Collision-Line Counting Method Using DeepSORT to Count Pedestrian Flow Density and Hungary Algorithm
Yuncheng Pei, Haiying Liu, Qiancheng Bei · 2021 IEEE 3rd International Conference on Civil Aviation Safety and Information Technology (ICCASIT) · 2021
With the great success of deep learning in the field of machine vision, crowd density statistics based on machine vision have become more and more important in today's world. In order to calculate the density of people flow in a certain area, this paper combines the YOLOv4 objective detection algorithm and the DeepSORT multi-objective tracking algorithm, and uses the Kalman filter algorithm and the Hungarian algorithm for trajectory prediction and data association. And it is proposed to carry out density statistics through the Collision-line counting method. This method uses the ID information and trajectory information of pedestrians in the objective tracking process to count the number of people and directions passing through a certain set line segment, and indirectly count the density of pedestrian flow in the corresponding area. This method can also be used in conjunction with multiple cameras at multiple entrances and exits in a certain area, and has the characteristics of flexible operation and high precision. In addition, this method can also be used to detect traffic flow.