3D anthropometric algorithms for the estimation of measurements required for specialized garment design

Abstract

A complete guide for anthropometric data acquisition from a 3D scan is introduced.A comparison with manual measurements and a state-of-the-art system is presented.Common 3D anthropometry problems and origins are discussed. 3D anthropometry is key to the automation and facilitation of tedious, costly, and time-consuming traditional anthropometric tasks such as the size designation of a specialized garment.This article provides a short survey of 3D anthropometry in garment design. The results show that due to a lack of detailed, complex analyses of the entire anthropometric procedure from a raw body scan to a set of anthropometric measurements, there was a need to prepare and describe a comprehensive system from scratch. The aim of this article is, therefore, to present the developed 3D anthropometric solution, along with fully documented algorithms for automatic measurement extraction from a 3D body scan, results of tests, and its validation.Based on a list of desired measurements, a general processing path was prepared. Its methods are described in detail, including algorithms for body segmentation, characteristic points localization (body landmarking), and final specific measurements of girth, arc, and linear lengths (widths and heights). Furthermore, pseudo-code for the algorithms and 3D description of the characteristic points is included in Appendices A and B. The scanning procedure and posture recommendations are explained. Finally, test results and analyses are presented.The validation dataset consisted of 40 subjects (21 male and 19 female volunteers) aged between 25 and 55 years, weighing from 55 to 105kg and 150 to 205cm tall. Each of the subjects was measured once manually and three times automatically by both our system and the Human Solutions system to check the repeatability of the consecutive measurements. The performance of the 3D anthropometric system was evaluated by comparing its output with the manual measurements treated as the best possible ground truth. The output was also compared with the results from a leading commercial 3D anthropometric scanning solution provided by Human Solutions GmbH. The accuracy of both systems was measured using both the relative percent and millimeter difference error. Consistency and absolute agreement between systems and manual measurements were evaluated using the Intraclass Correlation Coefficient (ICC) method. Finally, comparability between the manual and automated measurements was assessed according to ISO 20685. It appeared that for our system, only 5 out of 26 measurement types passed the highly demanding test from ISO 20685 and for the Human Solutions system, 3 out of 26 types passed the test. However, most of the accuracy, consistency, and absolute agreement results appeared to be on a satisfactory level according to garment design experts taking part in the project. Girth measurements were characterized by the highest degree of consistency and absolute agreement, while arc length measurements were still acceptable, but least satisfactory. The degrees of general consistency and absolute agreement between our system and manual measurements fell into the excellent interval of the ICC practical significance measure. These tests also showed high inter-rater agreement between the proposed system and the commercial one (the Human Solutions product). It appeared that the current version of the system can provide results relatively close to those of the state-of-the-art solution. However the system still needs further development and tests on a larger population, as it is not completely free of errors, particularly those resulting from improper body landmarking and inconsistent posture.