princeton-computational-imaging/MaskToF

Official code repository for the paper: "Mask-ToF: Learning Microlens Masks for Flying Pixel Correction in Time-of-Flight Imaging"

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Time-of-flight (ToF) cameras are used to capture 3D depth information, but often suffer from inaccuracies caused by 'flying pixels.' This project helps imaging scientists, optical engineers, and researchers improve the quality of 3D depth maps from ToF cameras. It takes raw ToF camera data and outputs more accurate 3D depth measurements by learning optimal microlens masks to correct these errors.

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Use this if you are working with Time-of-Flight cameras and need to correct inaccuracies in depth measurements, especially those caused by light scattering or 'flying pixels.'

Not ideal if you are working with other 3D sensing technologies like LiDAR or structured light, or if you don't have access to the raw data necessary to simulate and refine mask patterns.

3D-imaging Time-of-Flight-cameras computational-photography optical-engineering depth-sensing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 16 / 25
Community 13 / 25

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16

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Language

Jupyter Notebook

License

MIT

Last pushed

Jan 18, 2024

Commits (30d)

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