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基于RGB图像的三维人手姿态估计技术综述

Review on 3D Hand Pose Estimation based on a RGB Image

  • 摘要: 由于RGB相机在虚拟现实头盔等移动计算设备中的普遍性, 基于RGB图像的三维人手姿态估计技术具有广阔的应用前景和研究价值, 近年来已成为计算机视觉领域的一个研究热点. 得益于深度学习技术的快速发展, 与之相关的三维人手姿态估计算法层出不穷. 文中回顾和总结了三维人手姿态估计技术. 首先简述了三维人手姿态估计的相关工作, 指出了其当前面临的挑战; 然后梳理了基于RGB图像的三维人手姿态估计算法, 对现有的基于参数模型方法和非参数模型方法进行了讨论, 分析了每类算法包含的技术方法以及优缺点; 之后总结了相关的三维手数据集与评价标准, 并比较了每类算法在常用数据集上的表现; 最后探讨了该技术的发展前景.
     

     

    Abstract: Due to the ubiquity of RGB cameras in mobile computing devices such as virtual reality headsets, the 3D hand pose estimation technology based on a RGB image has broad application prospects and research value, which becomes a research hotspot in the field of computer vision in recent years. Thanks to the development of deep learning technology, algorithms related to 3D hand pose estimation emerge in endlessly. This paper reviews and summarizes the 3D hand pose estimation technology. Firstly the relevant work on 3D hand pose estimation is briefly described, and the current challenges it faces are pointed out; then the algorithms of 3D hand pose estimation from a single RGB image are reviewed, and the existing model-based methods and model-free methods are discussed; then the relevant datasets and evaluation criteria are summarized; finally the development prospects of this technology are discussed.

     

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