一种基于数据手套的动态手势识别方法

2017 International Conference on Virtual Reality and Visualization (ICVRV) Pub Date : 2017-10-01 DOI:10.1109/ICVRV.2017.00018

Xiaopei Guo, Zhiquan Feng, Changsheng Ai, Yingjun Li, Jun Wei, Xiaohui Yang, Kaiyun Sun

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引用次数: 3

摘要

手势识别的正确性和鲁棒性对后续操作有重要影响。本文提出了一种利用数据手套获取手指关节角度变化数据的算法，然后将数据拟合到曲线上，计算曲线与曲线之间的豪斯多夫距离，进行动态手势识别。实验结果表明，当手势分类数为10时，该方法的识别率可达98%。该算法计算复杂度低，效率高，可以保证手势识别的正确性和鲁棒性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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A Novel Method for Data Glove-Based Dynamic Gesture Recognition

The correctness and robustness of gesture recognition have a significant effect on subsequent operations. In this paper, an algorithm is proposed to obtain angle change data of finger joints by means of data glove, and then the process of dynamic gesture recognition is carried out by fitting the data to curves and calculating the Hausdorff distance between them. The experimental results show that the recognition rate of the method can reach 98% when the number of gesture categories are ten. The algorithm has low computational complexity and high efficiency, which can guarantee the correctness and robustness of gesture recognition.

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2017 International Conference on Virtual Reality and Visualization (ICVRV)

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