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Unsupervised Progressive Structure-from-Motion for Unordered Images
Du YK(杜英魁); Fan BJ(范保杰); Tang YD(唐延东); Han JD(韩建达)
Department机器人学研究室
Conference Name2012 IEEE International Conference on Robotics and Biomimetics (ROBIO 2012)
Conference DateDecember 11-14, 2012
Conference PlaceGuangzhou, China
Author of SourceIEEE Robotics and Automation Society
Source PublicationProceedings of the 2012 IEEE International Conference on Robotics and Biomimetics
PublisherIEEE Computer Society
Publication PlaceWashington, DC, USA
2012
Pages72-78
Indexed ByEI ; CPCI(ISTP)
EI Accession number20131716243786
WOS IDWOS:000321004000021
Contribution Rank1
ISBN978-1-4673-2125-9
AbstractA robust progressive structure from motion (PSFM) method is proposed for unordered images. Our method can reduce accumulative error efficiently during scene dense recovery and camera motion estimation. The whole unordered images are divided into two classes: key frames and non-key frames. For key frames, superior features are selected and tracked to initialize the parameters of PSFM reliably and reduce the accumulative errors. During the implementation of PSFM, several novel and efficient strategies are proposed to detect the parameter estimation errors and remove the outliers in feature tracking. A local on-demand scheme is proposed to dramatically reduce the computing cost of sparse bundle adjustment. The experimental results from different scenes show that our method is efficient and robust in scene dense recovery and camera motion estimation.
Language英语
Citation statistics
Document Type会议论文
Identifierhttp://ir.sia.cn/handle/173321/10365
Collection机器人学研究室
Corresponding AuthorDu YK(杜英魁)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.College of Automation, Nanjing University of Posts and Telecommunications, Nanjing 210046, China
Recommended Citation
GB/T 7714
Du YK,Fan BJ,Tang YD,et al. Unsupervised Progressive Structure-from-Motion for Unordered Images[C]//IEEE Robotics and Automation Society. Washington, DC, USA:IEEE Computer Society,2012:72-78.
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