Machine Learning Deformable Object Appearance Prediction
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Solution Overview
Problem
Current simulation methods for animating deformable objects in video games are computationally expensive, making real-time rendering challenging.
Innovation Solution
A computer-implemented method using a machine learning model to predict the appearance of deformable objects by determining the configuration of underlying moveable objects, generating mesh and texture data, and rendering the objects using these data, which reduces computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If simulation methods are used to animate deformable objects, then the appearance realism is improved, but the computational cost increases
Solution Approach 1:
The patent pre-computes and stores correspondence relationships between moveable object configurations and deformable object appearances during an offline training phase. This preliminary action allows the system to avoid performing expensive simulations in real-time, instead simply looking up pre-computed results during gameplay, thus resolving the contradiction between appearance realism and computational cost
Solution Approach 2:
The patent creates a simplified computational model (machine learning model) that copies the essential visual appearance characteristics of deformable objects from complex physics simulations. This copy captures the visual essence without requiring the full computational machinery of traditional simulation methods, enabling realistic appearance at lower computational cost
2Measurement precision
If simulation methods are used to animate deformable objects, then the visual accuracy is improved, but the processing time increases
Solution Approach 1:
The system performs visual accuracy optimization in advance by training the machine learning model offline with high-fidelity simulation data. During real-time rendering, the pre-trained model instantly provides visually accurate results without requiring time-consuming simulations, thus resolving the contradiction between visual accuracy and processing time
Solution Approach 2:
The patent replaces the traditional physics-based simulation mechanical system with a machine learning-based predictive system. This substitution maintains visual accuracy by learning from simulation data but eliminates the time-consuming nature of real-time physics calculations, enabling fast rendering
Data Source
AI summary
This specification describes a computer-implemented method of predicting the appearance of a deformable object in a video game. The method comprises determining a configuration of a moveable object underlying the deformable object. Input data is inputted into a machine-learning model. The input data comprises a representation of the configuration of the moveable object. A model output is generated as output of the machine-learning model for predicting the appearance of the deformable object. Mesh and texture data for the deformable object is determined from the model output. The deformable object is rendered using the generated mesh and texture data.