Motion Vector Predictor Candidate List Construction
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Solution Overview
Problem
Current video coding technologies face challenges in efficiently encoding and decoding motion vectors, particularly in reducing redundancy and improving compression ratios, especially when dealing with large datasets like 1080p60 video, which requires significant bandwidth and storage space.
Innovation Solution
The proposed solution involves an apparatus and method for video encoding/decoding that constructs a candidate list with base motion vector predictor candidates and adds new predictors satisfying specific spacing requirements, using a coverage window to prune candidates and scale predictors for efficient motion vector reconstruction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of substance
If motion vector prediction is used to reduce redundancy, then compression ratio is improved, but the complexity of constructing and managing candidate lists increases
Solution Approach 1:
The candidate list is segmented into base motion vector predictor candidates and new motion vector predictors with offsets. This segmentation allows the system to manage complexity by separating the construction of base candidates from the generation of offset-based candidates, enabling independent optimization of each segment while maintaining overall compression efficiency.
Solution Approach 2:
The candidate list construction is made dynamic through spacing requirements that adaptively determine whether new motion vector predictors are added. The spacing requirement mechanism dynamically adjusts the candidate list based on the geometric relationships between candidates, allowing the system to optimize compression ratio while controlling complexity through adaptive rather than static list management.
2Measurement precision
If more motion vector predictor candidates are added to improve prediction accuracy, then reconstruction quality is improved, but the bandwidth and storage requirements increase
Solution Approach 1:
The invention changes parameters by introducing spacing requirements as a filtering criterion for adding new motion vector predictors. This parameter change allows the system to control the quantity of candidates in the list while maintaining prediction accuracy. By adjusting the spacing threshold, the system can optimize between reconstruction quality and bandwidth/storage requirements without linearly increasing data quantity.
3Productivity
If spacing requirements are enforced to prune candidates, then compression efficiency is improved, but the complexity of candidate evaluation increases
Solution Approach 1:
Spacing requirements are evaluated preliminarily during the candidate list construction phase rather than during decoding. This preliminary action allows the system to prune unsuitable candidates early in the encoding process, improving compression efficiency without significantly increasing decoding complexity. The spacing evaluation is performed once during list construction, avoiding repeated complex calculations during actual video decoding.
Data Source
AI summary
Aspects of the disclosure provide methods and apparatuses for video encoding/decoding. For example, processing circuitry decodes prediction information for a block in a current picture from a coded video bitstream. The prediction information is indicative of an inter prediction mode that signals an offset associated with one of base motion vector predictor candidates in a candidate list. The processing circuitry constructs the candidate list with one or more existing base motion vector predictor candidates and adds a new motion vector predictor into the candidate list when the new motion vector predictor satisfies a spacing requirement to the one or more existing base motion vector predictor candidates. The processing circuitry decodes an index of a specific base motion vector predictor candidate in the candidate list and the offset to determine a final motion vector, and reconstructs samples of the block according to the final motion vector.