FreeArtGS: 自由移动场景下的关节高斯溅射重建
FreeArtGS: Articulated Gaussian Splatting Under Free-moving Scenario
AI总结：
FreeArtGS通过自由移动部分分割、关节估计和端到端优化，实现高可扩展性的自由移动关节物体重建，实验表明其在真实资产生成中具有实用性。
摘要：
随着增强现实和机器人技术的发展，对高可扩展性关节物体重建的需求增加。然而，现有方法在离散关节状态或随意单目视频重建中需要复杂的轴对齐或存在覆盖不足的问题。本文提出FreeArtGS，一种在自由移动场景下重建关节物体的新方法，采用简单的设置和高可扩展性。FreeArtGS结合自由移动部分分割、关节估计和端到端优化，仅需单目RGB-D视频作为输入。通过优化离线点跟踪和特征模型的先验信息，自由移动部分分割模块在无约束捕获下从相对运动中识别刚性部分。关节估计模块校准统一的物体到相机姿态，并从部分分割中稳健地恢复关节类型和轴。最后，基于3DGS的端到端优化用于联合重建关节物体的视觉纹理、几何和关节角度。我们在两个基准和真实世界自由移动关节物体上进行了实验。实验结果表明，FreeArtGS在自由移动关节物体重建中表现一致，且在先前重建设置中保持高度竞争力，证明其在现实资产生成中是一种实用有效的解决方案。项目页面可访问：https://freeartgs.github.io/
英文摘要：
The increasing demand for augmented reality and robotics is driving the need for articulated object reconstruction with high scalability. However, existing settings for reconstructing from discrete articulation states or casual monocular videos require non-trivial axis alignment or suffer from insufficient coverage, limiting their applicability. In this paper, we introduce FreeArtGS, a novel method for reconstructing articulated objects under free-moving scenario, a new setting with a simple setup and high scalability. FreeArtGS combines free-moving part segmentation with joint estimation and end-to-end optimization, taking only a monocular RGB-D video as input. By optimizing with the priors from off-the-shelf point-tracking and feature models, the free-moving part segmentation module identifies rigid parts from relative motion under unconstrained capture. The joint estimation module calibrates the unified object-to-camera poses and recovers joint type and axis robustly from part segmentation. Finally, 3DGS-based end-to-end optimization is implemented to jointly reconstruct visual textures, geometry, and joint angles of the articulated object. We conduct experiments on two benchmarks and real-world free-moving articulated objects. Experimental results demonstrate that FreeArtGS consistently excels in reconstructing free-moving articulated objects and remains highly competitive in previous reconstruction settings, proving itself a practical and effective solution for realistic asset generation. The project page is available at: https://freeartgs.github.io/
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
