Unsupervised Progressive Structure-from-Motion for Unordered Images
文献类型：会议论文
| 作者 | Du YK(杜英魁); Fan BJ(范保杰) ; Tang YD(唐延东); Han JD(韩建达)
|
| 出版日期 | 2012 |
| 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 |
| 页码 | 72-78 |
| 通讯作者 | 杜英魁 |
| 中文摘要 | 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. |
| 收录类别 | EI ; CPCI（ISTP） |
| 产权排序 | 1 |
| 会议主办者 | IEEE Robotics and Automation Society |
| 会议录 | Proceedings of the 2012 IEEE International Conference on Robotics and Biomimetics
 |
| 会议录出版者 | IEEE Computer Society |
| 会议录出版地 | Washington, DC, USA |
| 语种 | 英语 |
| ISBN号 | 978-1-4673-2125-9 |
| WOS记录号 | WOS:000321004000021 |
| 源URL | [http://ir.sia.cn/handle/173321/10365]  |
| 专题 | 沈阳自动化研究所_机器人学研究室 |
| 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]. 见:2012 IEEE International Conference on Robotics and Biomimetics (ROBIO 2012). Guangzhou, China. December 11-14, 2012. |
入库方式： OAI收割
来源：沈阳自动化研究所
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