All-around 3D reconstruction from spherical images with semantic segmentation
Pennanen, Tuulia; Ariram, Siva; Tikanmäki, Antti; Röning, Juha (2021-08-27)
Pennanen, Tuulia
Ariram, Siva
Tikanmäki, Antti
Röning, Juha
Institute of Electrical and Electronic Engineers
27.08.2021
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
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© 2021 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2021102051686
https://urn.fi/URN:NBN:fi-fe2021102051686
Tiivistelmä
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.
Kokoelmat
- Avoin saatavuus [32008]