Posture-Invariant Three Dimensional Human Hand Statistical Shape Model
نویسندگان
چکیده
Abstract A high-fidelity digital representation of (part of) the human body is a key enabler for integrating humans in twin. Among different parts body, building model hand can be challenging task due to posture deviations among collected scans. In this article, we proposed invariant statistical shape (SSM) based on 59 3D scans hands. First, were spatially aligned using Möbius sphere-based algorithm. An articulated skeleton, which contains 20 bone segments and 16 joints, was embedded each scan. Then, all same skeleton linear blend skinning (LBS) Three methods, i.e., principal component analysis (PCA), kernel-PCA (KPCA) with kernel functions, independent (ICA), evaluated construction SSMs regarding compactness, generalization ability, specificity. The PCA-based SSM selected, where components used as parameters model. Results leave-one-out validation indicate that able fit given scan at an accuracy 1.21 ± 0.14 mm. Experiment results also indicated outperforms built without correction. It concluded correction approach effectively improve therefore enables its wide usage human-integrated twin applications.
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ژورنال
عنوان ژورنال: Journal of Computing and Information Science in Engineering
سال: 2021
ISSN: ['1530-9827', '1944-7078']
DOI: https://doi.org/10.1115/1.4049445