Pedestrian re-identification method based on spatio-temporal joint model of residual attention mechanism and device thereof
US11468697B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Dec 14, 2020 |
| Grant date | Oct 11, 2022 |
| Priority date | — |
| Expiry date | Apr 22, 2041 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/103
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
The disclosure provides a pedestrian re-identification method based on a spatio-temporal joint model of a residual attention mechanism and a device thereof. The method includes: performing feature extraction for an input pedestrian with a pre-trained ResNet-50 model; constructing a residual attention mechanism network including a residual attention mechanism module, a feature sampling layer, a global average pooling layer and a local feature connection layer; calculating a feature distance by using a cosine distance and denoting the feature distance as a visual probability according to the trained residual attention mechanism network; performing modeling for a spatio-temporal probability according to camera ID and frame number information in a pedestrian tag of a training sample, and performing Laplace smoothing for a probability model; and calculating a final spatio-temporal joint probability by using the visual probability and the spatio-temporal probability to obtain a pedestrian re-identification result.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.