SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds

SHPR-Net: Deep Semantic Hand Pose Regression From Point Clouds

3-D hand pose estimation is an essential problem for human-computer interaction. Most of the existing depth-based hand pose estimation methods consume 2-D depth map or 3-D volume via 2-D/3-D convolutional neural networks. In this paper, we propose a deep semantic hand pose regression network (SHPR-N...

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Bibliographic Details
Main Authors: Xinghao Chen, Guijin Wang, Cairong Zhang, Tae-Kyun Kim, Xiangyang Ji
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Human computer interaction
hand pose estimation
deep learning
machine learning
point cloud
Online Access:https://ieeexplore.ieee.org/document/8425735/

Internet

https://ieeexplore.ieee.org/document/8425735/

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