基于AR技术的文物数字化三维图像重建方法

doi:10.11996/JG.j.2095-302X.2025020369

图学学报 ›› 2025, Vol. 46 ›› Issue (2): 369-381.DOI: 10.11996/JG.j.2095-302X.2025020369

• 计算机图形学与虚拟现实 • 上一篇下一篇

基于AR技术的文物数字化三维图像重建方法

周伟(), 苍慜楠(), 程浩宗

西安理工大学艺术与设计学院，陕西西安 710048

收稿日期:2024-08-17 接受日期:2024-12-13 出版日期:2025-04-30 发布日期:2025-04-24
通讯作者:苍慜楠(1982-)，男，副教授，硕士。主要研究方向为文化遗产数字化与智能交互、数字媒体艺术理论。E-mail：cangminnan@xaut.edu.cn
第一作者:周伟(1998-)，男，硕士研究生。主要研究方向为文化遗产数字化与智能交互。E-mail：1944692418@qq.com
基金资助:
教育部人文社会科学研究规划基金(23YJA760004);西安理工大学人文社会科学研究专项(106-451623007)

Research on the method of 3D image reconstruction for cultural relics based on AR technology

ZHOU Wei(), CANG Minnan(), CHENG Haozong

School of Art and Design, Xi’an University of Technology, Xi’an Shaanxi 710048, China

Received:2024-08-17 Accepted:2024-12-13 Published:2025-04-30 Online:2025-04-24
First author：ZHOU Wei (1998-), master student. His main research interests cover digitization and intelligent interaction of cultural heritage. E-mail：1944692418@qq.com
Supported by:
Humanities and Social Sciences Research Planning Fund Project of the Ministry of Education(23YJA760004);Special Project for Humanities and Social Sciences Research of Xi’an University of Technology(106-451623007)

摘要/Abstract

摘要：

文物表面存在复杂多变的细节，要求数据采集过程需有极高的精度，以确保重建模型的原真性与准确性。然而，传统的方法难以在保持高效率的同时实现高精度，且后续的三维模型构建与纹理映射也极为复杂，需大量的手工调整。为此，提出一种基于AR技术的文物实体数字化三维图像重建方法。首先利用三维扫描与高分辨率相机，采集文物实体的点云数据和图像数据，并利用SIFT算法分别获取2类数据的特征点。依据特征点，利用Revit软件结合SketchUp和Geomagic Studio等工具，构建文物实体三维模型。通过实施虚拟相机三维注册操作，将建立的文物实体三维模型叠加在现实文物图像上，得到叠加后的虚拟文物模型。进一步，将现实文物与叠加后的虚拟文物模型实施虚拟融合，完成文物实体数字化三维图像重建。最终，结合VR技术，对重建的三维数字化图像实施交互式展示。以石峁相关文物数据集进行采集实验，结果表明，该方法能够精准重建文物的数字化三维模型。通过对比实验，该方法在三维重建精度与纹理映射上优于传统方法，减少了人工调整的工作量。有效解决传统数字三维图像重建中存在的精度不足与和操作繁琐等问题，能够高效且准确地完成文物数字化重建，为文物保护、虚拟展示及文化遗产的数字化存档提供了新的技术路径。

关键词: 增强现实, 三维重建, 文物数字化, 三维注册, 虚实融合

Abstract:

The surfaces of cultural relics possess complex and variable details, necessitating an exceptionally high level of precision in the data acquisition process to ensure the authenticity and accuracy of the reconstructed models. However, traditional methods often fail to achieve high precision while maintaining efficiency, and the subsequent processes of 3D model construction and texture mapping are highly complex, requiring substantial manual adjustments. To address these challenges, a method based on augmented reality (AR) was proposed for the digital three-dimensional image reconstruction of cultural relics. This method employed 3D scanning and high-resolution cameras to capture point cloud data and image data of the relics. The Scale-Invariant Feature Transform (SIFT) algorithm was utilized to extract feature points from both types of data. Based on these feature points, Revit software, in combination with SketchUp and Geomagic Studio, was used to construct the three-dimensional models of the cultural relics. Through virtual camera registration, the constructed 3D models were overlaid onto images of the actual relics, resulting in augmented virtual models. Subsequently, the real relics and the overlaid virtual models underwent virtual fusion, completing the digital three-dimensional image reconstruction of the cultural relics. Finally, by integrating virtual reality (VR) technology, interactive displays of the reconstructed digital 3D images were implemented. Experiments conducted using the Shimao cultural relics dataset as the experimental subject demonstrated that this method can accurately reconstruct digital 3D models of the relics. Comparative experiments indicated that the proposed method outperformed traditional approaches in both 3D reconstruction accuracy and texture mapping, while reducing the need for manual adjustments. This method effectively addressed the issues of insufficient precision and cumbersome operations inherent in traditional digital 3D image reconstruction, enabling efficient and accurate digital reconstruction of cultural relics. It provided a novel technological pathway for the preservation, virtual display, and digital archiving of cultural heritage.

Key words: augmented reality, 3D reconstruction, digitization of cultural relics, 3D registration, virtual real fusion

中图分类号:

TP391
K87

周伟, 苍慜楠, 程浩宗. 基于AR技术的文物数字化三维图像重建方法[J]. 图学学报, 2025, 46(2): 369-381.

ZHOU Wei, CANG Minnan, CHENG Haozong. Research on the method of 3D image reconstruction for cultural relics based on AR technology[J]. Journal of Graphics, 2025, 46(2): 369-381.

图/表 12

图1 基于SIFT算法提取文物特征点流程图

Fig. 1 Extracting feature points of cultural relics based on SIFT algorithm

表1 配准误差结果/mm

Table 1 Registration error results/mm

场景	场景描述	RMS 误差	Hausdorff 距离
场景1	具有多样几何形态的复杂表面雕刻物体	0.043	0.080
场景2	具有精细纹理的陶瓷物体	0.039	0.077
场景3	相对平滑的木雕艺术品	0.042	0.075
场景4	复杂表面纹理的岩画	0.040	0.079

图2 文物实体数字化三维图像重建框架

Fig. 2 The framework for digital 3D image reconstruction of cultural relics

图3 虚拟相机三维注册流程

Fig. 3 The process of 3D registration using a virtual camera

图4 虚实融合成像示意图

Fig. 4 Schematic diagram of virtual and real fusion imaging

表2 实验主要参数

Table 2 Main parameters of the experiment

名称	数值
三维扫描仪	CR-Scan Ferret
扫描站	10
采样点密度	1.5 mm
测量距离	3~5 m
工业相机	JHEM131GC-L
采样帧频	30 fps
LED灯	YMFB-7
数据采集卡	NIPCI/PXI-662
计算机	ADVANTECH-MIC-7700
VR平台	SteamVR

图5 文物数据采集平台

Fig. 5 Cultural relic data collection platform

表3 应用本文方法重建的模型与几何差异评估结果

Table 3 The model reconstructed by the method in this paper is used to evaluate the geometric differences

场景	名称	RMS误差/mm	Hausdorff距离/mm
简单几何形态	玉琮	0.035	0.052
简单几何形态	铜尺环	0.028	0.048
复杂几何形态	11号石雕(横)	0.041	0.061
复杂几何形态	立柱石雕(竖)	0.030	0.050
多种材质	鱼形佩	0.027	0.045
	绿松石串	0.032	0.053
	玉人头像	0.033	0.055
	玉环	0.036	0.059
	手串	0.034	0.057
	青铜臂钏	0.031	0.051
	陶鹰	0.030	0.052
	口簧	0.029	0.061

图6 应用本文方法的文物实体数字化三维图像重建结合虚拟现实交互结果展示((a)虚拟平台；(b)触碰界面；(c)语音介绍；(d)旋转缩放模型)

Fig. 6 The digital 3D image reconstruction of cultural relic entities using the method in this article combined with virtual reality interactive results display ((a) Virtual platform; (b) Touch interface; (c) Voice introduction; (d) Rotatable and scalable model)

图7 所提特征点提取方法性能测试

Fig. 7 Performance test of the proposed feature point extraction method

图8 虚实融合性能测试可视化图((a)几何一致性；(b)光照一致性；(c)三维误差分布；(d)综合效果)

Fig. 8 Virtual and real fusion performance test ((a) Geometric consistency; (b) Illumination consistency; (c) 3D error distribution; (d) Comprehensive effect)

表4 本文方法与其他3种方法在不同场景下的精度和效率对比结果

Table 4 Comparison results of the accuracy and efficiency of this article’s method with the other three methods in different scenarios

方法	RMS误差/mm			Hausdorff 距离/mm	平均计算时间/s
方法	场景1	场景2	场景3	Hausdorff 距离/mm	平均计算时间/s
本文	0.040	0.045	0.043	0.08	120
NeRF	0.065	0.075	0.070	0.10	180
MVS	0.055	0.065	0.060	0.09	150
ICP	0.080	0.085	0.078	0.12	90

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基于AR技术的文物数字化三维图像重建方法

Research on the method of 3D image reconstruction for cultural relics based on AR technology

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