基于模糊L隶属函数的Bharatanatyam舞蹈手势识别

S. Saha, Lidia Ghosh, A. Konar, R. Janarthanan
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引用次数: 24

摘要

本文提出了一种基于模糊L隶属度函数的“婆罗塔纳塔姆”舞蹈手势自动识别方法。在这里,我们设计了一个三级系统。第一阶段,采用基于纹理的分割方法将舞者的手从背景中分离出来,然后利用Sobel边缘检测技术提取手的轮廓;下一步,定位边界中心点,并以此为基础计算八个空间距离。这些距离通过除最大距离值而归一化。最后,计算每个距离的模糊L隶属度值,并基于L模糊隶属度函数将未知手势与数据库中的已知手势进行匹配。该算法在运行Mat lab R011b的Intel Pentium双核处理器上,每个手势的总体准确率为85.1%,时序复杂度为2.563秒。这个简单而有效的代码对于“Bharatanatyam”舞蹈的电子学习非常有用。
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Fuzzy L Membership Function Based Hand Gesture Recognition for Bharatanatyam Dance
This paper presents a method for automatic hand gesture recognition of 'Bharatanatyam' dance using Fuzzy L membership function based approach. Here, a 3-stage system has been designed. In the first stage, the hand of the dancer from background is isolated using Texture based segmentation and thus the contour of the hand is extracted by using Sobel edge detection technique. In the next stage, centre point of the boundary is located and based on this eight spatial distances are calculated. These distances are normalized by dividing the maximum distance value. In the final stage, fuzzy L Membership values are calculated for each distance and matching of an unknown hand gesture is done with the known hand gestures from the database based on L fuzzy membership function. The proposed algorithm gives overall an accuracy of 85.1% and timing complexity is 2.563 sec in an Intel Pentium Dual Core processor running Mat lab R011b for each hand gesture. This simple yet effective code is very useful for e-learning of 'Bharatanatyam' dance.
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