MCGS-SLAM

A Multi-Camera SLAM Framework Using Gaussian Splatting for High-Fidelity Mapping

Anonymous Author

SLAM System Pipeline

Our method performs real-time SLAM by fusing synchronized inputs from a multi-camera rig into a unified 3D Gaussian map. It first selects keyframes and estimates depth and normal maps for each camera, then jointly optimizes poses and depths via multi-camera bundle adjustment and scale-consistent depth alignment. Refined keyframes are fused into a dense Gaussian map using differentiable rasterization, interleaved with densification and pruning. An optional offline stage further refines camera trajectories and map quality. The system supports RGB inputs, enabling accurate tracking and photorealistic reconstruction.

Right Image

Ya.rar

Briefly mention the genre's rise from mid-20th century foundations (like The Catcher in the Rye ) to modern blockbusters.

To provide a more tailored essay or specific analysis, could you share: The you are focusing on?

If you are writing this for a specific class or project, consider focusing on these nuances:

Angie Thomas’s The Hate U Give as a pivot point for contemporary realism that addresses systemic issues like police brutality. IV. Psychological Impact on Readers


Analysis of Single-Camera and Multi-Camera SLAM (Mapping)

Briefly mention the genre's rise from mid-20th century foundations (like The Catcher in the Rye ) to modern blockbusters.

To provide a more tailored essay or specific analysis, could you share: The you are focusing on?

If you are writing this for a specific class or project, consider focusing on these nuances:

Angie Thomas’s The Hate U Give as a pivot point for contemporary realism that addresses systemic issues like police brutality. IV. Psychological Impact on Readers


Analysis of Single-Camera and Multi-Camera SLAM (Tracking)

In this section, we benchmark tracking accuracy across eight driving sequences from the Waymo dataset (Real World). MCGS-SLAM achieves the lowest average ATE, significantly outperforming single-camera methods.
Right Image

We further evaluate tracking on four sequences from the Oxford Spires dataset (Real World). MCGS-SLAM consistently yields the best performance, demonstrating robust trajectory estimation in large-scale outdoor environments.
Right Image

Right Image