Intelligent face tracking system and method based on depth learning and large-scale clustering

Abstract

The invention relates to an intelligent face tracking system and method based on depth learning and large-scale clustering. The system comprises a video input unit, a distribution server, a face identification server cluster, a streaming media server, a distributed file server, a message center server, a web front server and a client of a common operation system. According to the invention, by use of large-scale cluster servers, based on depth learning based face identification technology, a quite high identification rate can still be maintained under the condition of degraded image quality, and more important, a quite low false alarm rate and a quite low missed examination rate are maintained in a large-scale database, such that the reliability and the robustness of the intelligent tracking system can be ensured, and the intelligent tracking system based on face identification can be really applied to the field of safety protection.

Description

technical field [0001] The invention belongs to the field of security monitoring, and specifically relates to a face chasing system and method based on deep learning and large-scale clusters. Background technique [0002] With the rapid development of the economy and the acceleration of urban construction, the population in the city is dense, the floating population is increasing, and the social crime rate is increasing year by year, which has caused urban management issues such as transportation, social security, and key area prevention in urban construction. . Therefore, in recent years, in response to the high mobility of criminals, the complexity of the situation, and the difficulty in the deployment and control of key personnel, the face-based intelligent control and escape system has emerged as the times require. This type of system can be applied to the traditional video surveillance network, and does not require the cooperation of users, so the operation is highly c...

AI Technical Summary

Problems solved by technology

Furthermore, when the size of the database reaches a certain order of magnitude (such as a million), the false alarm rate and missed detection rate of the current face recognition system will increase significantly, resulting in a greatly increased chance of criminals evading inspection.

Therefore, the large-scale application of the intelligent monitoring system based on face recognition in the field of public security is largely limited.

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