Please use this identifier to cite or link to this item:
PIRA download icon_1.1View/Download Full Text
Title: Geometric integration of hybrid correspondences for RGB-D unidirectional tracking
Authors: Tang, SJ
Chen, W 
Wang, WX
Li, XM
Darwish, W 
Li, WB 
Huang, ZD
Hu, H 
Guo, RZ
Issue Date: 2018
Source: Sensors (Switzerland), May 2018, v. 18, no. 5, 1385, P. 1-23
Abstract: Traditionally, visual-based RGB-D SLAM systems only use correspondences with valid depth values for camera tracking, thus ignoring the regions without 3D information. Due to the strict limitation on measurement distance and view angle, such systems adopt only short-range constraints which may introduce larger drift errors during long-distance unidirectional tracking. In this paper, we propose a novel geometric integration method that makes use of both 2D and 3D correspondences for RGB-D tracking. Our method handles the problem by exploring visual features both when depth information is available and when it is unknown. The system comprises two parts: coarse pose tracking with 3D correspondences, and geometric integration with hybrid correspondences. First, the coarse pose tracking generates the initial camera pose using 3D correspondences with frame-by-frame registration. The initial camera poses are then used as inputs for the geometric integration model, along with 3D correspondences, 2D-3D correspondences and 2D correspondences identified from frame pairs. The initial 3D location of the correspondence is determined in two ways, from depth image and by using the initial poses to triangulate. The model improves the camera poses and decreases drift error during long-distance RGB-D tracking iteratively. Experiments were conducted using data sequences collected by commercial Structure Sensors. The results verify that the geometric integration of hybrid correspondences effectively decreases the drift error and improves mapping accuracy. Furthermore, the model enables a comparative and synergistic use of datasets, including both 2D and 3D features.
Keywords: RGB-D
Point cloud registration
Bundle adjustment
Feature matching
Camera tracking
Publisher: Molecular Diversity Preservation International (MDPI)
Journal: Sensors (Switzerland) 
ISSN: 1424-8220
DOI: 10.3390/s18051385
Rights: © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (
The following publication Tang, S., Chen, W., Wang, W., Li, X., Darwish, W., Li, W., ... & Guo, R. (2018). Geometric Integration of Hybrid Correspondences for RGB-D Unidirectional Tracking. Sensors (Basel, Switzerland), 18(5), 1-23 is available at
Appears in Collections:Journal/Magazine Article

Files in This Item:
File Description SizeFormat 
Tang_Geometric_Hybrid_RGB-D.pdf4.66 MBAdobe PDFView/Open
Open Access Information
Status open access
File Version Version of Record
View full-text via PolyU eLinks SFX Query
Show full item record

Page views

Last Week
Last month
Citations as of May 28, 2023


Citations as of May 28, 2023


Last Week
Last month
Citations as of Jun 1, 2023


Last Week
Last month
Citations as of Jun 1, 2023

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.