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Accurate nonrigid 3D human body surface reconstruction using commodity depth sensors
Author(s) -
Lu Yao,
Zhao Shang,
Younes Naji,
Hahn James K.
Publication year - 2018
Publication title -
computer animation and virtual worlds
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.225
H-Index - 49
eISSN - 1546-427X
pISSN - 1546-4261
DOI - 10.1002/cav.1807
Subject(s) - computer science , motion capture , artificial intelligence , computer vision , body surface , surface reconstruction , 3d reconstruction , reliability (semiconductor) , match moving , surface (topology) , motion (physics) , power (physics) , physics , geometry , mathematics , quantum mechanics
In the last decade, 3D modeling techniques enjoyed a booming development in both hardware and software. High‐end hardware generates high fidelity results, but the cost is prohibitive, whereas consumer‐level devices generate plausible results for entertainment purposes but are not appropriate for medical uses. We present a cost‐effective and easy‐to‐use 3D body reconstruction system using consumer‐grade depth sensors, which provides reconstructed body shapes with a high degree of accuracy and reliability appropriate for medical applications. Our surface registration framework integrates the articulated motion assumption, global loop closure constraint, and a general as‐rigid‐as‐possible deformation model. To enhance the reconstruction quality, we propose a novel approach to accurately infer skeletal joints from anatomical data using multimodality registration. We further propose a supervised predictive model to infer the skeletal joints for arbitrary subjects independent from anatomical data reference. A rigorous validation test has been conducted on real subjects to evaluate the reconstruction accuracy and repeatability. Our system has the potential to make accurate body surface scanning systems readily available for medical professionals and the general public. The system can be used to obtain additional health data derived from 3D body shapes, such as the percentage of body fat.