Encoder-Guided Adaptive Rendering for MMOG Latency
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Solution Overview
Problem
Current technologies for remote gaming struggle to optimize server-side rendering quality based on available bandwidth and computational resources, leading to wasted rendering work and increased latency in interactive applications like MMOGs.
Innovation Solution
The system uses a codec to communicate quantization settings to a renderer, which generates reference images and calculates perceived quality using the structural similarity index, creating a lookup table to match encoder settings with rendering quality settings, thereby optimizing rendering and encoding processes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the server renders video output at the highest quality, then the image quality is improved, but the server-side computational power and energy usage increase significantly
Solution Approach 1:
The system dynamically adjusts rendering quality settings based on real-time encoder feedback about actual encoded quality and bandwidth conditions. The renderer monitors encoder quantization parameters and adjusts rendering resolution, texture quality, and other settings dynamically to match the actual encoded output quality, preventing wasted computation on frames that will be compressed anyway.
Solution Approach 2:
The system implements a feedback loop where the encoder communicates quantization settings and actual encoded quality metrics back to the renderer. The renderer uses this feedback to adjust its rendering quality in real-time, ensuring that rendering effort matches the eventual perceived quality after encoding and transmission.
2Manufacturing precision
If the server renders video output at the highest quality, then the image quality is improved, but the rendering time increases, causing latency in interactive applications
Solution Approach 1:
The system dynamically adjusts rendering quality settings based on real-time encoder feedback about actual encoded quality and bandwidth conditions. The renderer monitors encoder quantization parameters and adjusts rendering resolution, texture quality, and other settings dynamically to match the actual encoded output quality, preventing wasted computation on frames that will be compressed anyway.
Solution Approach 2:
The system implements a feedback loop where the encoder communicates quantization settings and actual encoded quality metrics back to the renderer. The renderer uses this feedback to adjust its rendering quality in real-time, ensuring that rendering effort matches the eventual perceived quality after encoding and transmission.
3Productivity
If the encoder compresses video to fit limited bandwidth, then the transmission efficiency is improved, but the decoded output quality decreases
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing a lookup table that maps encoder quantization settings to optimal rendering quality settings. This lookup table is generated offline by encoding reference frames at various quality levels and measuring the actual encoded output quality, allowing the renderer to quickly determine appropriate rendering settings during runtime without real-time computation.
Solution Approach 2:
The system changes rendering parameters (resolution, texture quality, shadow quality, etc.) based on encoder quantization parameters. By adjusting these rendering parameters to match the encoder's compression level, the system ensures that rendering effort is optimized for the actual transmitted quality, preventing both waste and degradation.
4Speed
If existing video coding methods trade computational power for reductions in encoding time, then the encoding speed is improved, but the computational power requirements still remain high
Solution Approach 1:
The system performs preliminary actions by pre-calculating and storing a lookup table that maps encoder quantization settings to optimal rendering quality settings. This lookup table is generated offline by encoding reference frames at various quality levels and measuring the actual encoded output quality, allowing the renderer to quickly determine appropriate rendering settings during runtime without real-time computation.
Data Source
AI summary
Systems and methods for improving computer technology related to the rendering and encoding of images are disclosed, preferably for use in a video-game environment. In certain embodiments, a codec is used to encode one or more reference images for a partial range of encoder settings and a renderer is used to generate one or more rendering quality-settings profiles, generate one or more reference images, calculate perceived qualities for each of the one or more reference images, re-render the one or more reference images for each of the one or more rendering quality-setting profiles, and calculate perceived qualities for each of the one or more re-rendered reference images. The renderer compares the perceived qualities of the reference images to the perceived qualities of the re-rendered images and matches them. Those matches result in an association of one or more encoder settings with their matching rendering quality-settings profiles into a look-up table. The lookup table is used to generate a rendered image at a substantially identical perceived quality to an encoded frame during gameplay.