Similarity criteria: evaluating perceptual change for visual localization

Abstract

Visual localization systems may operate in environments that exhibit considerable perceptual change. This paper proposes a method of evaluating the degree of appearance change using a similarity criteria based on comparing the subspaces spanned by the principal components of the observed image descriptors. We propose two criteria - θmin measures the minimum angle between subspaces and Stotal measures the total similarity between the subspaces. These criteria are introspective - they evaluate the performance of the image descriptor using nothing more than the image descriptor itself. Furthermore, we demonstrate that these similarity criteria reflect the ability of the image descriptor to perform visual localization successfully, thus allowing a measure of quality control on the localization output.