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Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization
We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation displacements in the plane, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370870/ https://www.ncbi.nlm.nih.gov/pubmed/35957244 http://dx.doi.org/10.3390/s22155687 |
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author | Wang, Yifu Yang, Jiaqi Peng, Xin Wu, Peng Gao, Ling Huang, Kun Chen, Jiaben Kneip, Laurent |
author_facet | Wang, Yifu Yang, Jiaqi Peng, Xin Wu, Peng Gao, Ling Huang, Kun Chen, Jiaben Kneip, Laurent |
author_sort | Wang, Yifu |
collection | PubMed |
description | We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation displacements in the plane, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a low-dimensional homographic warping, thus complicating an application of the commonly used Image of Warped Events (IWE). We introduce a new solution to this problem by performing contrast maximization in 3D. The 3D location of the rays cast for each event is smoothly varied as a function of a continuous-time motion parametrization, and the optimal parameters are found by maximizing the contrast in a volumetric ray density field. Our method thus performs joint optimization over motion and structure. The practical validity of our approach is supported by an application to AGV motion estimation and 3D reconstruction with a single vehicle-mounted event camera. The method approaches the performance obtained with regular cameras and eventually outperforms in challenging visual conditions. |
format | Online Article Text |
id | pubmed-9370870 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-93708702022-08-12 Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization Wang, Yifu Yang, Jiaqi Peng, Xin Wu, Peng Gao, Ling Huang, Kun Chen, Jiaben Kneip, Laurent Sensors (Basel) Article We present a new solution to tracking and mapping with an event camera. The motion of the camera contains both rotation and translation displacements in the plane, and the displacements happen in an arbitrarily structured environment. As a result, the image matching may no longer be represented by a low-dimensional homographic warping, thus complicating an application of the commonly used Image of Warped Events (IWE). We introduce a new solution to this problem by performing contrast maximization in 3D. The 3D location of the rays cast for each event is smoothly varied as a function of a continuous-time motion parametrization, and the optimal parameters are found by maximizing the contrast in a volumetric ray density field. Our method thus performs joint optimization over motion and structure. The practical validity of our approach is supported by an application to AGV motion estimation and 3D reconstruction with a single vehicle-mounted event camera. The method approaches the performance obtained with regular cameras and eventually outperforms in challenging visual conditions. MDPI 2022-07-29 /pmc/articles/PMC9370870/ /pubmed/35957244 http://dx.doi.org/10.3390/s22155687 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Yifu Yang, Jiaqi Peng, Xin Wu, Peng Gao, Ling Huang, Kun Chen, Jiaben Kneip, Laurent Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title | Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title_full | Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title_fullStr | Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title_full_unstemmed | Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title_short | Visual Odometry with an Event Camera Using Continuous Ray Warping and Volumetric Contrast Maximization |
title_sort | visual odometry with an event camera using continuous ray warping and volumetric contrast maximization |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9370870/ https://www.ncbi.nlm.nih.gov/pubmed/35957244 http://dx.doi.org/10.3390/s22155687 |
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