WxBS: Wide Baseline Stereo Generalizations

Abstract

We present a generalization of the wide baseline two view matching problem - WXBS, where X stands for a different subset of “wide baselines" in acquisition conditions such as geometry, illumination, sensor and appearance. We introduce a novel dataset of groundtruthed image pairs which include multiple "wide baselines" and show that state-of-the-art matchers fail on almost all image pairs from the set. A novel matching algorithm for addressing the WXBS problem is introduced and we show experimentally that the WXBS-M matcher dominates the state-of-the-art methods both on the new and existing datasets.