A Hyperspectral and RGB Dataset for Building Facade Segmentation
December 06, 2022 Β· Declared Dead Β· π ECCV Workshops
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Authors
Nariman Habili, Ernest Kwan, Weihao Li, Christfried Webers, Jeremy Oorloff, Mohammad Ali Armin, Lars Petersson
arXiv ID
2212.02749
Category
cs.CV: Computer Vision
Citations
13
Venue
ECCV Workshops
Last Checked
3 months ago
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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