Weighted Motion Vector Prediction for Video Encoding

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Solution Overview

Problem

Existing video encoding technologies face challenges in achieving accurate motion vector prediction, which affects the encoding compression rate.

Innovation Solution

A method for acquiring motion vectors by obtaining related motion vectors from blocks with the same prediction mode, determining weights for these vectors, and calculating a weighted motion vector for the current block.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Measurement precision

If traditional motion vector prediction methods are used, then the encoding process is simple, but the prediction accuracy is low which affects compression rate

Engineering Contradiction:

Improvemotion vector prediction accuracyVSAvoidencoding process complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent segments the motion vector prediction process into multiple stages: collecting motion vectors from different reference frames and blocks, calculating weights based on block characteristics and distances, and performing weighted combination. This segmentation allows for higher accuracy while maintaining manageable complexity through structured processing steps.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The patent introduces weight parameters that dynamically change based on block characteristics, reference frame distances, and motion patterns. By adjusting these parameters adaptively, the system achieves higher prediction accuracy without requiring fundamentally complex encoding architecture.

Inventive Principle:

Principle #35Parameter changes

2Measurement precision

If multiple related motion vectors are collected and weighted calculated, then the prediction accuracy improves, but the calculation complexity increases

Engineering Contradiction:

Improvemotion vector prediction accuracyVSAvoidcalculation complexity

Core Design Contradiction:

Measurement precisionVSPower

Solution Approach 1:

The patent applies local quality by determining weights based on specific block characteristics such as block size, position, and motion patterns. Different regions and blocks receive customized weight assignments, which improves local prediction accuracy while avoiding the need for complex global optimization algorithms.

Inventive Principle:

Principle #3Local quality

Solution Approach 2:

The patent collects motion vectors from multiple reference frames and blocks (excessive action) but selectively applies weighting and combination only where it provides significant benefit. This partial application of complex processing reduces overall calculation complexity while maintaining accuracy where it matters most.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS12244822B2Method for acquiring motion vectors, prediction method and device

Publication Date: 2025.03.04 ZHEJIANG DAHUA TECH CO LTD

AI summary

A method for acquiring motion vectors includes: obtaining a number of related motion vectors of a current block, wherein the number of related motion vectors are motion vectors of a related block of the current block, a prediction mode of the related block is the same as a current prediction mode of the current block, an encoding has been completed; determining weights of at least part of the number of related motion vectors; and calculating a weighted motion vector of the current block based on at least part of the number of related motion vectors and the weights of at least part of the plurality of related motion vectors.