一种针对复杂场景的行人再识别优化方法

A Pedestrian Re-identification Optimization Method for Complex Scenes

针对室外场景中,因摄像头角度不统一、室外光照多变等因素导致行人难识别的问题,提出一种针对复杂场景的行人再识别优化方法。通过在ResNet的浅层嵌入实例-批归一化层和空间变换网络,引入Mish激活函数,构建改进的ResNet-50特征提取骨干网络,建立面向复杂场景的行人再识别模型。经在MSMT17数据集上验证,rank-1和mAP分别达到79.8%、58.5%,说明了该算法的有效性。

Aiming at the problem that it is difficult to recognize pedestrians in outdoor scenes due to different camera angles and changeable outdoor lighting,an optimization method for pedestrian re-identification in complex scenes is proposed.By embedding theinstance-batch normalization layer and spatial transformer networkin the shallow layer of ResNet,introducing the mish activation function,building an improved ResNet-50 feature extraction backbone network,and establishing a pedestrian re-identification model for complex environment.Verified on MSMT17 data set,rank-1 and map reach 79.8%and 58.5%respectively,which shows the effectiveness of the algorithm.