Motion Candidate List Management for Geometric Partition Video Coding
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current video coding technologies face challenges in efficiently managing motion vectors and prediction modes, particularly in geometry partitioning, which affects bandwidth usage and coding efficiency in video compression.
Innovation Solution
The proposed solution involves advanced methods for constructing and managing motion candidate lists, including uni-prediction, bi-prediction, and virtual motion candidates, as well as adaptive weighting and motion compensation processes, to optimize motion vector prediction and encoding in geometry partition modes within video coding standards like HEVC and VVC.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple motion candidate lists are constructed for geometry partition modes, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent divides the motion candidate management into separate lists (first motion candidate list and second motion candidate list) corresponding to different partition types (first partition and second partition). This segmentation allows independent optimization of candidates for each partition type, improving coding efficiency without requiring complete reconstruction of a single large candidate list.
Solution Approach 2:
The patent dynamically selects and merges motion candidates from different lists based on the specific geometry partition mode being used. The motion candidate list is not fixed but adapts its composition according to the partition type, allowing the system to optimize performance for each mode while managing complexity through conditional logic rather than hard-coded structures.
2Measurement precision
If motion candidates are inserted with specific priority rules, then prediction accuracy is improved, but processing time increases
Solution Approach 1:
The patent pre-establishes priority rules for inserting motion candidates into the lists based on their source (spatial, temporal, or combined) and partition type. By defining the insertion order in advance rather than determining it dynamically during encoding, the system achieves high prediction accuracy through systematic candidate selection while reducing processing time through predetermined rules.
3Adaptability or versatility
If multiple reference picture lists are used, then prediction flexibility is improved, but bandwidth usage increases
Solution Approach 1:
The patent creates motion candidate lists that can serve multiple prediction purposes (uni-prediction and bi-prediction) and work with different reference picture lists (List 0 and List 1). By designing a universal candidate list structure that adapts to different prediction modes and reference lists, the system achieves high flexibility without proportionally increasing bandwidth usage, as the same list infrastructure serves multiple functions.
Data Source
AI summary
Devices, systems and methods for digital video coding, which include geometric partitioning, are described. An exemplary method for video processing includes making a decision, based on a priority rule, regarding an order of insertion of motion candidates into a motion candidate list for a conversion between a current block of video and a bitstream representation of the video, wherein the current block is coded using a geometry partition mode; and performing, based on the decision and the motion candidate list, the conversion.