CROSS-REFERENCE TO RELATED APPLICATION

This application claims priority to Chinese Patent Application No. 201910905256.X filed Sep. 24, 2019, the disclosure of which is hereby incorporated by reference in its entirety.

BACKGROUND OF THE INVENTION

The present invention relates to the technical field of face image processing, and in particular, to an age recognition method, a computer storage medium, and an electronic device.

FIELD OF THE INVENTION

With the development of face recognition technologies, people have higher and higher requirements on recognitions of face attributes, especially for age recognition of face.

At present, a general age recognition algorithm is a method of CNN (Convolutional Neural Networks) deep learning technology, and although the CNN technology algorithm has a higher accuracy, it is high in complexity, time-consuming and high in requirement on hardware.

SUMMARY OF THE INVENTION

According to an aspect of the present disclosure, there is provided an age recognition method, comprising:

acquiring a face image to be recognized;

extracting face characteristic points in the face image to be recognized and characteristic point coordinates of the face characteristic points in the face image to be recognized;

extracting face global features from the face image to be recognized according to the characteristic point coordinates;

extracting face local features from the face image to be recognized according to the face characteristic points; and

determining an age recognition result corresponding to the face image to be recognized according to the face global features, the face local features and an age recognition model obtained by pre-training.

Alternatively, after extracting face characteristic points in the face image to be recognized and characteristic point coordinates of the face characteristic points in the face image to be recognized, the method further comprises:

denoising the face image to be recognized to obtain a denoised face image;

performing a geometric correction process on a face region in the denoised face image according to the characteristic point coordinates, to generate a corrected face image; and

acquiring from the corrected face image corrected characteristic points corresponding to the face characteristic points, and corrected characteristic point coordinates corresponding to the corrected characteristic points.

Alternatively, that extracting face global features from the face image to be recognized according to the characteristic point coordinates comprises:

calculating a width and a height of a corrected face region according to the corrected characteristic point coordinates;

performing a normalization process on the corrected characteristic point coordinates according to the width and the height, to obtain normalized coordinates; and

processing the normalized coordinates to generate the face global features.

Alternatively, that performing a normalization process on the corrected characteristic point coordinates according to the width and the height, to obtain normalized coordinates comprises:

performing a normalization process on horizontal coordinates corresponding to the corrected characteristic point coordinates according to the width, to obtain normalized horizontal coordinates; and

performing a normalization process on vertical coordinates corresponding to the corrected characteristic point coordinates according to the height, to obtain normalized vertical coordinates.

Alternatively, that processing the normalized coordinates to generate the face global features comprises:

generating a one-dimensional global feature vector according to the normalized horizontal coordinates and the normalized vertical coordinates, and taking the one-dimensional global feature vector as the face global features.

Alternatively, after acquiring from the corrected face image corrected characteristic points corresponding to the face characteristic points and corrected characteristic point coordinates corresponding to the corrected characteristic points, the method further comprises:

performing a size transformation process on the corrected face region corresponding to the corrected face image according to a preset ratio, to obtain a transformed face image; and

performing a coordinate transformation process on the corrected characteristic point coordinates according to the preset ratio, to obtain transformed characteristic point coordinates.

Alternatively, that extracting face local features from the face image to be recognized according to the face characteristic points comprises:

determining a region of interest in a transformed face region corresponding to the transformed face image according to the transformed face characteristic points in the transformed face image;

extracting initial face local features in the region of interest by adopting a preset feature extraction algorithm; and

calculating normalized histogram features corresponding to the initial face local features, and taking the normalized histogram features as the face local features.

According to another aspect of the present disclosure, there is provided an age recognition device, comprising:

an image to be recognized acquiring module configured to acquire a face image to be recognized;

a characteristic point coordinate extracting module configured to extract face characteristic points in the face image to be recognized and characteristic point coordinates of the face characteristic points in the face image to be recognized;

a global feature extracting module configured to extract face global features from the face image to be recognized according to the characteristic point coordinates;

a local feature extracting module configured to extract face local features from the face image to be recognized according to the face characteristic points; and

a recognition result determining module configured to determine an age recognition result corresponding to the face image to be recognized according to the face global features, the face local features and an age recognition model obtained by pre-training.

Alternatively, the face recognition device further comprises:

a denoised image acquiring module configured to denoise the face image to be recognized to obtain a denoised face image;

a corrected image generating module configured to perform a geometric correction process on a face region in the denoised face image according to the characteristic point coordinates, to generate a corrected face image; and

a corrected characteristic point acquiring module configured to acquire from the corrected face image corrected characteristic points corresponding to the face characteristic points, and corrected characteristic point coordinates corresponding to the corrected characteristic points.

Alternatively, the global feature extracting module comprises:

a height and width calculating sub-module configured to calculate a width and a height of a corrected face region according to the corrected characteristic point coordinates;

a normalized coordinate acquiring sub-module configured to perform a normalization process on the corrected characteristic point coordinates according to the width and the height, to obtain normalized coordinates; and

a global feature generating sub-module configured to process the normalized coordinates to generate the face global features.

Alternatively, the global feature generating sub-module comprises:

a normalized horizontal coordinate acquiring sub-module configured to perform a normalization process on horizontal coordinates corresponding to the corrected characteristic point coordinates according to the width, to obtain normalized horizontal coordinates; and

a normalized vertical coordinate acquiring sub-module configured to perform a normalization process on vertical coordinates corresponding to the corrected characteristic point coordinates according to the height, to obtain normalized vertical coordinates.

Alternatively, the global feature generating sub-module comprises:

a face global feature acquiring sub-module configured to generate a one-dimensional global feature vector according to the normalized horizontal coordinates and the normalized vertical coordinates, and taking the one-dimensional global feature vector as the face global features.

Alternatively, the age recognition device further comprises:

a transformed image acquiring module configured to perform a size transformation process on the corrected face region corresponding to the corrected face image according to a preset ratio, to obtain a transformed face image; and

a transformed feature acquiring module configured to perform a coordinate transformation process on the corrected characteristic point coordinates according to the preset ratio, to obtain transformed characteristic point coordinates.

Alternatively, the local feature extracting module comprises:

a region of interest determining sub-module configured to determine a region of interest in a transformed face region corresponding to the transformed face image according to the transformed face characteristic points in the transformed face image;

an initial local feature extracting sub-module configured to extract initial face local features in the region of interest by adopting a preset feature extraction algorithm; and

a face local feature acquiring sub-module configured to calculate normalized histogram features corresponding to the initial face local features, and take the normalized histogram features as the face local features.

According to another aspect of the present disclosure, there is provided an electronic device, comprising: a processor, a memory and a computer program stored on the memory and executable on the processor, the processor, when executing the program, implementing any of the aforementioned age recognition methods.

According to another aspect of the present disclosure, there is provided a non-transitory computer storage medium having stored thereon computer-readable program instructions, when executed by a processor, perform the age recognition method as described above.

