多视图几何约束下的大场景三维高斯重建

doi:10.16182/j.issn1004731x.joss.25-0925

系统仿真学报 ›› 2026, Vol. 38 ›› Issue (8): 2353-2363.doi: 10.16182/j.issn1004731x.joss.25-0925

• 论文 • 上一篇

多视图几何约束下的大场景三维高斯重建

崔浩浩¹, 邸彦强¹, 刘青¹^,², 孟宪国¹

^1.陆军工程大学石家庄校区，河北石家庄 050003
^2.河北科技大学经济管理学院，河北石家庄 050018

收稿日期:2025-09-23 修回日期:2025-11-05 出版日期:2026-08-28 发布日期:2026-08-31
通讯作者: 邸彦强
第一作者简介:崔浩浩(1987-)，男，讲师，博士生，研究方向为武器系统仿真。

Three-dimensional Gaussian Reconstruction of Large-scale Scenes Under Multi-view Geometry Constraints

Cui Haohao¹, Di Yanqiang¹, Liu Qing¹^,², Meng Xianguo¹

^1.Shijiazhuang Campus, Army Engineering University of PLA, Shijiazhuang 050003, China
^2.School of Economics and Management, Hebei University of Science and Technology, Shijiazhuang 050018, China

Received:2025-09-23 Revised:2025-11-05 Online:2026-08-28 Published:2026-08-31
Contact: Di Yanqiang

摘要/Abstract

摘要：

为提升高斯泼溅算法(GS)在大场景重建中的几何重建质量，提出一种使用多视图几何重建结果为约束的优化 方法。使用2D高斯平面为几何基元以克服深度各向异性，引入由DUSt3R生成并经稀疏点云对齐的稠密深度图作为约束。通过设计几何与渲染解耦的多阶段优化策略，解决了多目标训练的梯度冲突问题。在MatrixCity数据集上的实验表明：该方法在大场景的几何重建质量与渲染质量相关指标方面超越了对比方法。多视图重建结果证明了对于提升GS算法几何重建质量的有效性。

关键词: 高斯泼溅, 大场景重建, 2D高斯, 多视图重建, 几何重建质量

Abstract:

To enhance the geometry reconstruction quality of the GS algorithm in large-scale scene reconstruction, an optimization method constrained by multi-view geometry reconstruction results was proposed. 2D Gaussian planes were used as geometric primitives to overcome depth anisotropy, and dense depth maps generated by DUSt3R and aligned by sparse point clouds were introduced as constraints. By designing a multi-stage optimization strategy that decouples geometry and rendering, the gradient conflict problem in multi-objective training was solved. Experiments on the MatrixCity dataset indicate that the method surpasses comparison methods in related indicators of geometry reconstruction quality and rendering quality in large-scale scenes. The multi-view reconstruction results demonstrate the effectiveness in improving the geometry reconstruction quality of the GS algorithm.

Key words: Gaussian splatting, large-scale scene reconstruction, 2D Gaussian, multi-view reconstruction, geometry reconstruction quality

中图分类号:

TP391.9

崔浩浩,邸彦强,刘青等 . 多视图几何约束下的大场景三维高斯重建[J]. 系统仿真学报, 2026, 38(8): 2353-2363.

Cui Haohao,Di Yanqiang,Liu Qing,et al . Three-dimensional Gaussian Reconstruction of Large-scale Scenes Under Multi-view Geometry Constraints[J]. Journal of System Simulation, 2026, 38(8): 2353-2363.

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参考文献 21

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方法	MatrixCity-Aerial				MatrixCity-Street
方法	R_PSN	P	R	F₁	R_PSN	P	R	F₁
SuGaR	OOM	OOM	OOM	OOM	19.82	0.053	0.111	0.071
2DGS	21.35	0.207	0.390	0.270	21.50	0.334	0.659	0.443
GOF	17.42	FAIL	FAIL	FAIL	20.32	0.219	0.473	0.300
CityGS	27.46	0.362	0.637	0.462	22.98	0.283	0.689	0.401
CityGS V2	27.23	0.441	0.752	0.556	22.19	0.376	0.759	0.503
本文方法	27.25	0.509	0.767	0.612	22.45	0.419	0.780	0.546

方法	MatrixCity-Aerial			MatrixCity-Street
方法	SSIM	R_PSN	LPIPS	SSIM	R_PSN	LPIPS
SuGaR	OOM	OOM	OOM	0.662	19.82	0.478
2DGS	0.632	21.35	0.562	0.723	21.50	0.477
GOF	0.374	17.42	0.588	0.703	20.32	0.440
CityGS	0.865	27.46	0.204	0.808	22.98	0.301
CityGS V2	0.857	27.23	0.169	0.784	22.19	0.382
本文方法	0.859	27.25	0.174	0.795	22.45	0.341

方法	平均误差
不考虑置信图+Procrustes	0.188 2
考虑置信图+Procrustes	0.119 1
考虑置信图+RANSAC	0.035 0

优化阶段	MatrixCity-Aerial
优化阶段	R_PSN	P	R	F₁
单阶段	27.16	0.508	0.763	0.610
多阶段	27.25	0.509	0.767	0.612

多视图几何约束下的大场景三维高斯重建

Three-dimensional Gaussian Reconstruction of Large-scale Scenes Under Multi-view Geometry Constraints

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