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Unmanned Aerial Vehicle Interactive Apparatus and Method Based on Deep Learning Posture Estimation

机译:基于深度学习姿态估计的无人机交互装置和方法

摘要

An unmanned aerial vehicle interactive apparatus based on a deep learning posture estimation is provided. The apparatus (10) comprises: a shooting unit (11) for shooting an object video; a key frame extraction unit (12) for extracting a key frame image relating to an object from the shot object video; a posture estimation unit (13) for recognizing an object posture with respect to the key frame image based on an image recognition algorithm of a deep convolutional neural network; and an unmanned aerial vehicle operation control unit (14) for converting the recognized object posture into a control instruction so as to control the operation of the unmanned aerial vehicle. A human posture estimation is used to control the unmanned aerial vehicle conveniently. Moreover, in the key frame extraction and posture estimation, faster and more accurate results can be obtained by using the deep convolution neural network algorithm.
机译:提供了一种基于深度学习姿势估计的无人机交互设备。装置( 10 )包括:用于拍摄对象视频的拍摄单元( 11 );以及关键帧提取单元( 12 ),用于从拍摄的对象视频中提取与对象有关的关键帧图像;姿势估计单元( 13 ),用于基于深度卷积神经网络的图像识别算法来识别关键帧图像的物体姿势;无人飞行器操作控制单元( 14 ),用于将识别出的物体姿势转换为控制指令,以控制无人飞行器的操作。人体姿势估计被用来方便地控制无人机。此外,在关键帧提取和姿势估计中,使用深度卷积神经网络算法可以获得更快,更准确的结果。

著录项

  • 公开/公告号US2018186452A1

    专利类型

  • 公开/公告日2018-07-05

    原文格式PDF

  • 申请/专利权人 BEIJING DEEPHI TECHNOLOGY CO. LTD.;

    申请/专利号US201815860772

  • 发明设计人 LU TIAN;YI SHAN;SONG YAO;

    申请日2018-01-03

  • 分类号B64C39/02;G05D1;G06K9/46;G06T7/70;G06T11/60;G06T5/20;

  • 国家 US

  • 入库时间 2022-08-21 12:57:38

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