The problem of structure from motion (SFM) is to obtain a 3D model of a scene using multiple images taken from different camera locations. Traditional SFM algorithms using just two images often produce inaccurate 3D reconstructions, mainly due to incorrect estimation of the camera's motion. More recent algorithms have used multiple (>2) image sequences. This paper describes a new incremental algorithm for reconstructing structure from multi-image sequences which estimates and corrects for the error in computing the camera motion. Experimental results of the algorithm are reported on one synthetic and three real image sequences. Unlike many previous incremental algorithms, the new algorithm in principle is capable of reconstructing a 3D model of the scene to arbitrary accuracy given a sufficient number of images. It is demonstrated experimentally that the algorithm gives superior results compared to others which do not correct for the error in recovering motion.

In structure from motion algorithms, the error in the estimated motion affects each reconstructed 3-D point in a systematic way. The authors attempt to isolate the effect of the motion error as correlations in the structure error and show theoretically that these correlations can improve existing multi-frame structure from motion techniques. Experimental results and previously reported work confirm the theoretical predictions.>