Distributed face data scheduling method and system, terminal and storage medium

Abstract

The invention discloses a distributed face data scheduling method and system, a terminal and a storage medium, and the method mainly comprises the steps: information base management and special extraction, bottom base management, distribution scheduling, face collection, feature extraction, feature comparison, space-time splicing and labeling, data distribution, data synchronization between a front end and a light-weight cloud center, data transmission safety, data acquisition uplink, dynamic scheduling comparison and downlink dynamic scheduling distribution. Through the distributed architecture design, the data synchronization, distribution and dynamic scheduling of local equipment and a light-weight cloud center are realized, the data efficient transmission and quick response are realized, and the effect of efficient face recognition is achieved; and meanwhile, based on internal and external network firewall reinforcement, the data security is ensured.

Description

technical field [0001] The invention relates to the field of face recognition, in particular to a distributed face data scheduling method, system, terminal and storage medium. Background technique [0002] Face recognition is currently a research hotspot in artificial intelligence and pattern recognition. The initial application originated from the archive management of criminal photos and criminal investigation in the public security department. With the development of science and technology, the requirements for fast, efficient and automatic face recognition are becoming increasingly urgent. This technology has good applications in the fields of document verification, criminal investigation, access control, information security and video surveillance; at present, face recognition application systems at home and abroad are independently maintaining information, photos and face feature databases of various personnel Face recognition algorithm manufacturers have different fac...

AI Technical Summary

Problems solved by technology

This technology has good applications in the fields of document verification, criminal investigation, access control, information security and video surveillance; at present, face recognition application systems at home and abroad are independently maintaining information, photos and face feature databases of various personnel Face recognition algorithm manufacturers have different face feature extraction algorithms, data structures, storage methods, and comparison algorithms. The face feature data among algorithm manufacturers cannot be used universally, and basic face information and personnel photo data lack complete privacy. Protection and update mechanism, the system saves complete personnel information and photos, there is a huge risk of privacy leakage, which is easy to cause personal information to be abused; and face data transmission is slow, cannot respond quickly, and cannot meet the efficiency of face recognition

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