A Robust Method for the Estimation of Reliable Wide Baseline Correspondences

In this paper we present a complete method to retrieve reliable correspondences among wide baseline images, that is images of the same scene/object acquired from very different viewpoints. We propose a solution based on matching of affine co-variant features, composed by the following four steps: interest region detection, normalization, description and matching. In our method we implemented improved versions of some techniques recently introduced in the literature: the MSER detector (maximally stable extremal regions) and SIFT and RIFT descriptors (scale/rotation invariant feature transform). After a general introduction to the wide baseline problems and a summary of the recent state-of-the-art solutions, we illustrate the proposed method detailing the added improvements, then we present some experimental results obtained on wide baseline images.