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Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud

文献类型：期刊论文

作者Guo, Jianwei1,2; Xing, Xuejun1,2; Quan, Weize1,2; Yan, Dong-Ming1,2; Gu, Qingyi3; Liu, Yang4; Zhang, Xiaopeng1,2
刊名IEEE TRANSACTIONS ON IMAGE PROCESSING
出版日期2021
卷号30页码:5072-5084
关键词Three-dimensional displays Pose estimation Shape Object detection Feature extraction Object recognition Transmission line matrix methods 6D pose estimation 3D object recognition point pair features 3D point cloud
ISSN号1057-7149
DOI10.1109/TIP.2021.3078109
通讯作者Yan, Dong-Ming(yandongming@gmail.com) ; Zhang, Xiaopeng(xiaopeng.zhang@ia.ac.cn)
英文摘要We present a novel and efficient approach to estimate 6D object poses of known objects in complex scenes represented by point clouds. Our approach is based on the well-known point pair feature (PPF) matching, which utilizes self-similar point pairs to compute potential matches and thereby cast votes for the object pose by a voting scheme. The main contribution of this paper is to present an improved PPF-based recognition framework, especially a new center voting strategy based on the relative geometric relationship between the object center and point pair features. Using this geometric relationship, we first generate votes to object centers resulting in vote clusters near real object centers. Then we group and aggregate these votes to generate a set of pose hypotheses. Finally, a pose verification operator is performed to filter out false positives and predict appropriate 6D poses of the target object. Our approach is also suitable to solve the multi-instance and multi-object detection tasks. Extensive experiments on a variety of challenging benchmark datasets demonstrate that the proposed algorithm is discriminative and robust towards similar-looking distractors, sensor noise, and geometrically simple shapes. The advantage of our work is further verified by comparing to the state-of-the-art approaches.
WOS关键词RECOGNITION
资助项目National Natural Science Foundation of China[61802406] ; National Natural Science Foundation of China[61772523] ; National Natural Science Foundation of China[61972459] ; National Key Research and Development Program[2018YFB2100602] ; Scientific Instrument Developing Project of the Chinese Academy of Sciences[YJKYYQ20200045] ; Alibaba Group through Alibaba Innovative Research Program ; Suzhou Key Industrial Technology Innovation-Prospective Application Research[SYG201929]
WOS研究方向Computer Science ; Engineering
语种英语
WOS记录号WOS:000652060600006
出版者IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
资助机构National Natural Science Foundation of China ; National Key Research and Development Program ; Scientific Instrument Developing Project of the Chinese Academy of Sciences ; Alibaba Group through Alibaba Innovative Research Program ; Suzhou Key Industrial Technology Innovation-Prospective Application Research
源URL[http://ir.ia.ac.cn/handle/173211/45220]  
专题模式识别国家重点实验室_三维可视计算
中国科学院自动化研究所
通讯作者Yan, Dong-Ming; Zhang, Xiaopeng
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit NLPR, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing 100049, Peoples R China
3.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
4.Suzhou CASIA All Phase Intelligence Technol Co Lt, Suzhou 215413, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Jianwei,Xing, Xuejun,Quan, Weize,et al. Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud[J]. IEEE TRANSACTIONS ON IMAGE PROCESSING,2021,30:5072-5084.
APA Guo, Jianwei.,Xing, Xuejun.,Quan, Weize.,Yan, Dong-Ming.,Gu, Qingyi.,...&Zhang, Xiaopeng.(2021).Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud.IEEE TRANSACTIONS ON IMAGE PROCESSING,30,5072-5084.
MLA Guo, Jianwei,et al."Efficient Center Voting for Object Detection and 6D Pose Estimation in 3D Point Cloud".IEEE TRANSACTIONS ON IMAGE PROCESSING 30(2021):5072-5084.

入库方式： OAI收割

来源：自动化研究所

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