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多属性融合网络的行人重识别方法
引用本文:徐思敏,胡士强. 多属性融合网络的行人重识别方法[J]. 计算机工程与应用, 2020, 56(6): 126-132. DOI: 10.3778/j.issn.1002-8331.1811-0322
作者姓名:徐思敏  胡士强
作者单位:上海交通大学 航空航天学院,上海 200240
摘    要:针对基于视频的行人重识别中由于光照与视角变化带来的问题,提出了一种结合局域质量评估网络与行人属性特征的网络。对部分行人图像进行预处理,裁掉部分行人图像的底部;将行人分割成三段通过卷积神经网络对其进行质量评估;结合事先人工标注的行人属性标签,进行训练从而完成重识别的过程。通过学习行人的全局特征和局部特征,能够有效解决行人图像中出现的遮挡和不对齐问题,通过在三个数据集上的结果对比表明方法实现了准确率上的提升。

关 键 词:行人重识别  计算机视觉  基于视频  质量评估  属性识别  对齐

Video-Based Person Re-identification by Attributes Fusion Network
XU Simin,HU Shiqiang. Video-Based Person Re-identification by Attributes Fusion Network[J]. Computer Engineering and Applications, 2020, 56(6): 126-132. DOI: 10.3778/j.issn.1002-8331.1811-0322
Authors:XU Simin  HU Shiqiang
Affiliation:School of Aeronautics and Astronautics, Shanghai Jiao Tong University, Shanghai 200240, China
Abstract:To solve the difficulties brought by illumination and viewpoint varieties in video-based person re-identification(re-ID),a network combining the region-based quality estimation and attribute classification is proposed.Some images are pre-processed by cutting the bottom part.the images are input into convolutional network after being divided into three-part-division,which will predict the quality of each part.the network is trained by combining with the attribute labels of pedestrians to finish the whole re-ID process.Through learning global features and local features of pedestrians,the network can effectively handle occlusions and misalignments,thus achieve comparable results in three public datasets.
Keywords:person re-identification  computer vision  video-based  quality estimation  attribute classification  alignment
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