3D arm movement recognition using syntactic pattern recognition

Mu-Chun Su, Yi-Yuan Chen, Kuo-Hua Wang, Chee-Yuen Tew, Hai Huang
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引用次数: 7

Abstract

Gesture-based applications widely range from direct manipulation interfaces to speaking aids for the deaf. The crucial point in recognizing gestures is that it requires great computational power to deal with spatio-temporal patterns. In this paper, a syntactic approach is proposed to provide a simple recognition algorithm. In order to verify the proposed method, we apply it to recognize 3D arm movements involved in the Taiwanese Sign Language. We extract prime patterns from the input patterns. The classification is then accomplished by deciding which one of possible arm movements can produce the sequence of primary patterns. Experiments were conducted to confirm the effectiveness of the method.

基于句法模式识别的三维手臂运动识别
基于手势的应用范围很广,从直接操作界面到聋哑人的语音辅助。识别手势的关键在于,它需要强大的计算能力来处理时空模式。本文提出了一种语法方法来提供一种简单的识别算法。为了验证所提出的方法,我们将其应用于识别台湾手语中涉及的3D手臂动作。我们从输入模式中提取素数模式。然后通过确定哪一种可能的手臂运动可以产生主要模式序列来完成分类。通过实验验证了该方法的有效性。
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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