基于随机擦除行人对齐网络的行人重识别方法

基于检测出的行人图像容易出现错位和深度网络容易出现过拟合现象的问题,使用行人对齐网络和随机擦除数据增强,对行人数据集进行预处理。使图像生成不同程度的遮挡,并通过仿射估计分支中的空间变换网络层将图像中的错位进行修正。裁剪背景大的部分,填补行人图像缺失的部分,从而降低网络过拟合的现象,提高网络泛化能力。Market1501、DuckMTMC-reID和CUHK03数据集上进行试验,结果表明在rank-1的值达到84%左右。将随机擦除行人对齐网络方法与其他方法进行比较,发现随机擦除行人对齐网络的行人重识别方法的试验结果要好。

Person re-identification based on random erasing pedestrian alignmentnetwork method

The detected pedestrian images were prone to misalignment and the depth network was prone to over-fitting phenomenon. Pedestrian datasets were preprocessed using pedestrian alignment networks and random erasing data enhancements. It made the images generating different levels of occlusion, and corrected the misalignment in the images by the spatial transformation network layer in the affine estimation branch. It cropped the large part of the background and filled in the missing part of the pedestrian images, which reduced the phenomenon of network over-fitting and improved the generalization ability of the network. The tests were performed on the Market1501, DuckMTMC-reID and CUHK03 datasets, which showed the value of rank-1 reached approximately 84%. Compared the methods of randomly erasing pedestrian alignment network with other methods, it was found that the test results of pedestrian recognition method for randomly erasing pedestrian alignment network were better.