Tufts Outdoor Hyperspectral Dataset

Hyperspectral images are represented by numerous
narrow wavelength bands in the visible and near-infrared parts
of the electromagnetic spectrum. As hyperspectral imagery gains
traction for general computer vision tasks, there is an increased
need for large and comprehensive datasets for use as training
data.
Recent advancements in sensor technology allow us to capture
hyperspectral data cubes at higher spatial and temporal reso-
lution. However, there are few publicly available multi-purpose
hyperspectral datasets captured in outdoor terrestrial conditions.
Furthermore, there are no publicly available datasets that include
3D mesh representations of objects captured in outdoor scenes.
This article introduces the first hyperspectral dataset of 3D
objects and terrestrial outdoor scenes, the Tufts Outdoor Hyper-
spectral Dataset (TOHS Dataset). The dataset includes 100 2D +
3D hyperspectral scenes, each containing 164 spectral bands.
The contributions of this work are 1) Detailed description of
the content, acquisition procedure, and benchmark results on
state-of-the-art neural networks for 3D object scenes in the Tufts
Hyperspectral Database; 2) The first-of-its-kind hyperspectral
3D dataset of outdoor objects that will be publicly available to
researchers worldwide, which will allow for the assessment and
creation of more robust, consistent, and adaptable AI algorithms;
and 3) a comprehensive and up-to-date review on hyperspectral
systems and datasets