多尺度特征融合的双通道SSD行人头部检测算法  

Two-Channel SSD Pedestrian Head Detection Algorithm Based on Multi-Scale Feature fusion

作　　者：周永福[1] 李文龙 胡冉冉 Zhou Yongfu;Li Wenlong;Hu Ranran(School of Management Engineering,Jilin Communications Polytechnic,Changchun,Jilin 130012,China;School of Electromie Informatiom Engineering,Changchun University of Science and Techrology.Changchun,Jilin 130022,China)

机构地区：[1]吉林交通职业技术学院管理工程学院,吉林长春130012 [2]长春理工大学电子信息工程学院,吉林长春130022

出　　处：《激光与光电子学进展》2021年第24期375-386,共12页Laser & Optoelectronics Progress

基　　金：吉林省重点科技发展计划(20180201042GX)。

摘　　要：针对行人头部易受光照变化和遮挡的影响而导致目标检测准确率较低的问题,提出一种基于多尺度融合的双通道SSD(Single Shot Multibox Detector)行人头部检测算法。首先在SSD网络上增加一条深度通道,将带有深度信息的头部特征与SSD网络的特征进行融合,形成双通道SSD网络;然后在双通道SSD网络的基础上,将具有丰富语义信息的高层特征图与低层特征图进行特征融合,实现更精确的头部定位;最后重新调整SSD的先验框以减少SSD网络的计算量。实验结果表明,在光照和遮挡的情况下,相比于传统SSD目标检测算法,改进后算法的检测精度提高了12.9个百分点,其可有效解决光照变化和遮挡对行人头部检测的影响。Aiming at the problem that pedestrian head is susceptible to illumination changes and occlusion, which leads to low target detection accuracy, a pedestrian head detection algorithm based on two-channel single shot multibox detector(SSD) with multi-scale fusion is proposed. First, a deepth channel is added to the SSD network, and the head features with depth information are fused with the features of the SSD network to form a two-channel SSD network. Then, on the basis of the two-channel SSD network, the high-level feature map with rich semantic information is fused with the low-level feature map to achieve more accurate head location. Finally, the prior frame of SSD is re-adjusted to reduce the computational complexity of the SSD network. Experimental results show that in the case of illumination and occlusion, the detection accuracy of the improved algorithm is improved by 12.9 percentage points compared with the traditional SSD target detection algorithm, and it can effectively solve the influence of illumination changes and occlusion on pedestrian head detection.

关 键 词：机器视觉 行人头部检测 SSD网络 深度信息 多尺度特征融合 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]