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Person identification from actions based on Artificial Neural Networks

机译:基于人工神经网络的动作识别

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In this paper, we propose a person identification method exploiting human motion information. A Self Organizing Neural Network is employed in order to determine a topographic map of representative human body poses. Fuzzy Vector Quantization is applied to the human body poses appearing in a video in order to obtain a compact video representation, that will be used for person identification and action recognition. Two feedforward Artificial Neural Networks are trained to recognize the person ID and action class labels of a given test action video. Network outputs combination, based on another feedforward network, is performed in the case of multiple cameras used in the training and identification phases. Experimental results on two publicly available databases evaluate the performance of the proposed person identification approach.
机译:在本文中,我们提出了一种利用人体运动信息的人识别方法。为了确定代表性人体姿势的地形图,使用了自组织神经网络。模糊矢量量化应用于视频中出现的人体姿势,以获得紧凑的视频表示形式,将其用于人员识别和动作识别。经过训练的两个前馈人工神经网络可以识别给定测试动作视频的人员ID和动作类别标签。在训练和识别阶段使用多个摄像机的情况下,将基于另一个前馈网络执行网络输出组合。在两个公共数据库上的实验结果评估了所提出的人员识别方法的性能。

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