Robust sequence proximity estimation by radial distance hashing

There is a recent growing interest in image analysis of multiple views of a scene, often involving aspects of reconstruction, mosaicing and new view generation. As the availability of multiple camera systems augments, we suggest that such tasks could be carried out where the image source is a set of unsynchronized and uncalibrated cameras moving arbitrarily in a 3D scene. In order to make efficient use of this data, it is necessary to define a measure of inter-sequence proximity. In this paper we suggest such a measure, based on pure 2D analysis, namely the ratios between image-space distances among a set of feature points. We show this measure to be sound, and propose a simple iterative method to robustly estimate the relative positions of the set of moving cameras, even in the presence of substantial amount of noise, and without computing egomotion.