Initial applications of 3D Gaussian Splatting (3DGS) in Visual Simultaneous Localization and Mapping (VSLAM) demonstrate the generation of high-quality volumetric reconstructions from monocular video streams. However, despite these promising advancements, current 3DGS integrations have reduced tracking performance and lower operating speeds compared to traditional VSLAM. To address these issues, we propose integrating 3DGS with Direct Sparse Odometry, a monocular photometric SLAM system. We have done preliminary experiments showing that using Direct Sparse Odometry point cloud outputs, as opposed to standard structure-from-motion methods, significantly shortens the training time needed to achieve high-quality renders. Reducing 3DGS training time enables the development of 3DGS-integrated SLAM systems that operate in real-time on mobile hardware. These promising initial findings suggest further exploration is warranted in combining traditional VSLAM systems with 3DGS.

本研究针对当前3D高斯喷射在视觉同步定位与地图构建中的追踪性能下降和速度慢的问题，提出将3DGS与直接稀疏测程（Direct Sparse Odometry）相结合的新方法。实验结果显示，该方法显著减少了高质量渲染所需的训练时间，从而推动了在移动硬件上实现实时操作的3DGS集成SLAM系统的发展。

实时高斯喷射的研究：通过光度SLAM加速3DGS