K-SMPl : Korean body measurement data based parametric human modelK-SMPL: 한국인 체형 데이터 기반의 매개화된 인체 모델

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The Skinned Multi-Person Linear Model (SMPL) is the most widely used parametric 3D Human Model optimized and learned from CAESAR, a 3D human scanned database created with measurements from 3,800 people living in United States in the 1990s. We point out the lack of racial diversity of body types in SMPL and propose K-SMPL that better represents Korean 3D body shapes. To this end, we develop a fitting algorithm to estimate 2,773 Korean 3D body shapes from Korean body measurement data. By conducting principle component analysis to the estimated Korean body shapes, we construct K-SMPL model that can generate various Korean body shape in 3D. K-SMPL model allows to improve the fitting accuracy over SMPL with respect to the Korean body measurement data. K-SMPL model can be widely used for avatar generation and human shape fitting for Korean.
Advisors
Lee, Sung-Heeresearcher이성희researcher
Description
한국과학기술원 :문화기술대학원,
Publisher
한국과학기술원
Issue Date
2022
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 문화기술대학원, 2022.8,[iii, 22 p. :]

Keywords

Geometric modeling▼a3d human model▼abody shape▼aoptimization▼askinning; 기하학적 모델링▼a3D 인체 모델▼a최적화 기법▼a스키닝

URI
http://hdl.handle.net/10203/308305
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=1008238&flag=dissertation
Appears in Collection
GCT-Theses_Master(석사논문)
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