Virtual Insertion: Robust Bundle Adjustment Over Long Video Sequences

Abstract

Our goal is to circumvent one of the roadblocks of using existing bundle adjustment algorithms for achieving satisfactory large-area structure from motion over long video sequences, namely, the need for sufficient visual features tracked across consecutive frames. We accomplish it by using a novel “”virtual insertion”” scheme, which constructs virtual points and virtual frames to adapt the existence of visual landmark link outage, namely “”visual breaks”” due to no common features observed from neighboring camera views in challenging environments. We show how to insert virtual point correspondences at each break position and its neighboring frames, by transforming initial motion estimations from non-vision sensors into 3D to 2D projection constraints of virtual scene landmarks. We also show how to add virtual frames to bridge the gap of non-overlapping field of view (FOV) across sequential frames. Experiments are conducted on several real-world challenging video sequences, collected by multi-sensor based visual odometry systems. We demonstrate our proposed scheme significantly improves bundle adjustment performance in both drift correction and reconstruction accuracy.