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Application of support vector machine algorithm based gesture recognition technology in human-computer interaction

机译:基于支持向量机算法的手势识别技术在人机交互中的应用

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Gesture recognition technology is an important part of human-computer interaction. This study focused on the application of support vector machine (SVM) in gesture recognition. The gesture image was segmented by YCgCr color space based skin color segmentation method. Then four Hu invariant moments and the ratio of area to circumference of gesture were taken as eigenvalues to?extract gesture features. Finally, SVM was used for recognition. It was found that the proposed method had good performance in gesture recognition and could segment the collected images accurately. The recognition rate of Hu invariant moments based SVM algorithm reached 99.2% in the recognition of the six gestures designed in this study, which was 9.2% higher than that of HMM algorithm. The proposed method is reliable and feasible and can achieve simple man-machine interaction.
机译:手势识别技术是人机交互的重要组成部分。这项研究集中在支持向量机(SVM)在手势识别中的应用。通过基于YCgCr颜色空间的肤色分割方法对手势图像进行分割。然后将四个Hu不变矩以及手势的面积与周长之比作为特征值提取手势特征。最后,将SVM用于识别。结果表明,该方法在手势识别中具有良好的性能,可以准确地对采集到的图像进行分割。在本研究设计的六个手势识别中,基于Hu不变矩的SVM算法的识别率达到99.2%,比HMM算法高9.2%。所提出的方法可靠可行,可以实现简单的人机交互。

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