While 3D body models have been vastly studied in the last decade, acquiring accurate models from the sparse information about the subject and few computational resources is still a main open challenge. In this paper, we propose a methodology for finding the most relevant anthropometric measurements and facial shape features for the prediction of the shape of an arbitrary segmented body part. For the evaluation, we selected 12 features that are easy to obtain or measure including age, gender, weight and height; and augmented them with shape parameters extracted from 3D facial scans.
New developments in the field of technology have led to the use of scanners in order to obtain anthropometric measurements. As a matter of fact, anthropometry finds its roots in the seventeenth century, currently its usage has been strengthened by the employment of scanners. 3D whole-body scanners allow to collect reliable data and to visualise the exact human body shape. Thus, this paper aims at exploring the combination of these topics, anthropometry and scan, through an innovative tool, the scientometrics analysis.
Human body metrics have become a significant source of product innovation to industries where consumer fit, comfort and ergonomic considerations are key factors. This is especially the case for fashion (e.g. footwear or apparel), health (e.g. orthotics or prosthetics), transport and aerospace (e.g. seats or human-machine interfaces), and safety (e.g. protective equipment or workstations) among others. Large-scale databases of 3D body scans are today a research tool for most of the leading companies of those sectors. In the last few years, new emerging businesses using 3D body data (e.g.
In this narrative review several articles that explain the application of 3D Body Scanner were analyzed. Among all published articles in the last 10
years only 14 met the inclusion criteria. There are several fields of application of this technology: Body shape and posture analysis, pediatrics, metrical analysis,
and forensic medicine. The results indicate that 3D Body Scanner is a promising technology that could help clinicians and researchers to improve their work both
in term of quality and time saving.
Blockchain is widely regarded as a breakthrough innovation that may have a profound impact on the economy and society, of a magnitude comparable to the effects of the introduction of the Internet itself. In essence, a blockchain is a decentralized peer-to-peer network with no central authority figure, which adds information to the distributed database by collectively validating the accuracy of data. Since each node of the network participates in the review and confirmation of the new information before being accepted, the need for a trustworthy intermediary is eliminated.
This paper presents partial results of a larger validation study of different Data-driven 3D Reconstruction (D3DR) technologies developed by IBV to create watertight 3D human models from measurements (1D3D), 2D images (2D3D) or raw scans (3D3D). This study quantifies the reliability (Standard Error of Measurement, SEM; Mean Absolute Deviation, MAD; Intra-class Correlation Coefficient, ICC; and Coefficient of Variation, CV) of body measurements taken on human subjects.