Incremental Online Scene Reconstruction by 3D Gaussian Triangulation

Incremental scene reconstruction is essential for real-worldapplications. Although 3D Gaussian Splatting shows strong potential,most existing approaches require offline conversion of the optimized Gaus-sians into an intermediate implicit field for explicit mesh extraction,which hinders seamless integration with downstream tasks. To addressthis limitation, we propose a novel online framework that incrementallyreconstructs and updates high-fidelity explicit meshes by directly trian-gulating a dense geometric Gaussian representation, which supports bothhigh-quality rendering and incremental surface reconstruction. More-over, we present a direct meshing algorithm that efficiently extractsand updates the mesh from the Gaussian set. To ensure mesh accu-racy, we enforce a plane-based pulling constraint that dynamically aligns3D Gaussian primitives to the approximated local surface. Furthermore,our framework significantly reduces memory and computational overheadduring long-sequence processing by dynamically freezing fully optimizedhistorical regions. Experiments on public datasets demonstrate that ourmethod outperforms conventional Gaussian-based methods on both ren-dering quality and reconstruction accuracy.