Quasi-dense Wide Baseline Matching for Three Views

This paper proposes a method for computing a quasi-dense set of matching points between three views of a scene. The method takes a sparse set of seed matches between pairs of views as input and then propagates the seeds to neighboring regions. The proposed method is based on the best-first match propagation strategy, which is here extended from two-view matching to the case of three views. The results show that utilizing the three-view constraint during the correspondence growing improves the accuracy of matching and reduces the occurrence of outliers. In particular, compared with two-view stereo, our method is more robust for repeating texture. Since the proposed approach is able to produce high quality depth maps from only three images, it could be used in multi-view stereo systems that fuse depth maps from multiple views.