Combining 3D Interpolation, Regression, and Body Features to build 3D Human Data for Garment: An Application to Building 3D Vietnamese Female Data Model

Abstract

Modeling 3D human body is an advanced technique used in human motion analysis and garment industry. In this paper, we propose a method for forming deformation functions so that we can rebuild the 3D human body given anthropometric measurements. The advanced idea in our approach is that we split the 3D body into small parts. In that way, we can specialize different set of parameters needed to interpolate for each section. With an interpolation approach, we build a 3D human body for 593 female bodies with the corresponding body shape but require fewer input measurements than 3D laser scans.

Building 3-D Human Data Based on Handed Measurement and CNN

“…4 shows the results of errors of the method compared with other methods. Our method has errors lower than other methods, including interpolation [3], CNN [4].…”

“…4, we trained the 3-D model with 7000 iterations to save training time. The error of slices of 3-D models were calculated with the formula in [3], applied to Tabs. 2 and 3.…”

“…To calculate errors of 3-D model, we use the method in [3] to calculate perimeter base on i th slice from model, as shows in Eq. (1).…”

“…p p is the perimeter of the 3-D model slice that we collect from the hand measurements. loss = loss chamfer × w chamfer + loss edge × w edge + loss normal × w normal + loss laplacian × w laplacian (3) The error is calculated based on 3-D model after training and 3-D output model, using Eq. ( 3).…”

“…They are being applied in modern printing and scanning 3-D equipment to respond demands of building complete human models. Kieu et al [3] applied regression and interpolation to build 3-D human model. They divided the model into parts, then used Hermite interpolation to interpolate each part of the model.…”