Geometry Partition Coding With MMVD Motion Vector Signaling
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing video coding technologies face inefficiencies in predicting motion vectors, particularly in scenarios where block partitions require different motion vectors, leading to increased data requirements and reduced compression efficiency.
Innovation Solution
Implementing a geometry partition mode (GPM) and merge mode with motion vector difference (MMVD) to partition blocks into multiple parts, using angle and edge indexes for angles and edge positions, and distance and direction indexes for distances and directions, to determine motion vectors for each part, allowing for more precise motion vector prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If motion vectors are predicted from surrounding blocks using conventional merge mode, then data requirements are reduced, but prediction accuracy deteriorates when block partitions require different motion vectors
Solution Approach 1:
The current block is divided into two sub-blocks (first and second sub-blocks) with different motion vector predictions. Each sub-block can have its own motion vector difference (MVD) applied independently, allowing different motion characteristics to be captured for different regions while still using compact indexing to signal the parameters.
Solution Approach 2:
Different motion vector prediction strategies are applied to different sub-blocks within the same current block. The first sub-block uses one prediction method while the second sub-block uses another, allowing each region to be optimized for its specific motion characteristics rather than applying a uniform approach.
2Measurement precision
If blocks are partitioned into multiple parts with different motion vectors, then motion prediction accuracy is improved, but data requirements increase
Solution Approach 1:
Multiple motion vector prediction candidates are merged into a single compact representation using the MMVD technique. Instead of signaling separate motion vectors for each sub-block, the invention uses a base motion vector plus a single motion vector difference (MVD) that is applied to both sub-blocks, significantly reducing the data required while maintaining prediction accuracy.
Solution Approach 2:
The invention changes the parameter representation from signaling complete motion vectors to signaling only the difference (delta) from a base motion vector. This parameter transformation reduces the number of bits required to encode motion information while preserving the ability to represent different motion characteristics across sub-blocks.
3Productivity
If conventional merge mode is used for inter prediction, then compression ratio is limited, but device complexity is reduced
Solution Approach 1:
Motion vector prediction candidates are prepared in advance and stored in a candidate list before the actual prediction process. The decoder can then select from these pre-computed candidates using simple indexing, reducing the computational complexity during real-time decoding while still achieving high compression ratios through efficient motion compensation.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
In a method of decoding, coded information of a block is received from a coded video bitstream. The coded information indicates that the block is partitioned based on a geometry partition mode (GPM) into a first part and a second part and inter predicted based on merge mode with motion vector difference (MMVD). That a motion vector for the first part of the block partitioned by GPM is not identical to a motion vector for the second part of the block partitioned by GPM is determined. The block is further reconstructed based on the motion vector for the first part of the block and the motion vector for the second part of the block.