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中文摘要：
一条新人的行动识别途径基于混乱 invariants 和关联向量机器(RVM ) 被介绍。骨骼图匹配估计的引用关节的轨道为代表人的行动的非线性的动态系统被采用。C-C 方法被用于估计延期时间并且嵌入被每条轨道重建的一个阶段空格的尺寸。然后，代表行动的某混乱 invariants 能在重建的阶段空间被捕获。最后， RVM 被用来认出行动。实验在 KTH， Weizmann 和测试并且评估建议方法的芭蕾舞人的行动数据集上被执行。实验结果证明平均识别精确性是超过 91.2% ，它验证它的有效性。
英文摘要：
A new human action recognition approach was presented based on chaotic invariants and relevance vector machines （RVM）. The trajectories of reference joints estimated by skeleton graph matching were adopted for representing the nonlinear dynamical system of human action. The C-C method was used for estimating delay time and embedding dimension of a phase space which was reconstructed by each trajectory. Then, some chaotic invariants representing action can be captured in the reconstructed phase space. Finally, RVM was used to recognize action. Experiments were performed on the KTH, Weizmann and Ballet human action datasets to test and evaluate the proposed method. The experiment results show that the average recognition accuracy is over 91.2%, which validates its effectiveness.
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