True Motion Vector Editing Tool for Video Frame Interpolation
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Solution Overview
Problem
Current automatic motion vector calculations for frame interpolation often result in artifacts, reducing the quality of interpolated frames in video conversion from lower to higher frame rates.
Innovation Solution
A true motion editing tool that generates motion vectors based on object boundaries, using a framework with modules for object boundary identification, motion estimation, and layer generation, allowing for manual or automated editing to improve accuracy and reduce user workload.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If automatic motion vector calculations are used for frame interpolation, then the process is efficient and automated, but artifacts appear in interpolated frames reducing video quality
Solution Approach 1:
The patent introduces an intermediary manual editing interface between automatic motion vector calculation and frame interpolation. Users can manually adjust motion vectors by dragging control points on object boundaries, allowing correction of automatic calculation errors while maintaining overall automation. This intermediary step resolves the contradiction by enabling precision adjustment without eliminating automation entirely.
Solution Approach 2:
The patent segments the video frame into multiple objects with distinct boundaries, allowing independent motion vector editing for each object. By dividing the overall motion field into object-specific segments, users can precisely control motion vectors for individual objects while the system handles automatic calculation for others, balancing automation and precision at different levels.
2Manufacturing precision
If manual editing of motion vectors is performed to improve accuracy, then video quality improves, but user workload increases
Solution Approach 1:
The system provides self-service by automatically generating initial motion vectors and object boundaries, then allowing users to make minimal adjustments only where needed. The automatic system handles the bulk of the work (segmentation, initial vector calculation), and users only perform corrective edits on specific objects, significantly reducing overall user workload while maintaining high accuracy.
Solution Approach 2:
Instead of requiring users to edit all motion vectors manually, the system applies partial action by automatically handling most vectors and requiring manual editing only for objects where the automatic calculation is insufficient. This selective approach reduces user workload to only the necessary portions while maintaining overall precision.
3Manufacturing precision
If object boundary-based motion vector generation is used, then motion accuracy improves, but device complexity increases
Solution Approach 1:
The patent implements a universal framework where a single object boundary identification and motion editing system handles multiple objects and various editing operations. The same interface and algorithms work across different video content and object types, reducing the need for multiple specialized tools and minimizing overall system complexity despite the advanced functionality provided.
Data Source
AI summary
A method of generating motion vectors for image data includes identifying boundaries of at least one object in original frames of image data, performing object motion analysis based upon the boundaries, performing pixel-level motion layer generation, using the object motion analysis and the pixel-level motion layers to generate motion for blocks in the image data, and producing block level motion information and layer information for the original frames of image data.