Open AccessFast 3D Body Measurement Based on Multi-directional Point Cloud Piecing
Author(s) -
Yan Wan,
Jianpeng Jiang,
Jinghua Fan,
Min Liu,
Yingbin Zhao,
Li Yao
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 - 10.1088/1742-6596/1237/2/022160
Subject(s) - point cloud , waist , curve fitting , point (geometry) , computer science , circumference , function (biology) , algorithm , computer vision , mathematics , geometry , medicine , machine learning , evolutionary biology , biology , obesity
In order to realize fast, accurate and device-lightweight 3D body measurement, this paper proposes a quick measurement scheme which obtains measurement results by combining multi-directional human point cloud data. In this paper, the depth camera captures the point cloud data in front, side and rear of the human body, and combine the point cloud data with the skeleton point data provided by the depth camera somatosensory function. Taking the measurement of waist circumference as an example, the method of extracting the point cloud data of the waist is described. The curve equation of the waist curve is obtained by polynomial curve fitting with the discrete points. Finally, the length of the waist curve is calculated by the integral method. The measurement results are satisfactory.