Triangle Prediction Coding with CABAC Motion Vector Selection
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Solution Overview
Problem
Existing video coding technologies face challenges in efficiently encoding and decoding high-definition and ultra-high-definition video data while maintaining image quality, particularly in terms of redundancy reduction and compression efficiency.
Innovation Solution
Implementing geometric prediction units, such as triangular prediction units, with context-adaptive binary arithmetic coding (CABAC) for motion vector selection, allowing for more flexible block partitioning and improved prediction accuracy through a merge list construction process.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional block-based prediction is used, then coding simplicity is maintained, but compression efficiency deteriorates for high-definition and ultra-high-definition video
Solution Approach 1:
The patent divides the prediction unit into multiple triangular sub-regions instead of using a single rectangular block. This segmentation allows each triangle to be predicted independently with its own motion vector, capturing local motion variations more accurately and improving compression efficiency for high-definition video
Solution Approach 2:
Different triangular regions within the prediction unit are assigned different prediction characteristics and motion vectors based on local motion patterns. This local differentiation enables more accurate representation of complex motion fields while maintaining coding efficiency
2Measurement precision
If geometric partition prediction is implemented, then prediction accuracy is improved, but device complexity increases
Solution Approach 1:
The patent employs asymmetric triangular partitions instead of symmetric rectangular blocks. By using diagonal divisions that create unequal triangular regions, the method better adapts to natural motion patterns in video content, improving prediction accuracy while keeping the geometric complexity manageable
Solution Approach 2:
The prediction unit structure dynamically adapts to local motion characteristics by selecting different triangular partition configurations and motion vector assignments for different regions, enabling more accurate prediction without requiring a fixed complex structure
3Loss of information
If multiple motion vectors are used for different regions, then redundancy reduction is improved, but processing complexity increases
Solution Approach 1:
The prediction unit is segmented into multiple triangular regions, each with its own motion vector. This segmentation reduces temporal redundancy by independently capturing motion in different areas, improving compression while distributing the processing complexity across multiple simpler vector operations
Solution Approach 2:
The patent changes the motion representation parameters by using multiple motion vectors for different triangular regions instead of a single motion vector for the entire block. This parameter differentiation reduces information loss by better representing local motion variations
Data Source
AI summary
Methods, apparatuses, and non-transitory computer-readable storage mediums are provided for video decoding. The method includes: constructing, by a decoder, a first merge list comprising a plurality of candidates, based on a merge list construction process for regular merge prediction, wherein each one of the plurality of candidates is a motion vector comprising a List 0 motion vector, or a List 1 motion vector, or both; receiving, by the decoder, a first/second index value to indicate a first/second candidate that is chosen from the first merge list; receiving, by the decoder, a first/second binary flag that is coded using a first/second context-adaptive binary arithmetic coding (CABAC) context modeling method to indicate whether a List 0 motion vector of the first/second candidate or a List 1 motion vector of the first/second candidate is selected for a first PU of the geometric prediction.