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Alternative Title3D object recognition based on enhanced point pair features
鲁荣荣1,2,3,4,5; 朱枫1,2,4,5; 吴清潇1,2,4,5; 陈佛计1,2,3,4,5; 崔芸阁1,2,3,4,5; 孔研自1,2,3,4,5
Source Publication光学学报
Contribution Rank1
Funding Organization国家自然科学基金(U1713216) ; 机器人学国家重点实验室自主课题(2017-Z21)
Keyword机器视觉 点对特征 三维目标识别 可见性约束
Other AbstractAiming at the problem of memory waste and low efficiency in three-dimensional (3D) object recognition algorithm based on original point pair feature (PPF), a 3D object recognition algorithm based on enhanced point pair feature (EPPF) is proposed. By multiplying the fourth component of the original PPF with a sign function, a more distinguishing PPF is obtained, which eliminates the ambiguity of the original PPF. Considering the self-occlusion of the 3D model of the target to be identified, the large numbers of redundant point pairs existing in the target 3D model hash table are eliminated by means of the viewpoint visibility constraint between the point pair, which reduces the memory overhead and improves the accuracy and efficiency of the 3D object recognition algorithm. The experimental results on the open dataset and the actual collected dataset show that the proposed 3D object recognition algorithm in this paper has a certain degree of improvement in recognition accuracy and recognition efficiency.
Document Type期刊论文
Corresponding Author朱枫
Recommended Citation
GB/T 7714
鲁荣荣,朱枫,吴清潇,等. 基于增强型点对特征的三维目标识别方法[J]. 光学学报,2019:1-16.
APA 鲁荣荣,朱枫,吴清潇,陈佛计,崔芸阁,&孔研自.(2019).基于增强型点对特征的三维目标识别方法.光学学报,1-16.
MLA 鲁荣荣,et al."基于增强型点对特征的三维目标识别方法".光学学报 (2019):1-16.
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