University of Oulu

T. Pennanen, S. Ariram, A. Tikanmäki and J. Röning, "All-Around 3D Reconstruction from Spherical Images with Semantic Segmentation," 2021 IEEE International Conference on Mechatronics and Automation (ICMA), 2021, pp. 193-199, doi: 10.1109/ICMA52036.2021.9512619

All-around 3D reconstruction from spherical images with semantic segmentation

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Author: Pennanen, Tuulia1; Ariram, Siva1; Tikanmäki, Antti1;
Organizations: 1Biomimetics and Intelligent Systems Group University of Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 1.1 MB)
Persistent link: http://urn.fi/urn:nbn:fi-fe2021102051686
Language: English
Published: Institute of Electrical and Electronic Engineers, 2021
Publish Date: 2021-10-20
Description:

Abstract

Lightweight, affordable spherical cameras can be utilized in mobile robotics to build a 3D map of the working environment of a robot. This paper demonstrates how to use the optical flow between two spherical images to quickly construct a semantically meaningful 3D model spanning all directions. The main contribution of the paper is the use of semantic segmentation to increase the robustness of the reconstruction method in both indoor and outdoor applications.

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Series: International Conference on Industrial Mechatronics and Automation
ISSN: 2152-7431
ISSN-E: 2152-744X
ISSN-L: 2152-7431
ISBN: 978-1-6654-4101-8
ISBN Print: 978-1-6654-3119-4
Pages: 193 - 199
DOI: 10.1109/ICMA52036.2021.9512619
OADOI: https://oadoi.org/10.1109/ICMA52036.2021.9512619
Host publication: 18th IEEE International Conference on Mechatronics and Automation, ICMA 2021
Conference: IEEE International Conference on Mechatronics and Automation
Type of Publication: A4 Article in conference proceedings
Field of Science: 213 Electronic, automation and communications engineering, electronics
Subjects:
Funding: The authors would like to thank the NUVE-LAB – Developing Autonomous and Environmentally Sustainable Utility Vehicles project for the financial support.
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