Systems and techniques for retraining models for video quality assessment and for transcoding using the retrained models
US12230024B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 26, 2019 |
| Grant date | Feb 18, 2025 |
| Priority date | — |
| Expiry date | Nov 27, 2040 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N19/40
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
A trained model is retrained for video quality assessment and used to identify sets of adaptive compression parameters for transcoding user generated video content. Using transfer learning, the model, which is initially trained for image object detection, is retrained for technical content assessment and then again retrained for video quality assessment. The model is then deployed into a transcoding pipeline and used for transcoding an input video stream of user generated content. The transcoding pipeline may be structured in one of several ways. In one example, a secondary pathway for video content analysis using the model is introduced into the pipeline, which does not interfere with the ultimate output of the transcoding should there be a network or other issue. In another example, the model is introduced as a library within the existing pipeline, which would maintain a single pathway, but ultimately is not expected to introduce significant latency.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.