The accuracy of modern digital human models has led to the development of human simulation engines capable of performing a complex analysis of the biometrics and kinematics / dynamics of a digital model. While the capabilities of these simulations have seen much progress in recent years, they are hindered by a fundamental limitation regarding the diversity of the models compatible with the simulation engine, which in turn results in a reduction in the scope of the applications available to the simulation. This is typically due to the necessary implementation of a musculoskeletal structure within the model, as well as the inherent mass and inertial data that accompany it. As a result a significant amount of time and expertise is required to make a digital human model compatible with the simulation. In this research I present a solution to this limitation by outlining a process to develop a set of mutually compatible human models that spans the range of feasible body shapes and allows for a “free” exploration of body shape within the shape manifold. Additionally, a method is presented to represent the human body shapes with a reduction of dimensionality, via a spectral shape descriptor, that enables a statistical analysis that is both more computationally efficient and anthropometrically accurate than traditional methods. This statistical analysis is then used to develop a set of representative models that succinctly represent the full scope of human body shapes across the population, with applications reaching beyond the research-oriented simulations into commercial human-centered product design and digital modeling.
Identifer | oai:union.ndltd.org:uiowa.edu/oai:ir.uiowa.edu:etd-6483 |
Date | 01 May 2016 |
Creators | Mate, Samuel Spicer |
Contributors | Baek, Stephen |
Publisher | University of Iowa |
Source Sets | University of Iowa |
Language | English |
Detected Language | English |
Type | thesis |
Format | application/pdf |
Source | Theses and Dissertations |
Rights | Copyright 2016 Samuel Spicer Mate |
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