Content-Adaptive Encoding Point Selection for Video Quality
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Solution Overview
Problem
Existing video encoding methods using static lists of encoding operational points fail to optimize video quality and resource usage due to diverse content characteristics within and across videos, leading to suboptimal transcoding results and irregular quality gaps.
Innovation Solution
A system dynamically selects encoding operational points by analyzing video characteristics, generating rate distortion curves, clustering segments, and performing local and global optimizations to generate an optimized list of encoding operational points for each video portion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If default or universal encoding operational points are applied to videos with diverse characteristics, then encoding process simplicity is maintained, but video quality and resource efficiency deteriorate
Solution Approach 1:
The patent segments the video into multiple portions based on content characteristics, and applies different encoding operational points to each segment. This allows the system to maintain simplicity by using automated segmentation algorithms while achieving high quality through content-adaptive encoding parameters for each segment
Solution Approach 2:
The patent dynamically selects encoding operational points based on the characteristics of each video portion. Instead of using static universal parameters, the system adapts encoding settings (such as bitrate, resolution, and compression level) to match the content complexity and visual importance of each segment, thereby optimizing both quality and resource efficiency
2Manufacturing precision
If content-adaptive encoding operational points are selected for each video portion, then video quality and resource efficiency are improved, but system complexity increases
Solution Approach 1:
The patent performs preliminary analysis of video content characteristics before encoding, identifying different portions and their specific requirements in advance. This pre-processing step enables the main encoding system to operate with standardized adaptive algorithms, reducing the complexity burden during the actual encoding process while still achieving content-adaptive quality optimization
3Productivity
If static lists of encoding operational points are used, then encoding speed is maintained, but transcoding optimization deteriorates
Solution Approach 1:
The patent changes encoding parameters (such as bitrate, resolution, and compression level) based on the content characteristics of each video portion. By dynamically adjusting these parameters rather than using fixed static lists, the system achieves optimal transcoding results for different content types while maintaining efficient encoding speeds through automated parameter selection algorithms
Data Source
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Figure 3B
AI summary
In some embodiments, a method receives a plurality of representations of a relationship between bitrate and quality for a first portion of content. Representations in the plurality of representations are based on respective second portions of the content that is included in the first portion of the video. Clusters of the plurality of representations are generated and the clusters are analyzed to determine a first list of encoding operational points for respective clusters. The method analyzes the first list of encoding operational points for respective cluster to determine a second list of encoding operational points. The second list of encoding operational points is output for use in encoding the first portion of content.