Affine Motion Refinement for Accurate Video Block Prediction
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in intra prediction and motion compensation, particularly in handling complex motion vectors and affine models, leading to suboptimal compression ratios and increased data requirements.
Innovation Solution
The implementation of affine bi-prediction mode with bilateral matching motion refinement, which refines control point motion vectors and affine parameters using motion vector refinement offsets, to improve the accuracy of motion compensation and intra prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional motion compensation techniques are used, then device complexity is reduced, but compression ratio and coding efficiency deteriorate
Solution Approach 1:
The current block is divided into multiple subblocks, and motion compensation is performed independently for each subblock using different motion vectors. This segmentation allows the system to achieve better compression ratios by capturing local motion variations while maintaining manageable computational complexity through localized processing.
Solution Approach 2:
The patent implements dynamic motion vector refinement where motion vectors are adjusted and optimized based on local block characteristics and motion patterns. This dynamic adaptation enables the system to improve compression efficiency by matching motion compensation to actual block behavior rather than using static, uniform motion vectors.
2Measurement precision
If affine motion models with multiple control points are used, then motion compensation accuracy is improved, but data requirements and processing complexity increase
Solution Approach 1:
The patent extracts and utilizes only the necessary motion information from reference blocks, focusing on control points and their associated motion vectors. By taking out only the essential motion parameters needed for accurate compensation rather than processing all block data, the system achieves high accuracy while reducing data requirements.
Solution Approach 2:
The system dynamically adjusts motion model parameters including the number of control points, motion vector precision, and affine transformation coefficients based on block characteristics. This parameter adaptation allows the system to maintain high motion compensation accuracy while optimizing data usage by applying appropriate complexity only where needed.
Data Source
AI summary
Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. In some examples, an apparatus for video decoding includes processing circuitry. The processing circuitry receives a coded video bitstream including a current picture. The current picture includes a current block. The processing circuitry determines, based on decoded information from the coded video bitstream, that the current block in the current picture is coded in an affine bi-prediction mode. The current block is predicted by a plurality of control point motion vectors. The processing circuitry refines the plurality of control point motion vectors by applying bilateral matching motion refinement, and reconstructs the current block according to the refined plurality of control point motion vectors associated with the current block.