'Maximizing Rigidity' Revisited: A Convex Programming Approach for Generic 3D Shape Reconstruction from Multiple Perspective Views

Pan Ji, Hongdong Li, Yuchao Dai, Ian Reid

科研成果: 书/报告/会议事项章节会议稿件同行评审

15 引用 (Scopus)

摘要

Rigid 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.

源语言英语
主期刊名Proceedings - 2017 IEEE International Conference on Computer Vision, ICCV 2017
出版商Institute of Electrical and Electronics Engineers Inc.
929-937
页数9
ISBN(电子版)9781538610329
DOI
出版状态已出版 - 22 12月 2017
活动16th IEEE International Conference on Computer Vision, ICCV 2017 - Venice, 意大利
期限: 22 10月 201729 10月 2017

出版系列

姓名Proceedings of the IEEE International Conference on Computer Vision
2017-October
ISSN(印刷版)1550-5499

会议

会议16th IEEE International Conference on Computer Vision, ICCV 2017
国家/地区意大利
Venice
时期22/10/1729/10/17

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