Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/111347
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dc.contributor.authorJi, P.-
dc.contributor.authorLi, H.-
dc.contributor.authorDai, Y.-
dc.contributor.authorReid, I.-
dc.date.issued2017-
dc.identifier.citationProceedings / IEEE International Conference on Computer Vision. IEEE International Conference on Computer Vision, 2017, vol.2017-October, pp.929-937-
dc.identifier.isbn9781538610336-
dc.identifier.issn1550-5499-
dc.identifier.urihttp://hdl.handle.net/2440/111347-
dc.description.abstractRigid structure-from-motion (RSfM) and non-rigid structure-from-motion (NRSfM) have long been treated in the literature as separate (different) problems. Inspired by a previous work which solved directly for 3D scene structure by factoring the relative camera poses out, we revisit the principle of “maximizing rigidity” in structure-from-motion literature, and develop a unified theory which is applicable to both rigid and non-rigid structure reconstruction in a rigidity-agnostic way. We formulate these problems as a convex semi-definite program, imposing constraints that seek to apply the principle of minimizing non-rigidity. Our results demonstrate the efficacy of the approach, with stateof- the-art accuracy on various 3D reconstruction problems.-
dc.description.statementofresponsibilityPan Ji, Hongdong Li, Yuchao Dai, Ian Reid-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesIEEE International Conference on Computer Vision-
dc.rights© 2017 IEEE-
dc.source.urihttp://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=8234942-
dc.title"Maximizing rigidity" revisited: a convex programming approach for generic 3D shape reconstruction from multiple perspective views-
dc.typeConference paper-
dc.contributor.conferenceIEEE International Conference on Computer Vision (ICCV 2017) (22 Oct 2017 - 29 Oct 2017 : Venice, ITALY)-
dc.identifier.doi10.1109/ICCV.2017.106-
dc.publisher.placePiscataway, NJ-
dc.relation.granthttp://purl.org/au-research/grants/arc/CE140100016-
dc.relation.granthttp://purl.org/au-research/grants/arc/FL130100102-
dc.relation.granthttp://purl.org/au-research/grants/arc/DE140100180-
pubs.publication-statusPublished-
dc.identifier.orcidReid, I. [0000-0001-7790-6423]-
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Computer Science publications

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