A plane extraction approach in inverse depth images based on region-growing

Han，Xiaoning1,2,3; Wang，Xiaohui1,2,3; Leng，Yuquan4,5; Zhou，Weijia1

2021-02-02

10.3390/s21041141

SENSORS   影响因子和分区

1424-8220

1424-8220

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.

Normal estimation Plane extraction Region growing RGBD camera

SCI ; EI

英语

通讯

National Natural Science Foundation of China[51805237] ; State Key Laboratory of Robotics, China[2020-KF-22-03]

Chemistry ; Engineering ; Instruments & Instrumentation

Chemistry, Analytical ; Engineering, Electrical & Electronic ; Instruments & Instrumentation

WOS:000624683800001

MDPI

20210609897205

Computer vision ; Extraction ; Image segmentation ; Inverse problems ; Robotics

Computer Applications:723.5 ; Robotics:731.5 ; Chemical Operations:802.3

CHEMISTRY

2-s2.0-85100455375

Scopus

1.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

Han，Xiaoning,Wang，Xiaohui,Leng，Yuquan,et al. A plane extraction approach in inverse depth images based on region-growing[J]. SENSORS,2021,21(4):1-15.

Han，Xiaoning,Wang，Xiaohui,Leng，Yuquan,&Zhou，Weijia.(2021).A plane extraction approach in inverse depth images based on region-growing.SENSORS,21(4),1-15.

Han，Xiaoning,et al."A plane extraction approach in inverse depth images based on region-growing".SENSORS 21.4(2021):1-15.