Numerical characteristics of image geometric deformation parameters estimates convergence at stochastic gradient estimation

Abstract

Several approaches to the numerical description of image geometric deformations parameters estimates behavior at iterations of non-identification relay stochastic gradient estimation are considered. The probability density of the Euclidean mismatch distance of deformation parameters estimates vector is chosen as an argument of the characteristics forming the numerical values. It made it possible to ensure invariance to the set of parameters of the used inter-frame geometric deformations model. The mathematical expectation, the probability of exceeding a given threshold value of the convergence rate and the confidence interval of the Euclidean mismatch distance were investigated as characteristics. Probabilistic mathematical modeling is applied to calculate the probability density of the Euclidean mismatch distance. Examples of calculation are presented.