An End to End Framework to High Performance Geometry-Aware Multi-Scale Keypoint Detection and Matching in Fisheye Imag

This paper addresses the problem of robust feature detection and matching across different views of the same scene taken using two (or more) wide angle cameras, assuming that their intrinsic calibration parameters are approximately known. We introduce an end-to-end framework with an aim to enhance both precision and recall in the matching process, i.e. increase the number of correct matches across the fisheye images while reducing the number of false positive matches. Experimental results demonstrate the effectiveness of the proposed work.