基于多类特征融合的动态足迹检索方法  

Dynamic Footprint Retrieval Method Based on Multi-class Feature Fusion

作　　者：朱明[1] 骆刚 傅枭鑫 王年[2] 鲁玺龙 张艳[2] ZHU Ming;LUO Gang;FU Xiaoxin;WANG Nian;LU Xilong;ZHANG Yan(School of Integrated Circuits,Anhui University,Hefei 230601,China;School of Electronic and Information Engineering,Anhui University,Hefei 230601,China;Institute of Forensic Science,Ministry of Public Security,Beijing 100038,China)

机构地区：[1]安徽大学集成电路学院,合肥230601 [2]安徽大学电子信息工程学院,合肥230601 [3]公安部鉴定中心,北京100038

出　　处：《刑事技术》2025年第2期141-147,共7页Forensic Science and Technology

基　　金：安徽省重点研究与开发计划项目-科技合作专项-科技强警(2022k07020006);安徽高校自然科学研究重点项目(2022AH050093);安徽高校自然科学研究重大项目(KJ2021ZD0004)。

摘　　要：足迹特征作为人体的生物特征之一,在身份识别领域有着重要的地位。针对不同人之间的足迹有着相似性的问题,本文将动态足迹作为研究对象,提出了一种基于多类特征融合的动态足迹检索方法。首先,采用卷积神经网络提取动态足迹的帧级特征;然后,特征融合模块通过一个可训练的权重矩阵与帧级特征进行运算,从而得到融合后动态足迹完整的表观特征;其次,通过时空融合模块的时间聚合支路提取帧级特征内长期的时间特征,再通过正交融合的计算方法将长期的时间特征与帧级特征融合,形成时空特征;最后,将表观特征和时空特征融合进行动态足迹的检索。在200人的动态足迹数据集上与现有深度学习算法进行了对比实验,实验结果表明,该方法获得了更好的检索效果,其中Rank1和mAP分别为85.39%、55.28%。Footprint features,as one of the biological features of the human body,play an important role in the fi eld of personal identifi cation.At present,most research on footprint recognition focuses on footprint images as experimental data,using deep learning algorithms as the foundation and relying on auxiliary algorithms to complete high-precision footprint recognition tasks.However,there is a problem with models built on footprint images.Due to the similarity of footprints of different people,as the number of samples increases,the differences between the features of footprints of different people will continue to decrease,leading to an increasing false detection rate of the model.In order to reduce the interference of similarity between footprints on model recognition ability,this paper takes dynamic footprints as the research object and proposes a dynamic footprint retrieval method based on multi-class feature fusion.The proposed method uses a spatiotemporal fusion module to integrate the spatio-temporal information of footprints,so that the footprint recognition method is not limited to the apparent information of footprints.Firstly,the convolutional neural network is used to extract the frame level features of dynamic footsteps,and then the feature fusion module calculates the complete apparent features of the fused dynamic footprints through a trainable weight matrix and frame level features.Secondly,the temporal aggregation branch of the spatio-temporal feature fusion module is used to extract long-term temporal features within frame level features,and then the long-term temporal features are fused with frame level features through orthogonal fusion calculation method to form spatio-temporal features.Finally,the visual features and spatio-temporal features are fused for dynamic footprint retrieval.A comparative experiment is conducted on a dynamic footprint dataset of 200 people with existing deep learning algorithms,and the experimental results shows that this method achieved better performance,with Rank1 and

关 键 词：足迹检索 特征融合模块 时空特征融合模块 动态足迹 深度学习 神经网络 图像检索 

分 类 号：DF794.1[政治法律—诉讼法学]