This document discusses quantifying, modeling, and applying techniques to address descriptor instability in image processing. It introduces the problem of descriptor instability, models the instability using Fisher vectors, and applies the Fisher vector approach on image classification tasks, achieving steady but marginal improvements over previous methods. In conclusion, descriptor instability is modeled as observational variance, with the Fisher vector technique treating it as a physical phenomenon that can be engineered to produce more robust descriptors.