Cloud DVR Storage Bit Rate Selection
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Solution Overview
Problem
Current just-in-time transcode (JITX) systems in network DVRs store the highest bit rate representation of video content, which is wasteful due to not accounting for variability in content complexity, leading to excessive storage and transcoding requirements.
Innovation Solution
The system determines a quality metric for each video segment, storing the lowest bit rate representation that meets a predefined minimum quality threshold, allowing for reduced storage and transcoding by using padding or transcoding based on the quality metric, thereby balancing compression efficiency and compute resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the highest bit rate representation is stored for all video content, then all quality requirements are met, but storage space and transcoding workload are excessive
Solution Approach 1:
The patent applies local quality by analyzing video complexity at the segment level and storing different bit rate representations based on local content characteristics. Simple segments are stored at lower bit rates while complex segments are stored at higher bit rates, rather than applying a uniform highest bit rate to all content. This resolves the contradiction by matching storage quality to actual content requirements.
Solution Approach 2:
The patent changes the parameter of bit rate selection from a fixed highest value to a dynamically determined value based on video complexity analysis. By introducing quality metrics and complexity thresholds, the system adapts the stored bit rate parameter to match content requirements, reducing storage space while maintaining adequate quality.
2Reliability
If the highest bit rate representation is stored for all video content, then all quality requirements are met, but transcoding workload is excessive
Solution Approach 1:
The patent performs preliminary analysis of video complexity during the encoding stage and stores multiple bit rate representations in advance. This preliminary action eliminates the need for extensive transcoding during playback, as the appropriate bit rate representation is already available. The system prepares quality metrics and complexity assessments beforehand to guide storage decisions.
Solution Approach 2:
The patent introduces dynamic selection of stored representations based on video complexity characteristics. Rather than statically storing only the highest bit rate, the system dynamically determines which bit rate representations to store based on segment-specific complexity analysis, reducing the need for dynamic transcoding during playback operations.
3Device complexity
If a fixed set of bit rates is provided for ABR streaming, then implementation is simple, but storage requirements increase to accommodate all representations
Solution Approach 1:
The patent segments the video content and analyzes complexity at the segment level, allowing different storage strategies to be applied to different segments. This segmentation enables the system to provide a fixed set of bit rate representations only where needed (for complex segments) while using lower bit rates for simple segments, reducing overall storage requirements while maintaining implementation simplicity.
Solution Approach 2:
The patent applies partial action by providing multiple bit rate representations only for video segments that require them (complex segments), rather than providing all representations for all segments. This selective approach reduces storage space while maintaining the simplicity of fixed bit rate sets where applicable.
Data Source
AI summary
A method in an encoder, the method comprising: receiving a video; encoding a segment of the video at different bit rates to generate multiple representations of the segment at different bit rates; generating a quality metric for each representation of the video segment; and storing the lowest bit rate representation of the video segment for which the respective quality metric meets a predefined minimum quality threshold.