Next Article in Journal
Understanding Probabilistic Cognitive Relaying Communication with Experimental Implementation and Performance Analysis
Next Article in Special Issue
DeepMoCap: Deep Optical Motion Capture Using Multiple Depth Sensors and Retro-Reflectors
Previous Article in Journal
Advances in Molecularly Imprinting Technology for Bioanalytical Applications
Previous Article in Special Issue
Depth from a Motion Algorithm and a Hardware Architecture for Smart Cameras
Open AccessArticle

Incremental 3D Cuboid Modeling with Drift Compensation

1
Graduate School of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan
2
Library, Kyushu University, Fukuoka 819-0395, Japan
3
Faculty of Information Science and Electrical Engineering, Kyushu University, Fukuoka 819-0395, Japan
4
Voxar Labs, Centro de Informática, Universidade Federal de Pernambuco, Recife 50740-560, Brazil
5
Departamento de Computação, Universidade Federal Rural de Pernambuco, Recife 52171-900, Brazil
*
Author to whom correspondence should be addressed.
Sensors 2019, 19(1), 178; https://doi.org/10.3390/s19010178
Received: 3 December 2018 / Revised: 26 December 2018 / Accepted: 28 December 2018 / Published: 6 January 2019
(This article belongs to the Special Issue Depth Sensors and 3D Vision)
This paper presents a framework of incremental 3D cuboid modeling by using the mapping results of an RGB-D camera based simultaneous localization and mapping (SLAM) system. This framework is useful in accurately creating cuboid CAD models from a point cloud in an online manner. While performing the RGB-D SLAM, planes are incrementally reconstructed from a point cloud in each frame to create a plane map. Then, cuboids are detected in the plane map by analyzing the positional relationships between the planes, such as orthogonality, convexity, and proximity. Finally, the position, pose, and size of a cuboid are determined by computing the intersection of three perpendicular planes. To suppress the false detection of the cuboids, the cuboid shapes are incrementally updated with sequential measurements to check the uncertainty of the cuboids. In addition, the drift error of the SLAM is compensated by the registration of the cuboids. As an application of our framework, an augmented reality-based interactive cuboid modeling system was developed. In the evaluation at cluttered environments, the precision and recall of the cuboid detection were investigated, compared with a batch-based cuboid detection method, so that the advantages of our proposed method were clarified. View Full-Text
Keywords: geometric shape; cuboid; incrementally structural modeling; point cloud geometric shape; cuboid; incrementally structural modeling; point cloud
Show Figures

Figure 1

MDPI and ACS Style

Mishima, M.; Uchiyama, H.; Thomas, D.; Taniguchi, R.-I.; Roberto, R.; Lima, J.P.; Teichrieb, V. Incremental 3D Cuboid Modeling with Drift Compensation. Sensors 2019, 19, 178.

Show more citation formats Show less citations formats
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop