Mobile terminal face recognition method and system based on technology of embedded deep learning

Abstract

The invention belongs to the field of image recognition, and specifically provides a mobile terminal face recognition method and system based on the technology of embedded deep learning. The invention aims at solving problems in the prior art that a human face recognition program is complex, an occupied memory is large, the recognition speed is small, the recognition precision is low and a hand-held mobile terminal for human face recognition is limited by a network signal. In order to solve the above problems, the system comprises a human face detection module for obtaining a face region of a target person; a feature extraction module which is used for obtaining the face features of the target person according to the obtained face region; and a feature comparison module which is used for calculating the similarity between the obtained face features of the target person and preset face features, wherein the human face detection module, the feature extraction module and the feature comparison module are disposed on a mobile terminal. Therefore, the system enables the mobile terminal to be able to judge the identity of the target person quickly and accurately under the condition that there is no network signal.

Description

technical field [0001] The invention belongs to the field of image recognition, and specifically provides a mobile terminal face recognition method and system based on embedded deep learning technology. Background technique [0002] In the field of public security, such as during police patrols or on duty, staff need to quickly identify suspicious persons at the scene of emergencies and large-scale activities, such as judging whether the suspicious person is a fugitive, a petitioner or a gap seeker troublemakers, etc. Therefore, there is an urgent need for a mobile and portable identification system. [0003] The method usually adopted at present is to take photos of suspicious persons through a handheld mobile terminal, and then upload the photos to the server through a wireless network, and the server will match the photos taken by the mobile terminal with the photos in the portrait database, and finally the server will The matching result is fed back to the handheld mob...

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above-mentioned problems in the prior art, that is, in order to solve the complex face recognition program in the prior art, occupying a large memory, slow recognition speed, low recognition accuracy, and hand-held mobile terminals that recognize faces are limited by network signals problem, the present invention provides a mobile terminal face recognition system based on embedded deep learning technology, including a face detection module, a feature extraction module, a feature comparison module, and a portrait database module. The feature extraction module is based on depth The facial feature in the facial image of the target person that the face recognition model of study extracts; Described portrait database module comprises portrait characteristic data and the quick index tree of portrait characteristic data; Described feature comparison module is configured to The facial features extracted by the feature extraction module are quickly matched based on the fast index tree in the portrait database module, and the matching result is output

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