Media Encoding Subsequence Optimization via Convex Hull Filtering
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Solution Overview
Problem
Existing media encoding techniques, such as monolithic and subsequence-based encoding, face inefficiencies and quality variations, leading to increased computational and storage resources usage and playback interruptions due to inconsistent bitrate and quality levels across media titles.
Innovation Solution
A computer-implemented method that generates encoded media sequences by iteratively optimizing subsequence encode points using convex hull operations and filtering based on variability constraints, ensuring consistent quality and bitrate levels by aggregating individually encoded subsequences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If subsequence-based encoding is used to reduce encoding inefficiencies, then computational and storage resources are optimized, but quality and bitrate variations increase across the media title
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting encoding parameters (bitrate, resolution, quality settings) for different subsequences based on their complexity characteristics. Simple subsequences use lower bitrates while complex subsequences use higher bitrates, optimizing resource usage while maintaining quality consistency through controlled variation within acceptable ranges.
Solution Approach 2:
The patent implements dynamics by making the encoding process adaptive rather than static. The system dynamically determines subsequence complexity, selects appropriate encoding parameters for each subsequence, and ensures that transitions between subsequences maintain quality consistency. This dynamic approach allows the encoding to respond to content variations while constraining overall quality and bitrate variations.
2Manufacturing precision
If monolithic encoding is used with consistent resolution and rate control values, then quality consistency is maintained, but computational and storage resources are wasted on simple portions
Solution Approach 1:
The patent applies segmentation by dividing the media title into multiple subsequences based on complexity characteristics. Instead of encoding the entire media title uniformly, the system segments it into portions that can be encoded with different parameters. This allows simple subsequences to use lower resource settings while maintaining overall quality consistency through proper segmentation and transition handling.
3Manufacturing precision
If bitrate is increased to maintain quality during playback, then visual quality is improved, but bandwidth requirements and storage resources increase
Solution Approach 1:
The patent applies local quality by allowing different quality levels in different parts of the media title based on subsequence complexity. Simple subsequences use lower bitrate and resolution settings, while complex subsequences use higher settings. This local adaptation of quality parameters reduces overall bandwidth consumption and storage requirements while maintaining acceptable visual quality where it matters most.
4Productivity
If quality level is varied across subsequences to reduce encoding inefficiencies, then resource usage is optimized, but playback quality consistency deteriorates
Solution Approach 1:
The patent implements dynamics by making the encoding process adaptive rather than static. The system dynamically determines subsequence complexity, selects appropriate encoding parameters for each subsequence, and ensures that transitions between subsequences maintain quality consistency. This dynamic approach allows the encoding to respond to content variations while constraining overall quality and bitrate variations.
Solution Approach 2:
The patent applies feedback by using complexity analysis results to guide encoding parameter selection for each subsequence. The system analyzes subsequence characteristics, provides feedback on complexity levels, and adjusts encoding parameters accordingly. This feedback mechanism ensures that quality variations remain within acceptable ranges while optimizing resource efficiency.
Data Source
AI summary
In various embodiments, a subsequence-based encoding application generates a first set of subsequence encode points based on multiple encoding points and a first subsequence included in a set of subsequences that are associated with a media title. Notably, each subsequence encode point is associated with a different encoded subsequence. The subsequence-based encoding application then performs convex hull operation(s) across the first set of subsequence encode points to generate a first convex hull. The subsequence-based encoding application then generates an encode list that includes multiple subsequence encode points based on multiple convex hulls, including the first convex hull. Subsequently, the subsequence-based encoding application performs filtering operation(s) on the encode list based on a variability constraint associated with a media metric to generate an upgrade candidate list. Finally, the subsequence-based encoding application generates an encoded media sequence based on the upgrade candidate list and the first convex hull.