手势语言识别的神经网络方法

提供了一种用于人机交互（HCI）的手势语言可视化识别方法。该方法包括用于几种控制命令的手势的探测、分割、特征提取及识别，第一步的处理都用到了神经网络方法，像肤色探测、主元分析（PCA）以及在编码识别。实验结果显示正确识别率高达94％。

Gesture Recognition for Human-computer Interaction by Using Neural Networks

For the purpose of human-computer interaction(HCI),a visual approach based on gesture recognition is proposed in this paper.The technique essentially includes detection and segmentation,feature extraction,and recognition of a number of gestures which are assigned as some control commands.Each of the processing stages employs a neural network for skin-color detection,principal component analysis(PCA) as well as clustering encoding of the hand-gestures.Details of the approach and experiment results are provided.The experimental recognizing accuracy is 94 %.