华南理工大学学报（自然科学版）2025，Vol.53Issue(7)：31-38,8.DOI:10.12141/j.issn.1000-565X.240427
基于多目近红外视觉的多目标实时跟踪方法
Multi-Object Real-Time Tracking Method Based on Multi-View Near-Infrared Vision
摘要
Abstract
Near-infrared optical tracking systems can restore the movement of tracked objects in real time based on the markers attached to the tracked objects.This technology has now been widely adopted across numerous fields.This paper proposed a real-time tracking method for muli-objects that is robust to target loss.First,based on the imaging characteristics of reflective marker balls in near-infrared cameras,the geometric center of each marker was extracted using the grayscale centroid method.Then,the SORT algorithm was used as a multi-objetcs tracking method in each monocular camera to match each marker point between frames.The matching relationship of the image points of the markers in each camera was determined based on the principle of epipolar geometry combined with the weighted bipartite graph matching method,and the three-dimensional spatial coordinates of each tracked marker were calculated in real time based on the triangulation method.Next,the markers were grouped based on their spatial relationships during motion to identify markers belonging to the same object.Spatial feature vectors were established for tracked objects using the Euclidean distances between markers within the same group,serving as matching references for reappearing lost objects.When a fully lost object reproduced,re-matching is performed using cosine distance of these feature vectors.Finally,the proposed algorithm was experimentally verified.The experiment shows that the tracking accuracy of the proposed algorithm can reach about 0.5 mm at a speed of not less than 60 f/s.In addition,the lost reproduced objects and markers can be correctly re-matched.关键词
多目视觉/近红外光学跟踪/立体匹配/反光标记球Key words
multi-view vision/near-infrared optical tracking/stereo matching/marker分类
信息技术与安全科学引用本文复制引用
陈忠,王傲辰,高心怡,何利辉,张宪民..基于多目近红外视觉的多目标实时跟踪方法[J].华南理工大学学报（自然科学版）,2025,53(7):31-38,8.基金项目
广东省自然科学基金项目(2022A1515011263)Supported by the Natural Science Foundation of Guangdong Province(2022A1515011263) （2022A1515011263）
