Method and device for mapping three-dimensional (3D) point cloud model based on deep learning
US12175691B1 · kind B1 · utility
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Inventors
Key dates
| Filing date | Dec 28, 2023 |
| Grant date | Dec 24, 2024 |
| Priority date | — |
| Expiry date | Dec 28, 2043 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02A90/10
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method for mapping a three-dimensional (3D) point cloud model based on deep learning includes: extracting features of image data by using a convolutional neural network; extracting features of point cloud data by using a PointNet point cloud processing network, and constructing a 3D model of the point cloud data by using a triangular mesh; aligning the 3D model and an image spatially and temporally; performing projection mapping on the aligned 3D model and image, and superimposing location information in the point cloud data onto texture information of the image to obtain a first fused image; fusing the features of the point cloud data and the features of the image data to obtain a second fused image with a fused feature; and superimposing the first fused image onto the second fused image, and obtaining a superimposition weight by using the convolutional neural network, to generate a mapped 3D model.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.