User recognition method for advertising machine based on human faces

Abstract

The invention relates to a user recognition method for an advertising machine based on human faces. The advertising machine plays full-screen advertisements all the time under the condition that thereis no human face; when a human face appears on the screen, AR interaction is performed through the screen to capture an image of the human face, and an eigenvalue of the face image is calculated; andthe eigenvalue of the face image is matched with eigenvalues in a face database so as to perform recognition on the user. The method for calculating the eigenvalue of the face image is further improved, thereby being capable of improving the recognition speed on the basis of ensuring the face recognition accuracy. Identity recognition is performed on the advertising machine by using the human face as an identity feature, thereby being capable of pushing personalized advertisement contents in a targeted manner, avoiding the impact imposed on the user experience by fingerprint recognition in the prior art, and even avoiding a defect that two different users having similar fingerprints may pass fingerprint verification at the same time.

Description

technical field [0001] The invention relates to a face-based advertising machine user identification method, which belongs to the technical field of face recognition. Background technique [0002] The advertising machine is a new generation of intelligent equipment, which constitutes a complete advertising broadcast control system through terminal software control, network information transmission and multimedia terminal display, and through multimedia materials such as pictures, text, video, small plug-ins (weather, exchange rate, etc.) advertising. The original idea of ​​the advertising machine is to change the advertising from passive to active, so the interactive nature of the advertising machine enables it to have many public service functions, and to attract customers to actively browse the advertisements. [0003] With the development of artificial intelligence technology, people's demand for advertising machines is becoming more and more intelligent. Therefore, it w...

AI Technical Summary

Problems solved by technology

For example, the existing neural network model ResNet-50, although its prediction accuracy has reached more than 97%, there is still a lot of room for improvement before the model is put into actual products.

Some improved network models, such as Facenet, etc., have improved the accuracy of their models by using residual units, but they still face problems such as excessive memory usage and low calculation speed.

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