Architectural scene rapid reconstruction based on features

Abstract

Retrieve the structure of model and the motion of camera is a classical and hot topic in computer vision and photogrammetry. A lot of automatic or semiautomatic techniques have been developed to optimize the retrieving processing from accuracy, stability and reality perspectives. These techniques are variant from data source, feature selection for matching, feature clustering and 3D model representation. The optimization algorithm and a completely automatic system are still under exploring. In this paper, we use some image-based algorithms for feature selection and matching of 3D man-made scene reconstruction. We present a robust point matching algorithm with RANSAC estimator, and compare two methods of line matching in a complex man-made environment. We point out the degeneracy when use epipolar line as a constraint to match line, instead use a global optimization method. Our experiments show that the proposed method is robust in a complex man-made scene.