论文标题
基于骨架的动作识别
Spatio-Temporal Dual Affine Differential Invariant for Skeleton-based Action Recognition
论文作者
论文摘要
人类骨骼的动力学有重要信息，以实现行动识别任务。相应关节的轨迹之间的相似性是相同作用的一个特征，而这种相似性可能会受到某些变形，这些变形可以建模为空间和时间仿射变换的组合。在这项工作中，我们提出了一个新颖的功能，称为时空双伴侣差异不变（STDADI）。此外，为了提高神经网络的概括能力，提出了一种通道增强方法。在大型动作识别数据集NTU-RGB+D及其扩展版本NTU-RGB+D 120上，它比以前的最新方法实现了显着的改进。
The dynamics of human skeletons have significant information for the task of action recognition. The similarity between trajectories of corresponding joints is an indicating feature of the same action, while this similarity may subject to some distortions that can be modeled as the combination of spatial and temporal affine transformations. In this work, we propose a novel feature called spatio-temporal dual affine differential invariant (STDADI). Furthermore, in order to improve the generalization ability of neural networks, a channel augmentation method is proposed. On the large scale action recognition dataset NTU-RGB+D, and its extended version NTU-RGB+D 120, it achieves remarkable improvements over previous state-of-the-art methods.
