Motion Vector Predictor List Construction via Duplicate Pruning
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Solution Overview
Problem
Existing video coding techniques face inefficiencies in constructing motion vector predictor lists due to duplicates and increased processing time, particularly when the list size is large, which affects coding efficiency and processing speed.
Innovation Solution
A method is introduced to efficiently construct motion vector predictor lists by grouping neighboring blocks and pruning duplicates, allowing for faster processing by determining if motion vectors are the same as existing vectors in the list, thereby reducing the need for unnecessary insertions and improving list construction speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If motion vector predictor lists are constructed using existing video coding techniques, then the list contains motion vector candidates for prediction, but duplicates are included and processing time increases
Solution Approach 1:
The patent applies preliminary action by checking for duplicate motion vectors before inserting them into the predictor list. The encoder examines each candidate motion vector against existing list entries prior to insertion, preventing duplicates from being added in the first place. This proactive approach eliminates the need for subsequent duplicate removal operations, thereby reducing processing time while maintaining coding efficiency.
2Measurement precision
If the motion vector predictor list size is increased to include more candidates, then better prediction accuracy is achieved, but processing complexity and time increase
Solution Approach 1:
The patent reduces processing complexity by performing duplicate detection before list insertion. The encoder checks whether a candidate motion vector already exists in the predictor list before adding it, preventing unnecessary duplicates. This preliminary check simplifies the overall processing workflow while allowing the list to maintain an optimal size for accurate prediction without the burden of managing redundant entries.
Solution Approach 2:
The patent extracts and removes duplicate motion vectors from the candidate pool before they can pollute the predictor list. By identifying and eliminating redundant motion vectors through comparison operations, the patent ensures that only unique, valuable candidates remain in the final predictor list, thereby maintaining list quality without increasing processing burden.
3Ease of manufacture
If duplicate motion vectors are included in the predictor list, then the list construction is simpler, but the coding efficiency decreases
Solution Approach 1:
The patent maintains ease of list construction by implementing duplicate checking as a simple comparison operation during the insertion phase. The encoder compares each candidate motion vector with existing list entries using straightforward equality checks, and only inserts the candidate if it is unique. This approach preserves the simplicity of the construction process while ensuring coding efficiency by eliminating duplicates.
Data Source
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AI summary
A video coder is configured to perform motion vector prediction to predict a motion vector for a block of video data. The motion vector prediction may use a motion vector predictor list that includes both adjacent and non-adjacent candidates relative to the current block. The video coder may divide spatial motion vector prediction candidates for a current block of video data into groups, add the spatial motion vector prediction candidates to a motion vector predictor list based on the groups, and decode a motion vector for the current block of video data based on the motion vector predictor list.