Recursive Affine Structure and Motion from Image Sequences

Abstract

This paper presents a new algorithm for structure from motion from an arbitrary number of tracked features over an arbitrary number of images, which possesses several advantages over previous formulations. First, it is recursive, so the time complexity is independent of the number of images. The complexity is linear with the number of tracked features. The algorithm allows newly appeared features to be included, stale features to be discarded, and missing data to be handled naturally. Dynamic outlier elimination is achieved without recourse to heuristic segmentation strategies. Lastly, the algorithm can employ different kinds of tracked features, e.g. edges and corners, in the same framework. The actual structure from motion recovered is affine, which assumes limited depth variation within the field of view, but the recovery is based on a more general recursive estimation algorithm, known as the variable state dimension filter (VSDF), which we devised and applied earlier to active camera calibration. Results are presented for real image sequences, and timings for the algorithm demonstrate the feasibility for real-time implementation.