AI RESEARCH
Noise2Params: Unification and Parameter Determination from Noise via a Probabilistic Event Camera Model
arXiv CS.CV
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ArXi:2605.16317v1 Announce Type: new Accurate, unified models for event cameras (ECs) remain elusive, hampering calibration and algorithm design. We develop a foundational probabilistic model for EC event detection, grounded in photon statistics, that unifies the description of static scene noise events and step response curves (S-curves) within a single analytical framework. Three formulations of the probability distributions are derived, spanning all intensity regimes: exact Poisson, saddle-point, and Gaussian.