基于扩张重参数化和空洞卷积架构的步态识别方法  

Gait recognition method based on dilated reparameterization and atrous convolution architecture

作　　者：霍丽娜 薛乐仁 戴钰俊 赵新宇 王世行 王威[1] HUO Lina;XUE Leren;DAI Yujun;ZHAO Xinyu;WANG Shihang;WANG Wei(College of Computer and Cyber Security,Hebei Normal University,Shijiazhuang Hebei 050024,China;Software College,Hebei Normal University,Shijiazhuang Hebei 050024,China)

机构地区：[1]河北师范大学计算机与网络空间安全学院,石家庄050024 [2]河北师范大学软件学院,石家庄050024

出　　处：《计算机应用》2025年第4期1285-1292,共8页journal of Computer Applications

基　　金：国家自然科学基金资助项目(61702158);河北省教育厅重点科学基金资助项目(ZD2020317);中央引导地方科技发展资金资助项目(236Z0102G,226Z1808G);河北师范大学科技类科研基金资助项目(L2024ZD15,L2024J01,L2022B22)。

摘　　要：步态识别旨在通过人们的步行姿态进行身份识别。针对步态识别中有效感受野(ERF)与人体轮廓区域匹配不佳的问题,提出一种基于空洞卷积的步态识别方法DilatedGait。首先,采用空洞卷积扩大神经元感受野,缓解下采样和模型深度增加导致的分辨率下降,以提高轮廓结构的辨识度;其次,提出扩张重参数化模块(DRM),通过重参数化方法融合多尺度卷积核参数,优化ERF聚焦范围,使模型捕获更多的全局上下文信息;最后,通过特征映射提取判别性步态特征。在户外数据集Gait3D和GREW上的实验结果表明,对比目前的先进方法GaitBase,DilatedGait在Gait3D的Rank-1和平均逆负惩罚(mINP)上分别提升了9.0和14.2个百分点,在GREW的Rank-1和Rank-5上分别提升了11.6和8.8个百分点。可见,DilatedGait消除了复杂协变量带来的不利影响,能进一步提升户外场景下步态识别的准确率。Gait recognition aims at identifying people by their walking postures.To solve the problem of poor matching between the Effective Receptive Field(ERF)and the human silhouette region,a gait recognition method based on atrous convolution,named DilatedGait,was proposed.Firstly,atrous convolution was employed to expand the neurons’receptive fields,thereby alleviating the resolution degradation by downsampling and model deepening.Therefore,the recognizability of the silhouette structure was enhanced.Secondly,Dilated Reparameterization Module(DRM)was proposed to optimize the ERF focus range by fusing the multi-scale convolution kernel parameters through reparameterization method,thus enabling the model to capture more global contextual information.Finally,the discriminative gait features were extracted via feature mapping.Experiments were conducted on the outdoor datasets Gait3D and GREW,and the results show that compared with the existing state-of-the-art method GaitBase,DilatedGait improves 9.0 and 14.2 percentage points respectively in Rank-1 and mean Inverse Negative Penalty(mINP)on Gait3D and increases 11.6 and 8.8 percentage points respectively in Rank-1 and Rank-5 on GREW.It can be seen that DilatedGait overcomes the adverse effects of complex covariates and further enhances the accuracy of gait recognition in outdoor scenes.

关 键 词：步态识别 有效感受野 重参数化 空洞卷积 步态轮廓序列 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]