基于联合损失胶囊网络的换衣行人重识别  

Cloth-changing person re-identification based on joint loss capsule network

作　　者：刘乾[1] 王洪元[1] 曹亮 孙博言 肖宇[2] 张继[1] LIU Qian;WANG Hongyuan;CAO Liang;SUN Boyan;XIAO Yu;ZHANG Ji(School of Computer Science and Artificial Intelligence/Aliyun School of Big Data,Changzhou University,Changzhou Jiangsu 213164,China;Design Art College,Changzhou Vocational Institute of Engineering,Changzhou Jiangsu 213164,China)

机构地区：[1]常州大学计算机与人工智能学院、阿里云大数据学院,江苏常州213164 [2]常州工程职业技术学院设计艺术学院,江苏常州213164

出　　处：《计算机应用》2021年第12期3596-3601,共6页journal of Computer Applications

基　　金：国家自然科学基金面上项目(61976028)。

摘　　要：目前的行人重识别(Re-ID)研究主要集中在短时间情形,即一个人的衣着不太可能发生改变的情况。然而现实中更常见的是长时间的情况,这时一个人有很大的机会更换衣服,Re-ID模型应该考虑这种情况。为此,研究了一种基于联合损失胶囊网络的换衣行人重识别方法。所提方法基于换衣行人重识别胶囊网络ReIDCaps,使用与传统的标量神经元相比包含更多信息的矢量胶囊,用其长度表示行人身份信息,用其方向表示行人衣着信息;采用软嵌入注意力(SEA)防止模型过拟合;使用特征稀疏表示(FSR)机制提取具有判别性的特征;增加标签平滑正则化交叉熵损失与CircleLoss的联合损失以提高模型的泛化能力和鲁棒性。在三个换衣行人重识别数据集Celeb-reID、CelebreID-light和NKUP上进行实验,实验结果表明所提方法与目前已有的Re-ID方法相比具有一定优势。Current research on Person Re-Identification(Re-ID)mainly concentrates on short-term situations with person’s clothing usually unchanged.However,more common practical cases are long-term situations,in which a person has higher possibility to change his clothes,which should be considered by Re-ID models.Therefore,a method of person re-identification with cloth changing based on joint loss capsule network was proposed.The proposed method was based on ReIDCaps,a capsule network for cloth-changing person re-identification.In the method,vector-neuron capsules that contain more information than traditional scalar neurons were used.The length of the vector-neuron capsule was used to represent the identity information of the person,and the direction of the capsule was used to represent the clothing information of the person.Soft Embedding Attention(SEA)was used to avoid the model over-fitting.Feature Sparse Representation(FSR)mechanism was adopted to extract discriminative features.The joint loss of label smoothing regularization cross-entropy loss and Circle Loss was added to improve the generalization ability and robustness of the model.Experimental results on three datasets including Celeb-reID,Celeb-reID-light and NKUP prove that the proposed method has certain advantages compared with the existing person re-identification methods.

关 键 词：换衣行人重识别 胶囊网络 矢量胶囊 标签平滑正则化交叉熵损失 CircleLoss 

分 类 号：TP391.[自动化与计算机技术—计算机应用技术]