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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)
作者部门机器人学研究室
会议名称2012 IEEE International Conference on Robotics and Biomimetics (ROBIO 2012)
会议日期December 11-14, 2012
会议地点Guangzhou, China
会议主办者IEEE Robotics and Automation Society
会议录名称Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics
出版者IEEE Computer Society
出版地Washington, DC, USA
2012
页码72-78
收录类别EI ; CPCI(ISTP)
EI收录号20131716243786
WOS记录号WOS:000321004000021
产权排序1
ISBN号978-1-4673-2125-9
摘要A 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.
语种英语
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文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/10365
专题机器人学研究室
通讯作者Du YK(杜英魁)
作者单位1.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
推荐引用方式
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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