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A plane extraction approach in inverse depth images based on region-growing
Han XN(韩小宁)1,2,3; Wang XH(王晓辉)1,2,3; Leng YQ(冷雨泉)4,5
Department空间自动化技术研究室
Source PublicationSensors (Switzerland)
ISSN1424-8220
2021
Volume21Issue:4Pages:1-15
Indexed BySCI ; EI
EI Accession number20210609897205
WOS IDWOS:000624683800001
Contribution Rank1
Funding OrganizationNational Natural Science Foundation of China under Grant 51805237 ; Joint Fund of Science & Technology Department of Liaoning Province and State Key Laboratory of Robotics, China (Grant No.2020-KF-22-03)
Keywordplane extraction region growing RGBD camera normal estimation
Abstract

Planar surfaces are prevalent components of man-made indoor scenes, and plane extraction plays a vital role in practical applications of computer vision and robotics, such as scene understanding, and mobile manipulation. Nowadays, most plane extraction methods are based on reconstruction of the scene. In this paper, plane representation is formulated in inverse-depth images. Based on this representation, we explored the potential to extract planes in images directly. A fast plane extraction approach, which employs the region growing algorithm in inverse-depth images, is presented. This approach consists of two main components: seeding, and region growing. In the seeding component, seeds are carefully selected locally in grid cells to improve exploration efficiency. After seeding, each seed begins to grow into a continuous plane in succession. Both greedy policy and a normal coherence check are employed to find boundaries accurately. During growth, neighbor coplanar planes are checked and merged to overcome the over-segmentation problem. Through experiments on public datasets and generated saw-tooth images, the proposed approach achieves 80.2% CDR (Correct Detection Rate) on the ABW SegComp Dataset, which has proven that it has comparable performance with the state-of-the-art. The proposed approach runs at 5 Hz on typical 680 × 480 images, which has shown its potential in real-time practical applications in computer vision and robotics with further improvement.

Language英语
Citation statistics
Document Type期刊论文
Identifierhttp://ir.sia.cn/handle/173321/28334
Collection空间自动化技术研究室
Corresponding AuthorLeng YQ(冷雨泉)
Affiliation1.State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
2.Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110016, China
3.University of Chinese Academy of Sciences, Beijing 100049, China
4.Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems, Department of Mechanical and Energy Engineering, Southern University of Science and Technology, Shenzhen 518055, China
5.Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities, Southern University of Science and Technology, Shenzhen 518055, China
Recommended Citation
GB/T 7714
Han XN,Wang XH,Leng YQ. A plane extraction approach in inverse depth images based on region-growing[J]. Sensors (Switzerland),2021,21(4):1-15.
APA Han XN,Wang XH,&Leng YQ.(2021).A plane extraction approach in inverse depth images based on region-growing.Sensors (Switzerland),21(4),1-15.
MLA Han XN,et al."A plane extraction approach in inverse depth images based on region-growing".Sensors (Switzerland) 21.4(2021):1-15.
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