made.

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