Affine Motion Prediction Buffer Management
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Solution Overview
Problem
Current video coding techniques face challenges in efficiently compressing video data while maintaining high quality, particularly in handling complex motions like rotation, zooming, and translation, due to limitations in affine motion prediction methods which require significant memory resources and computational complexity.
Innovation Solution
The proposed solution improves affine motion prediction by deriving affine motion vector predictors from both affine and normal motion vectors of neighboring coded blocks, utilizing line buffers and local buffers to optimize memory usage and reduce computational demands, and introduces size constraints for control point motion vectors to limit unnecessary storage and enhance prediction efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If affine motion prediction is used to handle complex motions, then motion estimation accuracy is improved, but memory requirements and computational complexity increase significantly
Solution Approach 1:
The patent segments the complex affine motion estimation into multiple simpler steps: deriving control point motion vectors from neighboring blocks, constructing affine motion vector predictors, and determining affine parameters incrementally. This segmentation reduces computational complexity by breaking down the complex calculation into manageable stages that can be executed efficiently.
Solution Approach 2:
The patent performs preliminary actions by pre-storing motion information of previously coded blocks in line buffers and local buffers. This preliminary storage of motion vectors and affine parameters enables faster retrieval during affine motion prediction, reducing real-time computational burden while maintaining accuracy.
2Measurement precision
If affine motion prediction is used to handle complex motions, then motion estimation accuracy is improved, but memory requirements increase significantly
Solution Approach 1:
The patent applies local quality by using different buffer types (line buffers for boundary blocks, local buffers for intra-CTU blocks) with specific storage capacities tailored to their respective needs. This localized memory allocation optimizes memory usage by storing motion information only where and how it is needed, rather than uniformly across all blocks.
Solution Approach 2:
The patent implements partial action by storing only the necessary motion information (control point motion vectors and affine parameters) in buffers,而非 storing complete motion data for all blocks. This selective storage reduces memory requirements while providing sufficient information for accurate affine motion prediction.
3Measurement precision
If motion information of all neighboring blocks is stored in line buffers, then prediction accuracy is improved, but buffer utilization efficiency decreases
Solution Approach 1:
The patent changes the parameter of buffer storage by implementing size constraints on control point motion vectors that can be stored in line buffers. By selectively storing only valid and useful motion information based on block size and position criteria, the system maintains prediction accuracy while significantly improving buffer utilization efficiency and reducing wasted memory resources.
Data Source
AI summary
Systems and techniques for improving costs and efficiency in affine motion prediction of a current block includes storing motion information of previously coded block in a line buffer or one or more local buffers of a coding unit such as coding tree unit (CTU). The line buffer can store motion information of a line of coding blocks located at a boundary of the CTU, while the local buffers can be utilized for storing motion information of coding blocks located anywhere in the CTU. The utilization of the line buffer can be improved by limiting the number of motion vectors of a neighboring block stored in the line buffer and obtaining remaining motion vectors from an additional block when available. The utilization of local buffers can be improved by restricting a size of neighboring blocks whose motion information is stored in the local buffers.