基于改进MTCNN网络的目标人脸快速检测  

Fast detection of target face based on the improved MTCNN network

作　　者：贾小硕 曾上游[1] 潘兵 周悦 JIA Xiao-shuo;ZENG Shang-you;PAN Bing;ZHOU Yue(College of Electronic Engineering,Guangxi Normal University,Guilin 541004,China)

机构地区：[1]广西师范大学电子工程学院,广西桂林541004

出　　处：《计算机工程与科学》2020年第7期1262-1266,共5页Computer Engineering & Science

基　　金：国家自然科学基金(11465004)。

摘　　要：传统检测网络在复杂背景下一直存在检测效率低以及准确率低等问题。针对以上问题,在MTCNN网络上进一步设计了MT-Siam网络,主要为以后的单目标独立分割、单目标图像处理等操作快速地提供精准位置定位,从而快速获取目标位置,达到提高检测效率的目的。实验部分在YOLOv3、SSD300和MTCNN基础模型上进行了全面对比,验证了MTCNN网络的优越性,并从对比实验中得出MT-Siam网络在保持高精度的前提下,检测速度与MTCNN网络相比得到70%~85%不等的提升。Traditional detection networks have always had problems of low detection efficiency and low accuracy in complex backgrounds.Aiming at the above problems,this paper further designs the MT-Siam network based on the MTCNN algorithm,which mainly provides accurate position positioning for the independent segmentation of single target,image processing of single target and other operations in the future,so as to quickly obtain the target position and achieve the purpose of improving the detection efficiency.In the experiments,a comprehensive comparison is made on the basic model of YOLOv3,SSD300 and MTCNN to verify the superiority of MTCNN network.The comparative experiments show that,compared with MTCNN,the proposed MT-Siam algorithm can improve the detection speed by 70%to 85%while maintaining high precision.

关 键 词：卷积神经网络 MTCNN 检测网络 YOLOv3 目标分割 SSD300 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]