Tufts Outdoor Hyperspectral Dataset

Hyperspectral images are represented by numerousnarrow wavelength bands in the visible and near-infrared partsof the electromagnetic spectrum. As hyperspectral imagery gainstraction for general computer vision tasks, there is an increasedneed for large and comprehensive datasets for use as trainingdata.Recent advancements in sensor technology allow us to capturehyperspectral data cubes at higher spatial and temporal reso-lution. However, there are few publicly available multi-purposehyperspectral datasets captured in outdoor terrestrial conditions.Furthermore, there are no publicly available datasets that include3D mesh representations of objects captured in outdoor scenes.This article introduces the first hyperspectral dataset of 3Dobjects 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 ofthe content, acquisition procedure, and benchmark results onstate-of-the-art neural networks for 3D object scenes in the TuftsHyperspectral Database; 2) The first-of-its-kind hyperspectral3D dataset of outdoor objects that will be publicly available toresearchers worldwide, which will allow for the assessment andcreation of more robust, consistent, and adaptable AI algorithms;and 3) a comprehensive and up-to-date review on hyperspectralsystems and datasets