Representation learning for object detection from unlabeled point cloud sequences
US12397817B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Jul 7, 2022 |
| Grant date | Aug 26, 2025 |
| Priority date | — |
| Expiry date | Aug 5, 2043 |
Classification
- Technology area (CPC B)Performing Operations; Transporting
- CPC primaryB60W60/001
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A method of representation learning for object detection from unlabeled point cloud sequences is described. The method includes detecting moving object traces from temporally-ordered, unlabeled point cloud sequences. The method also includes extracting a set of moving objects based on the moving object traces detected from the sequence of temporally-ordered, unlabeled point cloud sequences. The method further includes classifying the set of moving objects extracted from on the moving object traces detected from the sequence of temporally-ordered, unlabeled point cloud sequences. The method also includes estimating 3D bounding boxes for the set of moving objects based on the classifying of the set of moving objects.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.