Predicting the appearance of deformable objects in video games
AssigneeElectronic Arts Inc.
InventorChristopher Lewin
Life of this patent
Estimating the term…
Abstract
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.
Claims20
A computer-implemented method of predicting an appearance of a deformable object in a video game, comprising:
- determining a configuration of a moveable object underlying the deformable object;
- inputting, into a machine-learning model, input data comprising a representation of the configuration of the moveable object;
- generating, as output of the machine-learning model, a model output including both a code for mesh data and a code for texture data for predicting the appearance of the deformable object;
- determining, from the model output including both the code for the mesh data and the code for the texture data, the mesh and texture data for the deformable object;
- and
- rendering the deformable object using the generated mesh and texture data.
A computer-implemented method of training a machine-learning model for predicting an appearance of a deformable object in a video game, the method comprising:
- performing one or more simulations of the deformable object overlying a moveable object, wherein the moveable object is in a particular configuration for each time step of a plurality of time steps of a simulation;
- for each simulation of the one or more simulations:
- generating one or more training examples for the simulation, wherein each training example comprises, for a particular time step of the simulation:
- (i) a representation of a configuration for the moveable object, (ii) a code for mesh data for the deformable object, and (iii) a code for texture data for the deformable object;
- and
- updating parameters of the machine-learning model, comprising for each of one or more training examples:
- inputting, into the machine-learning model, input data for the training example, the input data comprising the representation of the configuration of the moveable object;
- generating, as output of the machine-learning model, a model output including both a code for a predicted normal map and a code for a predicted mesh for predicting the appearance of the deformable object;
- and
- updating parameters of the machine-learning model based on a comparison of the model output for the training example with both:
- (i) the code for the mesh data, and (ii) the code for the texture data.
A non-transitory computer-readable medium containing instructions, which when executed by one or more processors, causes the one or more processors to perform a method comprising:
- determining a configuration of a moveable object underlying a deformable object in a video game;
- inputting, into a machine-learning model, input data comprising a representation of the configuration of the moveable object;
- generating, as output of the machine-learning model, a model output including both a code for mesh data and a code for texture data for predicting an appearance of the deformable object;
- determining, from the model output including both the code for the mesh data and the code for the texture data, the mesh and texture data for the deformable object;
- and
- rendering the deformable object using the generated mesh and texture data.
Dependencies are inferred from the claim text.