Human gait is a proven biometric trait with applications in security for authentication and disease diagnosis. However, it is one-sided to express and interpret gait data from a single point of view, which cannot reflect multi-dimensional characteristics of gait changes. Moreover, if the gait pattern observed from other views has pathological or abnormal behavior, or has micro movement, it is not easy to be detected and thus affects the recognition rate of gait. In addition, the multi-view fusion of gait knowledge can be challenging due to the close correlation between various visual angles. Owing to the above facts, we propose a spiderweb graph neural network (SpiderNet) to solve the multi-view gait recognition problem, which connects the gait data of single view with that of other views concurrently and constructs an active graph convolutional neural network. The gait trajectory of each view is analyzed by the combination of a memory module and a capsule module, which accomplishes the multi-view feature fusion, as well as the spatio-temporal feature extraction of single view. The experimental results show that the SpiderNet is superior to fifteen state-of-the-art methods, such as random forest, long-short term memory and convolutional neural network, and achieves 98.54%, 98.77%, and 96.91% of the results on three challenging gait datasets: SDUgait, CASIA-B, and OU-MVLP.

人的步态是一种经过验证的生物特征，可用于身份验证和疾病诊断的安全性。但是，从单一的角度来表达和解释步态数据是单方面的，不能反映步态变化的多维特征。此外，如果从其他角度观察到的步态模式具有病理性或异常行为，或者具有微小的运动，则不容易被检测到，从而影响步态的识别率。另外，由于各种视角之间的紧密相关性，步态知识的多视图融合可能具有挑战性。基于以上事实，我们提出了一种蛛网图神经网络（SpiderNet）来解决多视角步态识别问题，它将单个视图的步态数据与其他视图的步态数据同时连接，并构造了一个主动图卷积神经网络。通过存储模块和胶囊模块的组合来分析每个视图的步态轨迹，从而完成多视图特征融合以及单视图的时空特征提取。实验结果表明，SpiderNet优于随机森林，长期短期记忆和卷积神经网络等十五种最新方法，分别达到98.54％，98.77％和96.91％的结果。三个具有挑战性的步态数据集：SDUgait，CASIA-B和OU-MVLP。以及单视图的时空特征提取。实验结果表明，SpiderNet优于随机森林，长期短期记忆和卷积神经网络等十五种最新方法，分别达到98.54％，98.77％和96.91％的结果。三个具有挑战性的步态数据集：SDUgait，CASIA-B和OU-MVLP。以及单视图的时空特征提取。实验结果表明，SpiderNet优于随机森林，长期短期记忆和卷积神经网络等十五种最新方法，分别达到98.54％，98.77％和96.91％的结果。三个具有挑战性的步态数据集：SDUgait，CASIA-B和OU-MVLP。