Complexity-Aware Video Encoding for Rate-Distortion-Cycle Tradeoffs
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Solution Overview
Problem
Conventional convex-hull-optimized encoding methods are computationally demanding and do not consider processor cycle costs, leading to inefficient use of resources and limiting high-quality video streaming to high-paying users.
Innovation Solution
A complexity aware encoding system that applies a weighted measure to rate, distortion, and number of cycles, using negative distortion biases to favor lower resolutions, higher QPs, and lower bit rates, optimizing the convex-hull algorithm for better tradeoffs between quality and processing cycles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If conventional convex-hull-optimized encoding is used to improve video quality, then video quality is improved, but processor cycle cost increases significantly
Solution Approach 1:
The patent changes the optimization parameters of the convex-hull algorithm by introducing a weighted measure that incorporates processor cycle costs alongside rate and distortion. This modifies the objective function to balance video quality improvement against computational expense, allowing the system to select encoding parameters that achieve acceptable quality at reduced processor cycle costs.
Solution Approach 2:
The patent applies different weighting factors to different segments or regions of the video encoding process, allowing local optimization where high quality is prioritized for important content while accepting lower quality in less critical areas. This enables differential allocation of processor cycles based on local content importance.
2Manufacturing precision
If conventional convex-hull-optimized encoding is used to improve video quality, then video quality is improved, but encoding time increases
Solution Approach 1:
By modifying the convex-hull algorithm to include encoding time as a weighted parameter alongside rate and distortion, the system optimizes for a balanced tradeoff. The weighted measure allows the algorithm to identify encoding configurations that achieve sufficient video quality while minimizing total encoding time, rather than prioritizing quality alone.
3Manufacturing precision
If conventional convex-hull-optimized encoding is used to improve video quality, then video quality is improved, but computational complexity increases
Solution Approach 1:
The patent modifies the computational parameters of the convex-hull algorithm by introducing a weighted measure that incorporates processor cycle costs. This changes the complexity characteristics of the algorithm from purely quality-driven to a balanced optimization that considers computational expense, thereby reducing overall computational complexity while maintaining acceptable video quality.
Data Source
AI summary
This disclosure describes systems, methods, and devices related to complexity aware encoding. A device may generate a list of encodes based on pairs of resolution and quantization parameters (QP) pairs associated with one or more video segments received from a source. The device may generate an estimated bit rate associated with the one or more video segments based on an analysis of the one or more video segments. The device may determine distortion values associated with the one or more video segments. The device may apply a weighting mechanism to the distortion values using the estimated bit rate. The device may select a subset of encodes based on the weighting mechanism. The device may perform the subset of encodes on the one or more video segments for transmission.