Parametric Motion Vector Prediction for Complex Video Coding
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Solution Overview
Problem
Conventional motion prediction techniques in video coding, such as HEVC, are inadequate for handling complex motions like zoom and rotation, leading to inefficiencies in bit rate requirements and increased computational complexity.
Innovation Solution
The introduction of a Parametric Motion Vector Predictor (PMVP) using higher-order motion models and an efficient compression scheme based on transformation, quantization, and difference coding to predict and compress complex motion, replacing conventional predictors and merging spatial predictors for reduced bit indexing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional motion prediction techniques are used, then device complexity is reduced, but manufacturing precision (motion prediction accuracy) deteriorates for complex motions like zoom and rotation
Solution Approach 1:
The patent applies parameter changes by transitioning from conventional first-order motion models to higher-order parametric motion models. The PMVP uses parametric representations (e.g., affine transformations, perspective transformations) that introduce additional parameters to accurately describe complex motions like zoom and rotation, thereby improving motion prediction accuracy while managing computational complexity through efficient parameter estimation techniques.
2Manufacturing precision
If higher-order motion models are used to predict complex motion, then manufacturing precision improves, but device complexity increases
Solution Approach 1:
The patent implements partial action by selectively applying higher-order parametric motion models only when complex motions (zoom, rotation) are detected, rather than universally applying them to all video blocks. This approach improves prediction accuracy for complex motions while avoiding the computational overhead of higher-order models for simple translational motions, thus balancing precision and complexity.
3Loss of information
If conventional motion prediction techniques are used, then device complexity is reduced, but loss of information increases for complex motions
Solution Approach 1:
The patent applies preliminary action by performing motion model selection and parameter estimation in advance during the encoding process. The encoder预先 determines the appropriate parametric motion model and estimates its parameters before generating the final motion vectors, ensuring that accurate motion information is prepared upfront. This preliminary processing reduces information loss for complex motions while managing computational complexity through efficient pre-computation strategies.
Data Source
AI summary
Parametric Motion Vector Prediction (PMVP) methodologies and components and systems for performing those methodologies are provided to more effectively and efficiently encode video content that includes complex motion such as zoom or rotation. By substituting the PMVP for a collocated MVP used in HEVC in order to reduce the amount of bit rate increase required when including the PMVP analysis in the bit stream. Further, compression of the motion vectors is provided in a three stage approach based on transformation, quantization and difference coding.