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题名:
Three-dimensional object recognition using an extensible local surface descriptor
作者: Lu RR(鲁荣荣); Zhu F(朱枫); Wu QX(吴清潇); Hao YM(郝颖明)
作者部门: 光电信息技术研究室
通讯作者: Zhu F(朱枫)
关键词: three-dimensional object recognition ; local feature ; local reference frame ; photometric information
刊名: OPTICAL ENGINEERING
ISSN号: 0091-3286
出版日期: 2017
卷号: 56, 期号:12, 页码:1-13
收录类别: SCI ; EI
EI收录号: 20180304652587
WOS记录号: WOS:000419965800021
产权排序: 1
摘要: We present an extensible local feature descriptor that can encode both geometric and photometric information. We first construct a unique and stable local reference frame (LRF) using the sphere neighboring points of a feature point. Then, all the neighboring points are transformed with the LRF to keep invariance to transformations. The sphere neighboring region is divided into several sphere shells. In each sphere shell, we calculate the cosine values of the point with the x-axis and z-axis. These two values are then mapped into two one-dimensional (1-D) histograms, respectively. Finally, all of the 1-D histograms are concatenated to form the signature of position angles histogram (SPAH) feature. The SPAH feature can easily be extended to a color SPAH (CSPAH) by adding another 1-D histogram generated by the photometric information of each point in each shell. The SPAH and CSPAH were rigorously tested on several common datasets. The experimental results show that both feature descriptors were highly descriptive and robust under Gaussian noise and varying mesh decimations. Moreover, we tested our SPAH-and CSPAH-based three-dimensional object recognition algorithms on four standard datasets. The experimental results show that our algorithms outperformed the state-of-the-art algorithms on these datasets. (C) 2017 Society of Photo-Optical Instrumentation Engineers (SPIE)
语种: 英语
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.sia.cn/handle/173321/21507
Appears in Collections:光电信息技术研究室_期刊论文

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作者单位: 1.Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, China
2.University of Chinese Academy of Sciences, Beijing, China
3.Key Laboratory of Opto-Electronic Information Processing, Chinese Academy of Sciences, Shenyang, China
4.Key Laboratory of Image Understanding and Computer Vision, Liaoning Province, Shenyang, China

Recommended Citation:
Lu RR,Zhu F,Wu QX,et al. Three-dimensional object recognition using an extensible local surface descriptor[J]. OPTICAL ENGINEERING,2017,56(12):1-13.
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