One Capture, One Camera Family: Structured Camera Modeling for Light Field Gaussian Splatting

3D Gaussian Splatting (3DGS) has demonstrated remarkable performance for novel view synthesis, yet its conventional camera formulation is poorly matched to light field (LF) reconstruction. In particular, treating the sub-aperture views captured in a single LF exposure as independent cameras disregards their shared acquisition geometry and leads to inconsistent scene structure across views. To address this, we propose StructLFGS, a reconstruction framework built on the principle of one capture, one camera family. Specifically, we model all sub-aperture views as observations generated by a single structured camera family, which compresses the camera solution space from per-view 6-DoF states to a compact shared parameterization. Crucially, this reduction allows us to determine the canonical camera parameters directly from the observed angular trajectories. This defines a canonical frame shared by all views and eliminates per-view camera optimization. With this canonical family fixed, the trajectories are lifted into Gaussian primitives. Their disparity estimates further constrain optimization, making cross-view geometric consistency intrinsic to the representation. Extensive experiments on four LF benchmarks show that StructLFGS outperforms GS-based methods and remains competitive against LF-specific methods.