开发用于人体运动分析的深度学习神经网络

2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC) Pub Date : 2017-09-01 DOI:10.1109/RPC.2017.8168071

V. Golodov, Anna Zavei-Boroda, Sergey Ivanov, K. Nikolskaya

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引用次数: 6

摘要

本文根据荣格的经验类型论，探讨了感知/直觉亚型的识别问题。使用记录人类运动的视频片段作为输入数据。初步处理包括对视频片段的帧进行处理的算法，以选择图像的骨架，然后将其作为输入数据用于深度学习的人工神经网络。假设了神经网络的拓扑结构。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Development of a deep learning neural network for human movements analysis

The article deals with the recognition of the sensor/intuit subtype according to the empirical typology of K.G. Jung. A video fragment with the recording of human movements is used as the input data. Preliminary processing includes algorithms for processing the frames of the video fragment for selecting the skeleton of the image and then using it as input data to an artificial neural network of deep learning. The topology of the neural network is supposed.

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2017 Second Russia and Pacific Conference on Computer Technology and Applications (RPC)

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