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Article

HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes

1
School of Mechanical Engineering and Automation, Northeastern University, NO. 3-11, Wenhua Road, Heping District, Shenyang 110819, China
2
Shenzhen Academy of Aerospace Technology, Shenzhen 100080, China
3
Department of Advanced Robotics, Istituto Italiano di Tecnologia, Via Morego 30, 16163 Genova, Italy
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(10), 3214; https://doi.org/10.3390/s18103214
Received: 27 August 2018 / Revised: 19 September 2018 / Accepted: 20 September 2018 / Published: 23 September 2018
(This article belongs to the Special Issue Semantic Representations for Behavior Analysis in Robotic System)
Extracting horizontal planes in heavily cluttered three-dimensional (3D) scenes is an essential procedure for many robotic applications. Aiming at the limitations of general plane segmentation methods on this subject, we present HoPE, a Horizontal Plane Extractor that is able to extract multiple horizontal planes in cluttered scenes with both organized and unorganized 3D point clouds. It transforms the source point cloud in the first stage to the reference coordinate frame using the sensor orientation acquired either by pre-calibration or an inertial measurement unit, thereby leveraging the inner structure of the transformed point cloud to ease the subsequent processes that use two concise thresholds for producing the results. A revised region growing algorithm named Z clustering and a principal component analysis (PCA)-based approach are presented for point clustering and refinement, respectively. Furthermore, we provide a nearest neighbor plane matching (NNPM) strategy to preserve the identities of extracted planes across successive sequences. Qualitative and quantitative evaluations of both real and synthetic scenes demonstrate that our approach outperforms several state-of-the-art methods under challenging circumstances, in terms of robustness to clutter, accuracy, and efficiency. We make our algorithm an off-the-shelf toolbox which is publicly available. View Full-Text
Keywords: 3D data segmentation; 3D imaging sensor; 3D point cloud; horizontal plane extraction; plane segmentation 3D data segmentation; 3D imaging sensor; 3D point cloud; horizontal plane extraction; plane segmentation
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MDPI and ACS Style

Dong, Z.; Gao, Y.; Zhang, J.; Yan, Y.; Wang, X.; Chen, F. HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes. Sensors 2018, 18, 3214. https://doi.org/10.3390/s18103214

AMA Style

Dong Z, Gao Y, Zhang J, Yan Y, Wang X, Chen F. HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes. Sensors. 2018; 18(10):3214. https://doi.org/10.3390/s18103214

Chicago/Turabian Style

Dong, Zhipeng, Yi Gao, Jinfeng Zhang, Yunhui Yan, Xin Wang, and Fei Chen. 2018. "HoPE: Horizontal Plane Extractor for Cluttered 3D Scenes" Sensors 18, no. 10: 3214. https://doi.org/10.3390/s18103214

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