Video Coding With Shared CABAC Contexts for Motion Predictors
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Solution Overview
Problem
The existing video coding standards, such as HEVC, face challenges in efficiently encoding and decoding motion vectors due to the complexity and inefficiency of tools like affine motion mode and Alternative Temporal Motion Vector Prediction (ATMVP), particularly in handling complex motions and increased coding complexity.
Innovation Solution
Implement methods and devices for encoding and decoding motion vector predictor indices using Context Adaptive Binary Arithmetic Coding (CABAC) with techniques like bypass coding, shared contexts, and context variables based on neighboring blocks to optimize the encoding and decoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If ATMVP is enabled at SPS level to increase the number of Merge candidates, then the coding efficiency for motion vector prediction is improved, but the device complexity increases due to the need to manage and code a larger number of candidates
Solution Approach 1:
The patent segments the Merge candidate list into different groups based on their position and coding characteristics. It applies different CABAC contexts to different segments of the candidate list, allowing optimized coding for each segment while managing overall complexity through structured organization of the candidates.
Solution Approach 2:
The patent changes the CABAC context parameters dynamically based on the candidate index and position. By adjusting the context variable according to the specific candidate being coded, the system optimizes the coding efficiency for each candidate while maintaining manageable complexity through parameterization rather than structural expansion.
2Adaptability or versatility
If the number of Merge candidates is increased to include more motion prediction options, then the adaptability for different motion types is improved, but the difficulty of detecting and measuring (coding) the selected candidate increases
Solution Approach 1:
The patent applies different coding qualities (CABAC contexts) to different local positions in the candidate list. Each candidate or group of candidates receives a context tailored to its specific characteristics and position, optimizing the coding difficulty for each local element while maintaining overall adaptability.
Solution Approach 2:
The patent introduces context variables as intermediaries between the candidate list and the CABAC coding process. These context variables mediate the coding difficulty by providing a structured interface that maps candidates to appropriate coding parameters, making the detection and measurement of selected candidates more manageable.
3Productivity
If CABAC coding is applied to all bits of the motion vector predictor index, then the coding efficiency is optimized, but the processing time and complexity increase
Solution Approach 1:
The patent applies CABAC coding partially to only the necessary bits of the motion vector predictor index rather than all bits. By determining the minimum number of bits required to represent the selected candidate and applying CABAC only to those bits, the system achieves sufficient coding efficiency while reducing unnecessary processing time and complexity.
Solution Approach 2:
The patent skips the CABAC coding process for certain bits or candidates where simpler coding methods are sufficient. By identifying which bits can be coded using faster methods (such as bypass coding or fixed-length coding), the system rushes through the less critical parts of the coding process to reduce overall processing time while maintaining efficiency where needed.
Data Source
AI summary
A method of encoding information about a motion information predictor, comprising: selecting one of a plurality of motion information predictor candidates; and encoding information for identifying the selected motion information predictor candidate using CABAC coding, wherein the CABAC coding comprises, for at least one bit of said information, using the same context variable used for another inter prediction mode when one or both of a Triangle Merge mode or a Merge with Motion Vector Difference (MMVD) Merge mode is used.