Real-time Rendering Method Using Energy-Error Precomputation
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Solution Overview
Problem
Current rendering technologies consume excessive energy on battery-powered devices, reducing battery life and image quality, with existing solutions being limited in scope and often requiring hardware modifications or compromising image quality.
Innovation Solution
A real-time rendering method based on energy consumption-error precomputation, which involves adaptive subdivision of camera position and look subspaces to determine optimal rendering parameters that balance energy consumption and error, using Pareto curves to find the best parameters for rendering 3D scenes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If high resolution rendering is used to improve image quality, then rendering quality is improved, but energy consumption increases and rendering time increases
Solution Approach 1:
The camera position space and look space are divided into multiple subspaces through adaptive subdivision, creating a hierarchical spatial level structure. This segmentation allows the system to precompute rendering parameters for different spatial regions and select appropriate parameters based on current camera position, reducing real-time computation energy while maintaining rendering quality.
Solution Approach 2:
The system performs precomputation of rendering parameters and builds Pareto curves for energy consumption versus rendering error in advance for each subspace. This preliminary action stores optimal rendering configurations before runtime, enabling fast selection during actual rendering without repeating expensive computations, thus reducing real-time energy consumption.
2Manufacturing precision
If high resolution rendering is used to improve image quality, then rendering quality is improved, but rendering time increases
Solution Approach 1:
Rendering parameters are precomputed and stored in a spatial level structure before runtime. During actual rendering, the system only needs to query and select precomputed parameters based on current camera position, dramatically reducing rendering time while maintaining high quality through the use of preoptimized parameters.
Solution Approach 2:
The system dynamically selects rendering parameters based on the current camera position and look direction by querying the spatial level structure. This dynamic selection allows the system to adaptively choose the most appropriate precomputed parameters for the current view, balancing rendering quality and speed without fixed constraints.
3Use of energy by moving object
If existing rendering optimization methods are used to reduce energy consumption, then energy consumption is reduced, but they are limited to specific Apps and require hardware modifications
Solution Approach 1:
The spatial level structure and Pareto curve-based optimization method are designed as a universal framework that can be applied to different rendering scenarios and applications. The system works with standard rendering pipelines and does not require hardware modifications, making it broadly applicable across different Apps and devices while reducing energy consumption.
Data Source
AI summary
The invention discloses a real-time rendering method based on energy consumption-error precomputation, comprising: determining the spatial level structure of the scene to be rendered through adaptive subdivision of the space positions and look space of the camera browsable to the user in the 3D scene to be rendered; during the process of adaptive subdivision of the space, for each position subspace obtained at the completion of each subdivision, obtaining the error and energy consumption of the camera for rendering the 3D scene using a plurality of sets of preset rendering parameters in each look subspace at each vertex of the bounding volume that bounds the position subspace, and Pareto curve of the corresponding vertex and look subspace is built based on the error and energy consumption; based on the current camera viewpoint information, searching and obtaining the target Pareto curve in the spatial level structure to determine a set of rendering parameters satisfying the precomputation condition as optimum rendering parameters to perform rendering. The present invention not only saves a great deal of energy, but also ensures the quality of rendering result and extends the battery life.