TY - JOUR
AU - Pajdla, Tomas
AB - In this paper we consider the motion segmentation problem on sparse and unstructured datasets involving rigid motions, motivated by multibody structure from motion. In particular, we assume only two-frame correspondences as input without prior knowledge about trajectories. Inspired by the success of synchronization methods, we address this problem by introducing a two-stage approach: first, motion segmentation is addressed on image pairs independently; then, two-frame results are combined in a robust way to compute the final multi-frame segmentation. Our synthetic and real experiments demonstrate that the proposed approach is very effective in reducing the errors among two-frame results and it can cope with a large amount of mismatches. Moreover, our method can be profitably used to build a multibody structure from motion pipeline.
TI - Multi-frame Motion Segmentation by Combining Two-Frame Results
JF - International Journal of Computer Vision
DO - 10.1007/s11263-021-01544-x
DA - 2022-03-01
UR - https://www.deepdyve.com/lp/springer-journals/multi-frame-motion-segmentation-by-combining-two-frame-results-c4z0DxcNe7
SP - 696
EP - 728
VL - 130
IS - 3
DP - DeepDyve
ER -