Super-joint and multi-modal network and behavior identification method thereof
A recognition method and super-joint technology, applied in the field of neural networks, can solve the problems of ignoring joint dependencies, unable to express dependencies with adjacent points, etc., to improve the recognition effect and improve the performance of action recognition.
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 The present invention will be further described below with reference to the accompanying drawings and embodiments. This figure is a simplified schematic diagram, and only illustrates the basic structure of the present invention in a schematic manner, so it only shows the structure related to the present invention.
 In order to evaluate the effectiveness of the method of the present invention, experiments are carried out on a public dataset based on the depth map and skeleton information; a large public dataset can provide a wider range of training data for the model, making the model stronger; in order to verify the robustness of the method of the present invention Due to the nature of the dataset, a classic small dataset is used in the selection of the dataset. Therefore, experiments are conducted on several datasets with distinct scales: UTD-MHAD and NTU-RGB+D.
 The invention is established based on the PyTorch framework, wherein the Python version is 3...
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