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An improved body action recognition method based on manifold learning

机译:一种基于流形学习的改进人体动作识别方法

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The body action recognition is one of the key technologies of the computer vision. As the fact that the features of body action usually reside on low dimensional manifolds embedded in a high dimensional ambient space, a new method of body action recognition based on manifold learning is proposed in this paper. In the proposed method, a Linear Local Embedding of Difference (DLLE) algorithm is applied to get the low dimensional manifolds of the images and achieve human action recognition. The result shows that the DLLE method has more advantage in time-consuming and recognition accuracy rate than the other dimensionality reduction methods. Furthermore, the experimental results demonstrated the feasibility and effectiveness of the proposed algorithm in body action recognition.
机译:身体动作识别是计算机视觉的关键技术之一。针对人体动作特征通常驻留在高维环境空间中嵌入的低维流形这一事实,提出了一种基于流形学习的人体动作识别新方法。该方法采用差分线性局部嵌入(DLLE)算法来获取图像的低维流形,并实现人体动作识别。结果表明,DLLE方法在耗时和识别准确率上比其他降维方法更具优势。此外,实验结果证明了该算法在人体动作识别中的可行性和有效性。

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