TMVP Candidate Search Order for Efficient Video Inter-Prediction
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Solution Overview
Problem
Existing video coding technologies face inefficiencies in determining temporal motion vector predictor candidates for inter-prediction, leading to suboptimal compression efficiency.
Innovation Solution
The method restricts the number of temporal motion vector predictor candidates and employs specific search mechanisms to enhance diversity among candidates, improving coding efficiency by identifying a set of potential predictors through controlled search orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the number of temporal motion vector predictor candidates is increased to improve prediction accuracy, then coding efficiency improves, but computational complexity and processing time increase
Solution Approach 1:
The patent segments the motion vector prediction process by dividing candidates into different types (spatial MVP candidates and temporal MVP candidates) and processing them in distinct stages. The temporal MVP candidates are generated separately from spatial candidates, allowing independent optimization of each segment's search strategy and reducing overall computational complexity while maintaining prediction accuracy.
Solution Approach 2:
The patent applies local quality by using different search strategies for different candidate types. Spatial MVP candidates use one generation approach while temporal MVP candidates use a separate approach with specific search order constraints. This localized optimization allows the system to maintain high prediction accuracy for each candidate type without uniformly increasing complexity across all processing.
2Measurement precision
If a comprehensive search of all candidate blocks is performed to ensure optimal predictor selection, then coding efficiency improves, but processing time increases
Solution Approach 1:
The patent performs preliminary action by establishing a defined search order for temporal MVP candidates before the actual prediction process. The search order is predetermined based on block positions and candidate types, allowing the encoder to quickly identify suitable candidates without exhaustive searching. This preliminary structuring of the search space significantly reduces processing time while maintaining optimal predictor selection.
Solution Approach 2:
The patent applies partial action by selecting only the necessary number of temporal MVP candidates (typically one or two) from the available pool, rather than processing all possible candidates. The defined search order allows the algorithm to stop once sufficient candidates are found, avoiding excessive processing while still achieving optimal prediction quality.
3Loss of substance
If more motion vector predictor candidates are generated to improve compression efficiency, then bitrate reduction improves, but memory requirements and data processing load increase
Solution Approach 1:
The patent extracts only the essential temporal MVP candidates needed for effective prediction, separating them from the full set of possible candidates. By defining specific extraction criteria based on block positions and candidate types, the system obtains sufficient prediction accuracy without processing or storing unnecessary candidate data, thus reducing data processing load while maintaining bitrate reduction benefits.
4Measurement precision
If the search scope for temporal motion vector predictors is expanded to include more reference blocks, then prediction accuracy improves, but computational complexity increases
Solution Approach 1:
The patent introduces asymmetry in the search scope by treating different block positions differently through the defined search order. Certain reference blocks are prioritized based on their positional relationship to the current block, creating an asymmetric search strategy that focuses computational effort on the most promising candidates while limiting the overall search scope, thereby maintaining accuracy without proportionally increasing complexity.
Data Source
AI summary
This disclosure relates generally to video coding and particularly to methods and systems for determination of temporal motion vector predictor (TMVP) candidates for inter-prediction in video coding. The disclosed methods, for example, include restricting the number of TMVP candidates in a motion vector predictor (MVP) list and provide various search mechanism in order to promote MVP candidate diversity among TMVP and other types of MVP candidates and to improve coding efficiency.