Factral/Spectral-material-segmentation
code for the paper: Beyond Appearances: Material Segmentation with Embedded Spectral Information from RGB-D imagery
This project helps specialists in computer vision or materials science automatically identify different materials in images. It takes standard RGB-D images (color and depth information, like from an iPad Pro) and outputs a segmented image where each material type is distinctly outlined. This tool is designed for researchers, engineers, or technicians who need precise material identification without expensive spectral imaging equipment.
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Use this if you need to accurately identify and segment different materials in natural scenes using readily available RGB-D cameras, even in challenging lighting conditions.
Not ideal if your application requires real-time, highly embedded material analysis on low-power devices, as it relies on a deep learning model that needs to be trained.
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Python
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Last pushed
Jun 19, 2024
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