Hybrid Matching of Uncalibrated Omnidirectional and Perspective Images

Abstract

This work presents an automatic hybrid matching of central catadioptric and perspective images. It is based on the hybrid epipolar geometry. The goal is to obtain correspondences between an omnidirectional image and a conventional perspective image taken from different points of view. Mixing both kind of images has multiple applications, since an omnidirectional image captures many information and perspective images are the simplest way of acquisition. Scale invariant features with a simple unwrapping are considered to help the initial putative matching. Then a robust technique gives an estimation of the hybrid fundamental matrix, to avoid outliers. Experimental results with real image pairs show the feasibility of that hybrid and difficult