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US 12,002,289 B2Granted
Expression recognition method and apparatus, computer device, and readable storage medium
AssigneeBoe Technology Group Co., Ltd.
InventorGuannan Chen
Life of this patent
Estimating the term…
Abstract
An expression recognition method and apparatus, a computer device, and a readable storage medium are provided. The method includes: performing face key-point position detection on a face image to obtain face key-point position information; and obtaining expression class information of the face image using four cascaded convolutional modules and a trained neural network classifier according to the face image and the face key-point position information.
Claims20
An expression recognition method, comprising the following steps:
- performing face key-point position detection on a face image to obtain face key-point position information;
- inputting the face image to four cascaded convolutional modules, and sequentially performing feature processing on the input face image to obtain a feature response map output by a fourth convolutional module of the four cascaded convolutional modules;
- inputting the feature response map output by the fourth convolutional module to a global average pooling layer module to obtain a feature vector of a first dimension;
- performing key-point feature extraction on feature response maps output by the first three convolutional modules of the four cascaded convolutional modules respectively using the face key-point position information to obtain key-point feature information of the response feature maps output by the first three convolutional modules respectively;
- connecting the feature vector of the first dimension with the key-point feature information of the feature response maps output by the first three convolutional modules respectively to obtain a feature vector of a second dimension;
- inputting the feature vector of the second dimension to a fully connected layer module, to process the feature vector of the second dimension to obtain a feature vector of a third dimension;
- and
- inputting the feature vector of the third dimension to a trained neural network classifier to output expression class information of the face image through the neural network classifier.
5 more elements
An expression recognition apparatus, comprising:
- a processor and a storage device, wherein the storage device is configured to store processor-executable programs, and the programs comprise:
- a face key-point position detection module, configured to perform face key-point position detection on a face image to obtain face key-point position information;
- four cascaded convolutional modules, configured to input the face image and sequentially perform feature processing on the input face image to obtain a feature response map output by a fourth convolutional module of the four cascaded convolutional modules;
- a global average pooling layer module, configured to obtain a feature vector of a first dimension according to the input feature response map output by the fourth convolutional module;
- a key-point feature information module, configured to perform key-point feature extraction on feature response maps output by the first three convolutional modules of the four cascaded convolutional modules respectively using the face key-point position information to obtain key-point feature information of the response feature maps output by the first three convolutional modules respectively;
- a feature vector connecting module, configured to connect the feature vector of the first dimension with the key-point feature information of the feature response maps output by the first three convolutional modules respectively to obtain a feature vector of a second dimension;
- a fully connected layer module, configured to process the input feature vector of the second dimension to obtain a feature vector of a third dimension;
- and
- a neural network classifier, configured to input the feature vector of the third dimension to a trained neural network classifier to output expression class information of the face image through the neural network classifier.
6 more elements
Dependencies are inferred from the claim text.