Learning from estimated high-dynamic range all weather lighting parameters
US10957026B1 · kind B1 · utility
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Key dates
| Filing date | Sep 9, 2019 |
| Grant date | Mar 23, 2021 |
| Priority date | — |
| Expiry date | Sep 12, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20208
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Methods and systems are provided for determining high-dynamic range lighting parameters for input low-dynamic range images. A neural network system can be trained to estimate high-dynamic range lighting parameters for input low-dynamic range images. The high-dynamic range lighting parameters can be based on sky color, sky turbidity, sun color, sun shape, and sun position. Such input low-dynamic range images can be low-dynamic range panorama images or low-dynamic range standard images. Such a neural network system can apply the estimates high-dynamic range lighting parameters to objects added to the low-dynamic range images.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.