Four-direction traffic police gesture recognition method based on time sequence linear human body skin model and graph convolutional network
The invention discloses a four-direction traffic police gesture recognition method based on a time sequence linear human body skin model and a graph convolutional network, and belongs to the field of electronic information. According to the method, a power tree of traffic police command gestures is...
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Format | Patent |
Language | Chinese English |
Published |
03.03.2023
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Abstract | The invention discloses a four-direction traffic police gesture recognition method based on a time sequence linear human body skin model and a graph convolutional network, and belongs to the field of electronic information. According to the method, a power tree of traffic police command gestures is reconstructed by using a sequential linear human body skin model (SMPL), and a traffic police gesture sequential dynamic graph model is constructed according to time context information. Secondly, for the problem that an existing graph structure division strategy is limited, a graph convolution kernel label division strategy (RHPS) based on the relative height is provided, and a graph convolution network (RHGCN) based on the relative height is designed; and finally, fusing the RHGCN and a spatial domain average predictor (SMP) design to realize a four-direction traffic police gesture recognizer MTPGR based on monocular vision. The task requirement of four-direction traffic police gesture recognition is effectively |
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AbstractList | The invention discloses a four-direction traffic police gesture recognition method based on a time sequence linear human body skin model and a graph convolutional network, and belongs to the field of electronic information. According to the method, a power tree of traffic police command gestures is reconstructed by using a sequential linear human body skin model (SMPL), and a traffic police gesture sequential dynamic graph model is constructed according to time context information. Secondly, for the problem that an existing graph structure division strategy is limited, a graph convolution kernel label division strategy (RHPS) based on the relative height is provided, and a graph convolution network (RHGCN) based on the relative height is designed; and finally, fusing the RHGCN and a spatial domain average predictor (SMP) design to realize a four-direction traffic police gesture recognizer MTPGR based on monocular vision. The task requirement of four-direction traffic police gesture recognition is effectively |
Author | ZHANG CHENG LYU MENGFEI HE JIAN XIONG ZHEBO |
Author_xml | – fullname: ZHANG CHENG – fullname: HE JIAN – fullname: LYU MENGFEI – fullname: XIONG ZHEBO |
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DocumentTitleAlternate | 基于时序线性人体蒙皮模型和图卷积网络的四方向交警手势识别方法 |
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Snippet | The invention discloses a four-direction traffic police gesture recognition method based on a time sequence linear human body skin model and a graph... |
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Title | Four-direction traffic police gesture recognition method based on time sequence linear human body skin model and graph convolutional network |
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