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6D Pose Estimation Based on Multiple Appearance Features from Single Color Image
Pan W(潘旺); Zhu F(朱枫); Hao YM(郝颖明); Zhang LM(张丽敏)
作者部门光电信息技术研究室
会议名称7th IEEE Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
会议日期July 31 - August 4, 2017
会议地点Hawaii, USA
会议主办者IEEE Robotics and Automation Society
会议录名称2017 IEEE 7th Annual International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2017
出版者IEEE
出版地New York
2017
页码406-411
收录类别EI ; CPCI(ISTP)
EI收录号20183905873556
WOS记录号WOS:000447628700075
产权排序1
ISBN号978-1-5386-0489-2
摘要

Template matching methods are widely used to recognize instances of an untextured object and determine the poses. But in many practical cases the false positive rate is high because of similar interference characteristic in images especially in complex and clutter scene. A method based on multiple appearance features is presented in the paper to recognize poorly textured 3D objects and estimate their 6D pose in single color image. The object is distinguished from cluttered environment by multi-features which include the color, size and aspect ratio. Image pyramid is introduced here to improve efficiency. And the CAD model of the object is used to generate a hierarchical shape model in the offline phase for estimating the 6D pose accurately. Lastly the approach is evaluated in our application and publicly available dataset, and achieves good performance both in speed and recognition rate compared with state-of-the-art methods.

语种英语
引用统计
文献类型会议论文
条目标识符http://ir.sia.cn/handle/173321/21303
专题光电信息技术研究室
通讯作者Pan W(潘旺)
作者单位1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.University of Chinese Academy of Sciences, Beijing 100049, China
3.Key Laboratory of Opto-Electronic Information Processing, CAS, Shenyang 110016, China
4.The Key Lab of Image Understanding and Computer Vision, Liaoning Province, Shenyang 110016, China
推荐引用方式
GB/T 7714
Pan W,Zhu F,Hao YM,et al. 6D Pose Estimation Based on Multiple Appearance Features from Single Color Image[C]//IEEE Robotics and Automation Society. New York:IEEE,2017:406-411.
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