Detection and Matching of Rectilinear Structures

Abstract

Indoor and outdoor urban environments posses many regularities which can be efficiently exploited and used for general image parsing tasks. We present a novel approach for detecting rectilinear structures and demonstrate their use for wide baseline stereo matching, planar 3D reconstruction, and computation of geometric context. Assuming a presence of dominant orthogonal vanishing directions, we proceed by formulating the detection of the rectilinear structures as a labeling problem on detected line segments. The line segment labels, respecting the proposed grammar rules, are established as the MAP assignment of the corresponding MRF. The proposed framework allows to detect both full as well as partial rectangles, rectangle-in-rectangle structures, and rectangles sharing edges. The use of detected rectangles is demonstrated in the context of difficult wide baseline matching tasks in the presence of repetitive structures and large appearance changes.