Human action recognition plays an important role in modern intelligent systems, such as human–computer interaction (HCI), sport analysis, and somatosensory game. Compared with conventional 2-D based human action analysis, using Kinect sensor can obtain depth information of human action, which is significant for human action recognition. In this paper, we propose a joint angle sequence model for recognizing human actions, where depth images are acquired by using Kinect sensor. We design an improved DTW method to improve the matching accuracy. Comprehensive experiments show the effectiveness and robustness of our proposed method.

中文翻译：

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使用Kinect学习骨骼信息以进行人体动作分析

人体动作识别在现代智能系统中扮演重要角色，例如人机交互（HCI），运动分析和体感游戏。与传统的基于二维的人体动作分析相比，使用Kinect传感器可以获得人体动作的深度信息，这对于人体动作识别具有重要意义。在本文中，我们提出了一种用于识别人类动作的关节角度序列模型，其中使用Kinect传感器获取深度图像。我们设计了一种改进的DTW方法来提高匹配精度。综合实验证明了我们提出的方法的有效性和鲁棒性。