Method for person re-identification based on deep model with multi-loss fusion training strategy
US11195051B2 · kind B2 · utility
Assignees
Inventors
Key dates
| Filing date | Mar 9, 2020 |
| Grant date | Dec 7, 2021 |
| Priority date | — |
| Expiry date | Mar 25, 2040 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06N3/047
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The invention relates to a method for person re-identification based on deep model with multi-loss fusion training strategy. The method uses a deep learning technology to perform preprocessing operations such as flipping, clipping, random erasing and style transfer, and then feature extraction is performed through a backbone network model; joint training of a network is performed by fusing a plurality of loss functions. Compared with other deep learning-based person re-identification algorithms, the present invention greatly improves the performance of person re-identification by adopting a plurality of preprocessing modes, the fusion of three loss functions and effective training strategy.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.