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

The validation dataset consisted of 40 subjects (21 male and 19 female volunteers) aged between 25 and 55 years, weighing from 55 to 105 kg and 150 to 205 cm 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.