MCGS-SLAM

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

Anonymous Author
Code and data [Available Upon Acceptance]

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.

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Ajb08639 Mp4 May 2026

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

: If your standard video player won't open it, try VLC Media Player . It can play almost any MP4 regardless of the specific codec used.

: If this is a specific viral video or a known error code, try searching for the name on platforms like YouTube or TikTok, as some users title their uploads with the original file name. Ajb08639 mp4

Could you provide more context on or what you expect it to contain? : If your standard video player won't open

: Use a tool like MediaInfo to look at the file's metadata. This might reveal the camera brand or software that created the video. Could you provide more context on or what

: If this file was downloaded from a website or received via email, verify the sender. Specific codes like this are often used by automated systems (e.g., CCTV exports or dashcams).

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.
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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.
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