Machine learning techniques for increasing color consistency across videos
US10679328B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | May 23, 2018 |
| Grant date | Jun 9, 2020 |
| Priority date | — |
| Expiry date | Jul 24, 2038 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/20084
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Disclosed systems and methods use machine-learning techniques to determine a set of parameters that if applied to a target video, apply a color characteristic of a reference video to the target video. For example, a color consistency application executing on a computing device computes a feature vector including a representation of a reference video and a target video. The application determines a set of color parameters (e.g., exposure, color temperature, tint, etc.) by applying the feature vector to one or more predictive models trained to determine color consistency. The application generates a preview image by applying the parameters to the target video. The applying causes an adjustment of exposure, color temperature, or tint in the target video such that a color consistency of the adjusted target video is consistent with a color consistency of the reference video. The color consistency application provides settings to further adjust the parameters.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.