Line cue augmented perspective structure from motion

Abstract

Object shape and camera motion can be recovered from a sequence of images using a set of feature point correspondences. This is known as the structure from motion problem. This paper describes a method of employing geometrical features available in a scene, in the form of straight lines, in a factorization-based structure from motion application. The effects of inaccuracies of feature data can be reduced by constraining the reconstructed features corresponding to the points forming straight lines. Our main contribution in this paper is the use of such geometric features to refine the shape recovery using the current advancements in the factorization method. Reconstructed features are mapped to straight lines and the measurement matrix containing image feature data is updated with the adjusted data. This increases the accuracy of reconstruction perceptually as well as quantitatively. The algorithm consists of first obtaining the reconstruction using singular value decomposition. Mapping 3D lines to sets of feature points is then carried out. The measurement matrix is refined followed by a second phase of factorization and, optionally, normalization to obtain metric reconstruction. Results pertaining to both synthetic and actual sequences of images are presented.