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A comparative study on pose estimation for monocular vision and binocular vision without modeling
He L(何雷); Zhu F(朱枫); Hao YM(郝颖明)
作者部门光电信息研究室
会议名称2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2007
会议日期June 25, 2007 - June 28, 2007
会议地点Las Vegas, NV, United states
会议主办者MIT, Media Laboratory,; Harvard Univ., Dep. Stat., Stat. Genomics Comput. Biol. Lab.; University of Texas at Austin, Texas Advanced Computing Center; Stat. Comput. Intell. Lab. Purdue Univ.
会议录名称Proceedings of the 2007 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2007
出版者CSREA Press
出版地Bogart, GA, USA
2007
页码627-631
收录类别EI
EI收录号20123315346983
产权排序2
ISBN号978-1-60132-043-8
摘要Pose estimation algorithms with regard to both monocular vision and binocular one have been studied respectively since about twenty years ago, however, few researchers considered comparing two representative methods for the sake of actual application. In this paper, considering the factual model, we have done a comparative study about these two methods quantitatively. The statistical result of calculated error based on simulation experiments denotes that the model-based monocular vision behaves more outstanding than the binocular vision on the computational accuracy and robust inasmuch the monocular vision introduces the known object model in the process of computing the coordinates of feature points. The simulated result has certain guided significance for choosing a suitable pose estimation algorithm in actual engineering projects.
语种英语
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/19986
专题光电信息技术研究室
通讯作者He L(何雷)
作者单位1.Graduate School of the Chinese Academy of Science, Shenyang Institute of Automation, Chinese Academy of Science, Shenyang City, Liaoning Province, China
2.Shenyang Institute of Automation, Chinese Academy of Science, Shenyang City, Liaoning Province, China
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He L,Zhu F,Hao YM. A comparative study on pose estimation for monocular vision and binocular vision without modeling[C]//MIT, Media Laboratory,; Harvard Univ., Dep. Stat., Stat. Genomics Comput. Biol. Lab.; University of Texas at Austin, Texas Advanced Computing Center; Stat. Comput. Intell. Lab. Purdue Univ.. Bogart, GA, USA:CSREA Press,2007:627-631.
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