Spatial Motion Vector Prediction With Derived Motion Trajectory
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Solution Overview
Problem
Existing block-based hybrid video coding techniques inaccurately or inefficiently represent non-linear motion using linear motion vector prediction, limiting the accuracy and efficiency of coding.
Innovation Solution
Implement spatial motion vector prediction with derived motion trajectory, utilizing motion trajectory data from previous blocks to enhance motion vector prediction for current blocks, thereby improving coding efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If linear motion vector prediction is used in block-based hybrid video coding, then the coding process is simple, but the accuracy of representing non-linear motion is poor
Solution Approach 1:
The patent divides the motion trajectory into multiple segments between reference frames, allowing different linear segments to approximate non-linear motion paths. Each segment uses its own motion vector, enabling accurate representation of complex motion while maintaining computational simplicity through piecewise linear approximation.
Solution Approach 2:
The patent introduces trajectory ID as an additional dimension to traditional motion vector prediction. By assigning trajectory IDs to blocks based on their motion paths and using these IDs to retrieve pre-calculated motion vectors from multiple reference frames, the system enhances prediction accuracy for non-linear motion without increasing computational complexity.
2Measurement precision
If spatial motion vector prediction with derived motion trajectory is implemented, then motion vector prediction accuracy is improved, but the device complexity increases
Solution Approach 1:
The patent pre-calculates and stores motion vectors for multiple reference frames during an initialization phase, organizing them by trajectory ID. This preliminary action allows the decoding stage to simply retrieve and combine pre-computed vectors, significantly reducing real-time computational complexity while maintaining high prediction accuracy.
Solution Approach 2:
The patent introduces trajectory ID as an intermediary that bridges the current block and multiple reference frames. Instead of directly computing complex motion vectors, the system uses trajectory ID to identify and retrieve appropriate pre-calculated vectors from reference frames, simplifying the overall process while improving accuracy.
3Productivity
If multiple reference frames are used with trajectory mapping, then coding efficiency is enhanced, but the amount of data to be processed increases
Solution Approach 1:
The patent creates a universal trajectory mapping structure that serves multiple reference frames simultaneously. By organizing motion vectors from different reference frames under a common trajectory ID framework, the system enables a single data structure to fulfill multiple prediction functions, reducing redundant data storage and processing while enhancing coding efficiency.
Data Source
AI summary
Spatial motion vector prediction with derived motion trajectory includes determining multiple reference frames available for reconstructing a current frame, determining trajectory mapping data for the current frame that is based on motion fields data between respective frames of the sequence of frames, determining a first reference frame of the multiple reference frames used to encode a neighboring block, determining a second reference frame used to encode the current block, determining a motion vector between the neighboring block and a block position within the second reference frame corresponding to the neighboring block according to the trajectory mapping data and a prediction block location for the neighboring block within the first reference frame, where the motion vector is the motion vector predictor for the current block, and reconstructing the video data of the current block using the motion vector predictor.