Three-dimensional mesh deformation using deep learning neural networks
US10916054B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Nov 8, 2018 |
| Grant date | Feb 9, 2021 |
| Priority date | — |
| Expiry date | Jan 22, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2219/2021
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Techniques are disclosed for deforming a 3D source mesh to resemble a target object representation which may be a 2D image or another 3D mesh. A methodology implementing the techniques according to an embodiment includes extracting a set of one or more source features from a source 3D mesh. The source 3D mesh includes a plurality of source points representing a source object, and the extracting of the set of source features is independent of an ordering of the source points. The method also includes extracting a set of one or more target features from the target object representation, and decoding a concatenation of the set of source features and the set of target features to predict vertex offsets for application to the source 3D mesh to generate a deformed 3D mesh based on the target object. The feature extractions and the vertex offset predictions may employ Deep Neural Networks.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.