Hyperspectral 3D Mapping of Underwater Environments
Not on the map. Why?
Abstract (arXiv)
Hyperspectral imaging has been increasingly used for underwater survey applications over the past years. As many hyperspectral cameras work as push-broom scanners, their use is usually limited to the creation of photo-mosaics based on a flat surface approximation and by interpolating the camera pose from dead-reckoning navigation. Yet, because of drift in the navigation and the mostly wrong flat surface assumption, the quality of the obtained photo-mosaics is often too low to support adequate analysis.In this paper we present an initial method for creating hyperspectral 3D reconstructions of underwater environments. By fusing the data gathered by a classical RGB camera, an inertial navigation system and a hyperspectral push-broom camera, we show that the proposed method creates highly accurate 3D reconstructions with hyperspectral textures. We propose to combine techniques from simultaneous localization and mapping, structure-from-motion and 3D reconstruction and advantageously use them to create 3D models with hyperspectral texture, allowing us to overcome the flat surface assumption and the classical limitation of dead-reckoning navigation.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 5 of its 37 references that are in the map. First posted on arXiv 13 Oct 2021.
Builds on
5 of 37 references.
References · 5
- 2015ORB-SLAM: a Versatile and Accurate Monocular SLAM Systemcited by 983
- 2019AQUALOC: An Underwater Dataset for Visual-Inertial-Pressure Localizationcited by 18
- 2021OV2SLAM : A Fully Online and Versatile Visual SLAM for Real-Time Applicationscited by 8
- 2018Real-time Monocular Visual Odometry for Turbid and Dynamic Underwater Environmentscited by 6
- 2019Automatic Scale Estimation of Structure from Motion based 3D Models using Laser Scalerscited by 2
Built on by
Citing papers per year: 2023: 1.
1 paper.
- 2023Spectral 3D Computer Vision -- A Reviewcited by 1
- 2023Spectral 3D Computer Vision -- A Review16 Feb 2023