Techniques for training a perceptual quality model to account for brightness and color distortions in reconstructed videos
US11557025B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Aug 17, 2020 |
| Grant date | Jan 17, 2023 |
| Priority date | — |
| Expiry date | Feb 27, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30168
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
In various embodiments, a training application generates a perceptual video model. The training application computes a first feature value for a first feature included in a feature vector based on a first color component associated with a first reconstructed training video. The training application also computes a second feature value for a second feature included in the feature vector based on a first brightness component associated with the first reconstructed training video. Subsequently, the training application performs one or more machine learning operations based on the first feature value, the second feature value, and a first subjective quality score for the first reconstructed training video to generate a trained perceptual quality model. The trained perceptual quality model maps a feature value vector for the feature vector to a perceptual quality score.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.