Open AccessResearch on Somatosensory Interaction Based on Convolutional Neural Network
Author(s) -
Hui Tang,
Qing Wang,
Hong Chen,
Hao Guo
Publication year - 2019
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1237/3/032019
Subject(s) - artificial intelligence , computer science , computer vision , convolutional neural network , somatosensory system , feature (linguistics) , pattern recognition (psychology) , residual , human body , psychology , algorithm , neuroscience , linguistics , philosophy
Somatosensory interaction is an important part of human-computer interaction. The core of somatosensory interaction must accurately obtain the 3D spatial information of the human body. This article uses an RGBD camera to acquire both color and depth images. We Perform 2D human pose estimation in color images using hourglass network with residual structure. At the same time, we use the sparse feature points to align the color map with the depth map in order to accurately map the detection results in color images to the corresponding depth images. The experimental results show that this method can accurately and quickly obtain the 3-dimensional posture information of the human body, which is an important guarantee for somatosensory interaction.