Plane detection from monocular image sequences

Abstract

Planes are important geometric features and can be used in a wide range of applications. This work aims to illustrate a homography-based method to detect planes using the affine model. Using two image frames from a monocular sequence, a set of match pairs of interest points is obtained using Harris corner detector combined with the Scale Invariant Feature Transform (SIFT) as local descriptor. A Delaunay triangulation is performed on the set of detected corners of the first image and we use a triangle to calculate an affine homography that represents a plane in the image. An algorithm was developed to cluster interest points belonging to the same plane based on the reprojection error of the affine homography. Tests are performed in different sequences of indoor and outdoor images and results are shown