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arXiv · 2212.02749

A Hyperspectral and RGB Dataset for Building Facade Segmentation

Nariman Habili·Ernest Kwan·Weihao Li·Christfried Webers·Jeremy Oorloff·Mohammad Ali Armin·Lars Petersson
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Abstract

Hyperspectral Imaging (HSI) provides detailed spectral information and has been utilised in many real-world applications. This work introduces an HSI dataset of building facades in a light industry environment with the aim of classifying different building materials in a scene. The dataset is called the Light Industrial Building HSI (LIB-HSI) dataset. This dataset consists of nine categories and 44 classes. In this study, we investigated deep learning based semantic segmentation algorithms on RGB and hyperspectral images to classify various building materials, such as timber, brick and concrete.

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Nariman Habili, Ernest Kwan, Weihao Li, Christfried Webers, Jeremy Oorloff, Mohammad Ali Armin, Lars Petersson. 2022-12-06. A Hyperspectral and RGB Dataset for Building Facade Segmentation. https://arxiv.org/abs/2212.02749

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