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Recognition of human actions using moment based features and artificial neural networks

机译:使用基于矩的特征和人工神经网络识别人类动作

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This paper presents performance of view-based approach in automated recognition of predefined hand and gross body actions using artificial neural network. This approach represents motion by a static grey scale image template computed by collapsing the temporal components into the cumulative image-difference of frames. The seven invariant Hu moments are used as the feature vectors. The performance of the system is tested in real time using feed forward multilayer perceptron (MLP) based on back propagation.
机译:本文介绍了基于视图的方法在使用人工神经网络自动识别预定义的手和身体动作方面的性能。该方法通过静态灰度图像模板来表示运动,该静态灰度图像模板是通过将时间分量折叠为帧的累积图像差来计算的。七个不变的Hu矩用作特征向量。使用基于反向传播的前馈多层感知器(MLP)实时测试系统的性能。

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