| 基于自适应正则化的东北虎重识别方法 |
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| 引用本文： | 于慧伶,钱成帅.基于自适应正则化的东北虎重识别方法[J].计算机工程与应用,2022,58(8):191-197. |
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| 作者姓名： | 于慧伶 钱成帅 |
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| 作者单位： | 东北林业大学 信息与计算机工程学院，哈尔滨 150040 |
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| 摘 要： | 随着东北虎数量不断减少，识别单只老虎进而做出保护和追踪变得很有意义，故采用了一种基于局部分块和自适应L2正则化方法的东北虎重识别网络模型（part-based convolutional baseline-adaptiveL2，PCB-AL2）以解决在自然环境下东北虎重识别困难等问题。自适应L2正则化因子通过反向传播进行自适应更新，这是通过将正则化因子作为可训练的变量来实现的。针对老虎依靠身体条纹分辨的特点，采用一种双分支网络结构：局部分支和全局分支，网络依靠局部特征指导全局特征学习。实验结果表明，在ATRW数据集上与PPbM-a、PPbM-b以及PPGNet对比得出结论，在单摄像头环境下mAP达到了92.1%，跨摄像头环境下mAP达到75.1%。
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| 关 键 词： | 重识别 残差网络 自适应L2正则化 特征融合 |
Re-Identification Method of Siberian Tiger Based on Adaptive Regularization |
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| YU Huiling,QIAN Chengshuai.Re-Identification Method of Siberian Tiger Based on Adaptive Regularization[J].Computer Engineering and Applications,2022,58(8):191-197. |
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| Authors: | YU Huiling QIAN Chengshuai |
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| Affiliation: | College of Information and Computer Engineering, Northeast Forestry University, Harbin 150040, China |
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| Abstract: | As the number of Siberian tigers continues to decrease, it becomes very meaningful to identify a single tiger for protection and tracking. Therefore, a Siberian tiger re-identification network model based on local partial blocks and an adaptive L2 regularization method（part- based convolutional baseline-adaptiveL2, PCB-AL2） is adopted to solve the problem of difficulty in re-identification of Siberian tiger in natural environment. The adaptive L2 regularization factor is adaptively updated through backpropagation, which is achieved by using the regularization factor as a trainable variable. Aiming at the characteristics of tigers relying on body stripes to distinguish, a two-branch network structure is adopted：local branch and global branch. The network relies on local features to guide global feature learning. Experimental results show that comparing with PPbM-a, PPbM-b and PPGNet on the ATRW data set, it is concluded that mAP reaches 92.1% in a single-camera environment and 75.1% in a cross-camera environment. |
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| Keywords: | re-identification residual network adaptive L2 regularization characteristics of fusion |
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