西南交通大学学报2025，Vol.60Issue(3)：761-769,9.DOI:10.3969/j.issn.0258-2724.20230125
基于行人重识别的施工现场人员位置信息感知
Location Information Perception of Onsite Construction Crew Based on Person Re-identification
摘要
Abstract
To obtain location information of onsite construction crew continuously with the consideration of dynamical changing,occluding,and high appearance similarity in construction scenes,a computer vision-based location information perception method for onsite construction crew was proposed.Firstly,a deep learning-based object detection method was utilized to percept targets preliminarily.Then,a data association method based on person re-identification was used,where ID assignment was completed by matching the deep learning-based feature.A distance metric method based on re-ranking was utilized to optimize the similarity measurement results,and the matching result was processed by using a buffering mechanism and a dynamical feature updating mechanism,so as to mitigate mismatch due to difficulties in construction scenes.2D coordinates and movement information corresponding to ID were obtained using perspective transformation of images to provide basic data for productivity analysis.Finally,standard test videos were created from images collected at different construction stages to test the proposed method.The test results show that in different scenes,the average F1 score of ID(IDF1)and multiple object tracking accuracy(MOTA)of the algorithm are 85.4%and 75.4%,respectively.The proposed re-ranking method and post-processing mechanism for matching effectively improve the tracking accuracy.Compared with the algorithm after removing these optimization mechanisms,the average improvement of IDF1 and MOTA is 52.8%and 3.8%,respectively.关键词
智能建造/目标追踪/计算机视觉/行人重识别/生产力管理Key words
intelligent construction/target tracking/computer vision/person re-identification/productivity management分类
建筑与水利引用本文复制引用
杨彬,胡晋铭,张其林,汪丛军..基于行人重识别的施工现场人员位置信息感知[J].西南交通大学学报,2025,60(3):761-769,9.基金项目
国家重点研发计划(2018YFD110090506) （2018YFD110090506）
