Open AccessAn Anthropometric Dimensions Measurement Method Using Multi-pose Human Images with Complex Background
Author(s) -
Yidong Chen,
Yigang Wang
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 - 10.1088/1742-6596/1335/1/012005
Subject(s) - anthropometry , computer science , matching (statistics) , artificial intelligence , ellipsoid , computer vision , pattern recognition (psychology) , mathematics , statistics , geography , archaeology , geodesy
Automatically acquire anthropometric dimensions using two-dimensional images, providing a convenient, effective and low-cost way for measuring anthropometric parameters. In the existing methods, the background and posture of the user are highly restricted, and the anthropometric dimensions obtained by using the ellipsoid model is not accurate enough. On this observation, we propose a new method for measuring the anthropometric dimensions. This method integrates the deep learning method with the deeplabv3 and openpose frameworks, and introduces the contour matching method to get anthropometric dimensions instead of using ellipsoid model. Experiments show our method can effectively dealing with the complex background and posture problems, and improving the accuracy.