郑舟轩 王勇 王瑛

摘要：多目标跟踪领域以基于检测的跟踪方法为主，CenterTrack算法提出了以目标中心点为检测对象，每帧输出基于目标中心点生成的热图以辅助下一帧的检测和跟踪的方法。此方法在保证帧率的前提下有效提升了多目标跟踪准确率，但由于其缺乏对目标重识别的关注，当目标遭遇到遮擋或噪声影响从检测结果中丢失时无法将随后重新出现的同一目标识别为原目标，导致ID切换较频繁。该文在CenterTrack算法模型中加入近期丢失跟踪链队列和重识别模块以改善其在重识别方面的表现。输入商场监控录像并取得跟踪结果后，根据行人目标移动与停驻时间分配权值生成商场热点图，帮助经营者提升销售能力。

关键词： 计算机视觉; 多目标跟踪; CenterTrack算法; 目标重识别; 商场热点图; MOTA（多目标跟踪准确率）

中图分类号：TP391      文献标识码：A

文章编号：1009-3044（2021）36-0106-03

开放科学（资源服务）标识码（OSID）：

Shopping Mall Heat Map Generation Method Based on Multi-object Tracking

ZHENG Zhou-xuan， WANG Yong， WANG Ying

（School of Computer Science and Technology， Guangdong University of Technology， Guangzhou 510006， China）

Abstract：The field of multi-object tracking is based on tracking-by-detection methods. The CenterTrack algorithm proposes a method that uses the center of the object as the detection target， and outputs a heat map generated based on the center of the target for each frame to assist the detection and tracking of the next frame. This method effectively improves multi-object tracking accuracy under the premise of ensuring the frame rate. However， due to its lack of attention to target re-identification， when the target encounters occlusion or the influence of noise， thus lost from the detection result， it cannot reappear as the same object. The object is not recognized as the original object， which leads to frequent ID switching. This paper adds a recently lost tracks queue and re-identification module to the CenterTrack to improve its performance in re-identification. After the input of the shopping mall surveillance video data and obtaining the tracking results， the shopping mall heat map is generated according to the weights of pedestrian target movement and staying time to help shop owners improve sales.

Key words：computer vision;  multi-object tracking;  CenterTrack algorithm;  target re-identification;  shopping mall heat map;  MOTA（Multi-Object Tracking accuracy）

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在许多高出货……