Moving Picture Coding With Selective Co-Located Motion Vector Storage
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Solution Overview
Problem
Conventional temporal motion vector predictor modes require high-capacity memory and bandwidth for storing motion vectors, which is inefficient.
Innovation Solution
A method for controlling motion vector information storage by using a co-located block in a reference picture to determine which motion vectors to store in memory, reducing the necessary memory capacity and bandwidth.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If motion vectors are stored in memory for temporal motion vector predictor mode, then prediction accuracy is improved, but memory capacity and bandwidth requirements increase
Solution Approach 1:
The patent extracts only the necessary motion vector information from reference blocks into a separate buffer structure. Instead of storing all motion vectors, only those needed for temporal motion vector prediction are extracted and stored, reducing memory capacity requirements while maintaining prediction accuracy.
Solution Approach 2:
The patent segments the motion vector storage into different components: reference picture buffers and a separate temporal motion vector predictor buffer. This segmentation allows efficient management of memory resources by storing only the specific motion vector information needed for temporal prediction, rather than all motion vectors from reference pictures.
2Measurement precision
If motion vectors are stored in memory for temporal motion vector predictor mode, then prediction accuracy is improved, but bandwidth requirements increase
Solution Approach 1:
The patent extracts only the necessary motion vector information from reference blocks into a separate buffer structure. Instead of storing all motion vectors, only those needed for temporal motion vector prediction are extracted and stored, reducing memory capacity requirements while maintaining prediction accuracy.
Solution Approach 2:
The patent implements dynamic management of the temporal motion vector predictor buffer, where motion vectors are added and removed based on picture type (I, P, or B pictures) and prediction mode. This dynamic approach optimizes bandwidth usage by storing motion vectors only when needed for temporal prediction, rather than maintaining static storage for all possible cases.
3Reliability
If all motion vectors are stored in reference pictures, then complete motion information is available, but memory efficiency decreases
Solution Approach 1:
The patent extracts only the necessary motion vector information from reference blocks into a separate buffer structure. Instead of storing all motion vectors, only those needed for temporal motion vector prediction are extracted and stored, reducing memory capacity requirements while maintaining prediction accuracy.
Solution Approach 2:
The patent applies local quality by treating different picture types (I, P, B pictures) and different blocks differently. Motion vectors are stored and managed based on their specific needs: temporal motion vector prediction is applied only to blocks where it is beneficial, while other blocks use standard prediction modes. This localized approach optimizes memory efficiency by storing motion vectors only where they provide value.
Data Source
AI summary
A moving picture coding apparatus includes a co-located block information determination unit which determines which one of a forward reference block and a backward reference block will be a co-located block and further determines whether only the unidirectional motion vector of the motion vectors of the co-located block is to be stored in a colPic memory; a temporal motion vector predictor calculation unit which derives a candidate motion vector predictor in temporal motion vector predictor mode using the colPic information stored in the colPic memory; and an inter prediction control unit which determines to code a motion vector using a candidate motion vector predictor having least error from the motion vector derived by motion estimation among candidate motion vector predictors.