The Geometric Observability Index: Influence, Fisher Information, and Weak Observability in SE(3) Pose Estimation
Read the original on arXiv Computer Vision →The paper introduces the Geometric Observability Index (GOI), a per-feature sensitivity metric for SE(3) pose estimation that quantifies the pose perturbation induced by a single measurement via the Gauss‑Newton curvature restricted to the observable subspace. GOI is shown to equal the norm of the M‑estimator influence function, to coincide with the Fisher information operator, and its smallest observable eigenvalue determines both worst‑case measurement amplification and a finite‑sample stability radius. Experiments on synthetic data and real RGB‑D/KITTI sequences validate that GOI accurately predicts leave‑one‑out pose shifts and explains the robustness of residual gating while highlighting the pitfalls of raw‑influence gating in weakly observable geometries.
Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.