Video Block Sub-Partitioning for Motion Vector Prediction
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Solution Overview
Problem
Current video compression techniques struggle to efficiently manage bandwidth demand for digital video, particularly as the number of connected devices increases, leading to growing bandwidth requirements.
Innovation Solution
The proposed solution involves encoding and decoding digital video using a merge list of motion vectors, which includes splitting video data into sub-blocks based on a partition structure, coding a subset of sub-blocks with common motion information, and coding another subset with different motion information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If video data is compressed using conventional techniques, then bandwidth usage is reduced, but compression ratio is insufficient to meet growing bandwidth demand
Solution Approach 1:
The video block is divided into multiple sub-blocks, and each sub-block is independently processed with its own motion information. This segmentation allows for more precise motion compensation and improves compression efficiency by capturing local motion variations that conventional whole-block processing misses.
Solution Approach 2:
Different motion information is applied to different sub-blocks based on their local characteristics. The patent derives motion candidates specifically for each sub-block, allowing the compression algorithm to adapt to local motion patterns and achieve better compression ratios without increasing overall bandwidth usage.
2Loss of information
If motion information is coded separately for each sub-block, then compression ratio improves, but device complexity increases
Solution Approach 1:
Motion candidates are pre-derived and stored in a candidate list before the actual encoding process. This preliminary preparation allows the encoder to efficiently select from pre-computed options rather than calculating motion information from scratch for each sub-block, reducing real-time encoding complexity while maintaining high compression ratios.
Solution Approach 2:
Motion information is copied from neighboring blocks and temporally co-located blocks to create motion candidates for sub-blocks. This copying approach avoids redundant calculations and leverages spatial and temporal correlations in video data, reducing encoding complexity while improving compression efficiency.
3Productivity
If merge candidate list is derived from neighboring blocks of parent node, then coding efficiency improves, but processing time increases
Solution Approach 1:
The merge candidate derivation is segmented and performed independently for each child node based on its specific position and characteristics. This allows parallel processing of different sub-blocks, improving overall coding efficiency while managing processing time through distributed computation rather than sequential analysis of the entire block.
Data Source
AI summary
A video processing method includes deriving multiple temporal motion vector prediction (TMVP) candidates for a video block in a current picture based on multiple blocks associated with a second block in one or more pictures that are temporally co-located with the current picture, wherein the current picture is excluded from the one or more pictures, and the second block is temporally collocated with the video block, wherein the second block has a same size as the video block, and wherein a relative position of the second block to a top-left corner of a second picture of the one or more pictures is same as that of the video block to a top-left corner of the current picture; adding the multiple TMVP candidates to a motion candidate list associated with the video block; and performing a conversion between the video block and a bitstream.