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首页> 外文期刊>Artificial Intelligence in Engineering >3D arm movement recognition using syntactic pattern recognition
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3D arm movement recognition using syntactic pattern recognition

机译:使用句法模式识别的3D手臂运动识别

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摘要

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.
机译:基于手势的应用广泛,从直接操作界面到聋人的助听器。识别手势的关键点在于,它需要强大的计算能力才能处理时空模式。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手臂运动。我们从输入模式中提取素数模式。然后通过确定哪种可能的手臂运动可以产生主要模式序列来完成分类。进行实验以证实该方法的有效性。

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