首页期刊在线 2022年（第25卷）第8期

基于预筛动态人脸数据库的城市轨道交通人脸识别过闸系统性能优化方案

展宗思1严军2

Performance Optimization Solution of Urban Rail Transit Face Recognition Gate System Based on Pre-filtering Dynamic Face Database

ZHAN ZongsiYAN Jun

作者信息:

1.1.西安市轨道交通集团有限公司， 710018，西安；
2.2.成都智元汇信息技术股份有限公司， 610213，成都
Affiliation:

Xi′an Rail Transit Group Co., Ltd., 710018, Xi′an, China
关键词:

城市轨道交通;人脸识别过闸系统;预筛动态人脸数据库
Key words:

urban rail transit;face recognition gate system;pre-filtering dynamic face database
DOI:

10.16037/j.1007-869x.2022.08.035
中图分类号/CLCN:

U293.2+2
栏目/Col:

应用技术

摘要:

针对城市轨道交通人脸识别过闸系统存在的性能不足问题，提出了一种基于预筛动态人脸数据库的性能优化方案。该方案通过人脸数据预筛，建立预筛动态人脸数据库，从而缩短人脸识别过闸系统中人脸比对+搜索的耗时，进而实现系统性能优化的目标。经试验，此优化方案能使人脸识别过闸系统性能得到较大提升，具有较高的可行性。

Abstracts:

Targeting the insufficient performance problem of urban rail transit face recognition gate system, a performance optimization solution based on pre-filtering dynamic face database is proposed. Through the pre-filtering of face data, a pre-filtering dynamic face database is established, so as to shorten the time-consumption of face comparison and search in system, thus to achieve the performance optimization goal. It has been verified by experiments that this optimization solution can greatly improve the performance of the face recognition gate system and has relatively high feasibility.