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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.<\/jats:p>","DOI":"10.1007\/s11263-021-01544-x","type":"journal-article","created":{"date-parts":[[2022,1,31]],"date-time":"2022-01-31T10:02:33Z","timestamp":1643623353000},"page":"696-728","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Multi-frame Motion Segmentation by Combining Two-Frame Results"],"prefix":"10.1007","volume":"130","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0331-4032","authenticated-orcid":false,"given":"Federica","family":"Arrigoni","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Elisa","family":"Ricci","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tomas","family":"Pajdla","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,31]]},"reference":[{"key":"1544_CR1","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1007\/s11263-019-01240-x","volume":"128","author":"F Arrigoni","year":"2020","unstructured":"Arrigoni, F., & Fusiello, A. 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