Multi-level machine learning-based early termination in partition search for video coding
US10812813B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jul 19, 2019 |
| Grant date | Oct 20, 2020 |
| Priority date | — |
| Expiry date | Jul 19, 2039 |
Classification
- Technology area (CPC H)Electricity
- CPC primaryH04N19/96
- WIPO fieldAudio-visual technology
- WIPO sectorElectrical engineering
Abstract
Described herein are classifiers that are used to determine whether or not to partition a block in frame during prediction using recursive partitioning. Blocks of training video frames are encoded using recursive partitioning to generate encoded blocks. Training instances are generated for the encoded blocks that include values of features extracted from each encoded block and a label indicating whether or not the encoded block is partitioned into smaller blocks in the recursive partitioning. The classifiers are trained for different block sizes using the training instances associated with the block size as input to a machine-learning process. When encoding frames of a video sequence, the output of the classifiers determines whether input blocks are partitioned during encoding.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.