Human face silence living body detection method and device, readable storage medium and equipment
A living body detection and living body technology, applied in the field of face recognition, can solve problems such as time-consuming and reduce user experience, and achieve the effect of improving performance, avoiding overfitting, and having good user experience.
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Embodiment 1
[0066] The implementation of the present invention provides a face silent living detection method, such as figure 1 As shown, the method includes:
[0067] Step S100': train a pre-built classification model, wherein:
[0068] The classification model includes several layers of convolutional neural networks. Each convolutional neural network in the previous layer corresponds to two convolutional neural networks in the latter layer. A convolutional neural network in the previous layer can input the convolutional neural network. The face image of the neural network is classified into two types: living body and prosthesis. The first of the two neural networks corresponding to the neural network in the previous layer can be classified as fake by the convolutional neural network in the previous layer. The face image of the body continues to be classified into two categories: living body and prosthesis, and the second of the two neural networks corresponding to the previous layer of...
Embodiment 2
[0137] The embodiment of the present invention provides a silent face detection device, such as Image 6 As shown, the device includes:
[0138] A training module 10' for training a pre-built classification model, wherein:
[0139] The classification model includes several layers of convolutional neural networks. Each convolutional neural network in the previous layer corresponds to two convolutional neural networks in the latter layer. A convolutional neural network in the previous layer can input the convolutional neural network. The face image of the neural network is classified into two types: living body and prosthesis. The first of the two neural networks corresponding to the neural network in the previous layer can be classified as fake by the convolutional neural network in the previous layer. The face image of the body continues to be classified into two categories: living body and prosthesis, and the second of the two neural networks corresponding to the previous la...
Embodiment 3
[0174] The methods described in the above embodiments provided in this specification can implement business logic through a computer program and record them on a storage medium, and the storage medium can be read and executed by a computer to achieve the effects of the solution described in Embodiment 1 of this specification. Therefore, the present invention also provides a computer-readable storage medium for silent face detection, including a memory for storing processor-executable instructions, and when the instructions are executed by the processor, the method for silent face detection in Embodiment 1 is implemented. A step of.
[0175] The invention mainly solves the problem of anti-counterfeiting of the printing-type prosthesis and the screen-type prosthesis. The present invention is the silent living body detection of the face. The silent living body detection of the human face means that it does not require any user cooperation, and only needs to input a face image int...
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