Face emotion recognition method based on dual-stream convolutional neural network
US11010600B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 24, 2019 |
| Grant date | May 18, 2021 |
| Priority date | — |
| Expiry date | Aug 7, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06V40/176
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
A face emotion recognition method based on dual-stream convolutional neural network uses a multi-scale face expression recognition network to single frame face images and face sequences to perform learning classification. The method includes constructing a multi-scale face expression recognition network which includes a channel network with a resolution of 224×224 and a channel network with a resolution of 336×336, extracting facial expression characteristics at different resolutions through the recognition network, effectively combining static characteristics of images and dynamic characteristics of expression sequence to perform training and learning, fusing the two channel models, testing and obtaining a classification effect of facial expressions. The present invention fully utilizes the advantages of deep learning, effectively avoids the problems of manual extraction of feature deviations and long time, and makes the method provided by the present invention more adaptable. Moreover, the present invention improves the accuracy and productivity of expression recognition.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.