Adaptive Motion Vector Precision for Video Coding
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Solution Overview
Problem
Current video coding technologies face challenges in efficiently encoding motion vectors, particularly in determining the optimal precision for motion vector differences (MVDs) across different types of video content, leading to suboptimal rate-distortion tradeoffs and increased bitrate for certain content types.
Innovation Solution
The techniques involve adaptively determining motion vector precision based on the content type, allowing for higher precision motion vectors where beneficial and lower precision where they do not improve coding quality, and using multiple MVD coding techniques to optimize bitstream representation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If higher precision motion vectors are used for all video content, then motion vector accuracy is improved, but bitrate increases
Solution Approach 1:
The patent applies different motion vector precision levels to different video content types. Specifically, it uses higher precision (e.g., 1/4 pixel or 1/8 pixel) for content that benefits from it (such as natural video with smooth motion) and lower precision (e.g., integer pixel) for content where high precision provides minimal benefit (such as screen content with sharp edges). This local differentiation resolves the contradiction by optimizing precision per content type rather than applying a uniform standard.
Solution Approach 2:
The patent dynamically changes the motion vector precision parameter based on content type detection. The system detects whether the video content is natural video, screen content, or mixed content, and adjusts the MVD precision accordingly. This parameter adaptation allows the system to achieve high precision where needed while maintaining low precision where sufficient, thereby optimizing the bitrate-accuracy tradeoff.
2Productivity
If multiple MVD coding techniques are implemented, then coding efficiency is improved, but device complexity increases
Solution Approach 1:
The patent implements a dynamic selection mechanism that chooses among multiple MVD coding techniques (such as CABAC, CAVLC, or other entropy coding methods) based on the specific content being encoded. Rather than implementing all techniques simultaneously or using a fixed technique, the system dynamically selects the most appropriate coding method for each block or sequence based on content characteristics, resolution, and other factors. This dynamic approach improves coding efficiency while managing complexity through selective implementation.
Solution Approach 2:
The patent divides the video content into different segments or blocks that can be encoded using different MVD coding techniques. By segmenting the video stream and applying different coding methods to different segments based on their specific characteristics, the system achieves improved overall coding efficiency without requiring the entire system to handle all possible coding techniques simultaneously, thus managing device complexity.
Data Source
AI summary
Coding a motion vector difference (MVD) during an inter-prediction process. Example techniques may include determining a particular coding and/or signaling method for an MVD from among two or more MVD coding and/or signaling techniques. A video coder (e.g., a video encoder and/or a video decoder) may determine a particular MVD coding and/or signaling technique based on characteristics of video data or coding methods, including MV precision, Picture Order Count (POC) difference, or any other already coded/decoded information of a block of video data.


