Predictive Image Prioritization via Probability Fields
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Solution Overview
Problem
Conventional computing devices, particularly in gaming and virtual reality, face challenges in accurately rendering images when rapid changes in user orientation occur, leading to potential misalignment due to prediction errors in head position, resulting in suboptimal image rendering and increased bandwidth usage.
Innovation Solution
The implementation of a probability field that prioritizes image portions for rendering based on predicted changes in scene orientation, using a prediction error model and human body movement limitations to determine which areas of the image are likely to change, allowing for overrendering and efficient reprojection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If the image is overrendered at a resolution greater than a predicted visible region to account for orientation changes, then the image rendering accuracy is improved, but the bandwidth usage increases
Solution Approach 1:
The patent applies local quality by differentiating the rendering resolution across different regions of the image. High-resolution rendering is applied only to the predicted visible region and its surrounding buffer area, while lower resolution is applied to the rest of the image. This is achieved through a probability field that assigns different rendering priorities to different image regions based on predicted head movement, thereby reducing overall bandwidth usage while maintaining high rendering accuracy where needed.
2Manufacturing precision
If the image is rendered at a higher resolution to compensate for prediction errors in head position, then the image accuracy is improved, but the processing time increases
Solution Approach 1:
The patent reduces processing time by applying high-resolution rendering only to the predicted visible region and its buffer area, rather than rendering the entire image at high resolution. The probability field guides the rendering process to allocate computational resources efficiently, focusing on regions that are likely to be visible given predicted head movement, thereby reducing overall processing time while maintaining image accuracy in critical areas.
Solution Approach 2:
The patent uses preliminary action by predicting head position and orientation changes before rendering the image. The probability field is generated based on predicted head movement, allowing the rendering system to prepare and render only the necessary regions in advance. This predictive approach ensures that the correct image regions are rendered at high resolution before the actual display, reducing processing time by avoiding unnecessary rendering of regions that will not be visible.
3Device complexity
If conventional rendering methods are used without prediction, then the processing simplicity is maintained, but the image alignment accuracy deteriorates
Solution Approach 1:
The patent introduces preliminary action through prediction-based rendering. The system predicts head position and orientation changes before rendering, using this prediction to generate a probability field that guides the rendering process. This preliminary prediction step enables the system to maintain image alignment accuracy by rendering the correct regions in advance, while the overall processing remains relatively simple through the use of probabilistic models and region-based rendering.
Data Source
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AI summary
Examples described herein generally relate to prioritizing portions of images for rendering in a computing device. A probability field for prioritizing portions of an image of a scene for processing can be determined, where the probability field includes a set of values each corresponding to a likelihood of a rendering parameter acquiring an altered value between a render time at which at least a portion of the image is rendered and a display time at which the image is displayed. A shaped probability field can be generated based at least in part on applying the probability field to an original target shape associated with a display. The shaped probability field can be provided to a downstream node for prioritizing, based at least in part on one or more of the set of values in the probability field, a portion of the image in processing the image.