Open AccessAutomatic measurement of anthropometric dimensions using frontal and lateral silhouettes
Author(s) -
Aslam Murtaza,
Rajbdad Fozia,
Khattak Shahid,
Azmat Shoaib
Publication year - 2017
Publication title -
iet computer vision
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.38
H-Index - 37
eISSN - 1751-9640
pISSN - 1751-9632
DOI - 10.1049/iet-cvi.2016.0406
Subject(s) - anthropometry , circumference , fiducial marker , mathematics , ellipsoid , statistics , mean absolute error , artificial intelligence , computer science , geometry , mean squared error , geodesy , geology , geography , archaeology
Anthropometric dimensions, such as lengths, heights, breadths, circumferences and their ratios are highly significant in healthcare, security, sports, clothing, tools and equipment industry. In this study, an automatic and precise method for anthropometric dimensions of human body using two‐dimensional images is proposed. The dimensions are obtained by using fiducial points that are detected from frontal and lateral views of body silhouettes. Primary anthropometric dimensions, which include heights, breadths, depths and lengths, are obtained by calculating the difference between two relevant fiducial points. The secondary dimensions: ratios are obtained directly from primary dimensions, and circumference dimensions are estimated precisely using ellipsoid model. A total of 75, i.e. 51 primary and 24 secondary dimensions are obtained, which are three times the number acquired by the state‐of‐the‐art method. The accuracy of acquired dimensions is verified by comparing it with the manual measurements by using the standard parameter of maximum allowable error. It is found that mean absolute difference of all the dimensions, obtained by the proposed method, lie within the limits of maximum allowable error. More importantly, the mean absolute difference for the majority of dimensions (20 out of 24) is significantly less for proposed method as compared with the best method in existing literature.