Pedestrian re-identification method based on virtual samples
US11837007B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 20, 2023 |
| Grant date | Dec 5, 2023 |
| Priority date | — |
| Expiry date | Jun 20, 2043 |
Classification
- Technology area (CPC Y)Emerging Cross-Sectional Technologies
- CPC primaryY02T10/40
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
This invention proposes a pedestrian re-identification method based on virtual samples, comprising following steps: s1) obtaining virtual persons generated by game engine, and generating the virtual samples with person labels by fusing a background of a target dataset and a pose of real persons through a multi-factor variational generation network; s2) rendering the generated virtual samples according to lighting conditions; s3) sampling the rendered virtual samples according to person attributes of target dataset; s4) constructing a training dataset according to virtual samples obtained by sampling to train a pedestrian re-identification model, and verifying identification effect of the trained model. The present invention uses a virtual image generation framework that integrates translation-rendering-sampling to narrow the distribution between virtual images and real images as much as possible to generate virtual samples, and conduct person re-identification model training, which can be effectively and effectively applied to pedestrian datasets in real scenes.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.