Page 104 - 《武汉大学学报（信息科学版）》2025年第6期

第 50 卷 第 6 期 武 汉 大 学 学 报（ 信 息 科 学 版 ） Vol.50 No.6
2025 年 6 月 Geomatics and Information Science of Wuhan University Jun. 2025

引文格式：朱军,丁永哲,游继钢，等 . 结构语义特征约束的地震灾害 AR 场景精准建模方法[J]. 武汉大学学报（信息科学版）,
2025,50(6):1126-1136.DOI:10.13203/j.whugis20240276
Citation：ZHU Jun,DING Yongzhe,YOU Jigang,et al.An Accurate Modeling Method of Earthquake Disaster AR Scene Con‑
strained by Structural Semantic Features[J]. Geomatics and Information Science of Wuhan University, 2025, 50(6): 1126-1136.
DOI:10.13203/j.whugis20240276

结构语义特征约束的地震灾害 AR 场景

精准建模方法

朱 军 1，2 丁永哲 游继钢 党 沛 杨文权 高雨涵 1
1
1
1
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1 西南交通大学地球科学与工程学院,四川 成都,611756
2 西南交通大学桥梁智能与绿色建造全国重点实验室，四川 成都,611756
摘 要：地震灾害具有突发性强、环境复杂等特点，增强现实(augmented reality, AR)场景建模对地震灾害应急救援具有
重要意义。现有 AR 场景建模方法在地震灾害场景下存在特征提取不准确、虚实融合建模精度低的问题，难以实现环境
复杂的地震灾害现场 AR 场景精准建模。因此，提出结构语义特征约束的地震灾害 AR 场景精准建模方法，首先，剖析地
震灾害场景特征，构建地震灾害现场结构语义特征库；其次，提出结构语义约束的地震灾害虚实特征提取方法，提高虚实
图像特征提取精准度；然后，基于虚实特征提取结果进行地震灾害 AR 场景虚实建模；最后，选择受损建筑作为实验案例
进行分析。实验结果表明，结构语义约束的地震灾害虚实特征提取方法 F1 分数达 90%，优化后的 AR 场景配准误差较直
接建模方法降低了 80%。所提方法实现了地震灾害 AR 场景的精准建模，为地震灾害应急救援提供了数字化场景支撑。
关键词：地震现场；增强现实；结构语义；特征约束；虚实融合建模
中图分类号：P237 文献标识码：A 收稿日期：2025‑01‑05
DOI：10.13203/j.whugis20240276 文章编号：1671‑8860（2025）06‑1126‑11
An Accurate Modeling Method of Earthquake Disaster AR Scene
Constrained by Structural Semantic Features

1
1，2
1
ZHU Jun DING Yongzhe YOU Jigang DANG Pei YANG Wenquan GAO Yuhan 1
1
1
1 Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu 611756, China
2 State Key Laboratory of Bridge Intelligent and Green Construction, Southwest Jiaotong University, Chengdu 611756, China
Abstract： Objectives: Earthquake disaster has become one of the natural disasters that pose a great threat
to human society, and it puts forward high requirements for the efficiency and accuracy of emergency res‑
cue. Augmented reality (AR) technology can provide more intuitive decision-making support for rescue per‑
sonnel by integrating virtual information into the real scene. However, the existing AR scene modeling
technologies face challenges in the complex environment of earthquake disaster. Methods: This paper pro‑
poses an accurate modelling method for earthquake disaster AR scenes with structural semantic feature con‑
straints. First, the characteristics of earthquake disaster scenes are analyzed, and the semantic feature li‑
brary of earthquake disaster scene structure is constructed. Second, the virtual-real feature extraction of
earthquake disasters with structural semantic constraints is proposed to improve the accuracy of virtual-real
image feature extraction. Then, the virtual-real modelling of the earthquake disaster AR scene is carried
out based on the results of virtual-real feature extraction. Finally, the damaged buildings are selected as the
experimental case area for experimental analysis. Results: Experimental results indicate that the proposed
method achieves an F1 score of 90% for earthquake disaster feature extraction based on structural semantic

基金项目：国家重点研发计划（2022YFC3005703）。
第一作者：朱军，博士，教授，研究方向为虚拟地理环境与灾害场景建模。vgezj@163.com
通信作者：游继钢，博士。vgeyjg523@my.swjtu.edu.cn