Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/64991
Title: Enhanced RGB-D mapping method for detailed 3D modeling of large indoor environments
Authors: Tang, S 
Zhu, Q
Chen, W 
Darwish, WAA 
Wu, BO 
Hu, H 
Chen, M
Keywords: Indoor modeling
RGB-D camera
Depth
Image
Camera pose
Registration
Issue Date: 2016
Publisher: Copernicus Publications
Source: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences, 2016, v. III-1, p. 151-158 How to cite?
Journal: ISPRS annals of the photogrammetry, remote sensing and spatial information sciences 
Abstract: RGB-D sensors are novel sensing systems that capture RGB images along with pixel-wise depth information. Although they are widely used in various applications, RGB-D sensors have significant drawbacks with respect to 3D dense mapping of indoor environments. First, they only allow a measurement range with a limited distance (e.g., within 3 m) and a limited field of view. Second, the error of the depth measurement increases with increasing distance to the sensor. In this paper, we propose an enhanced RGB-D mapping method for detailed 3D modeling of large indoor environments by combining RGB image-based modeling and depth-based modeling. The scale ambiguity problem during the pose estimation with RGB image sequences can be resolved by integrating the information from the depth and visual information provided by the proposed system. A robust rigid-transformation recovery method is developed to register the RGB image-based and depth-based 3D models together. The proposed method is examined with two datasets collected in indoor environments for which the experimental results demonstrate the feasibility and robustness of the proposed method.
Description: XXIII ISPRS Congress, 12-19 July 2016, Prague, Czech Republic
URI: http://hdl.handle.net/10397/64991
ISSN: 2194-9042 (print)
DOI: 10.5194/isprs-annals-III-1-151-2016
Rights: © Author(s) 2016. This is an open access article distributed under the Creative Commons Attribution 3.0 License (https://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The following publication: Tang, S., Zhu, Q., Chen, W., Darwish, W., Wu, B., Hu, H., and Chen, M.: ENHANCED RGB-D MAPPING METHOD FOR DETAILED 3D MODELING OF LARGE INDOOR ENVIRONMENTS, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-1, 151-158 is available at https://doi.org/10.5194/isprs-annals-III-1-151-2016, 2016.
Appears in Collections:Conference Paper

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