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http://dx.doi.org/10.15701/kcgs.2022.28.4.1

K-SMPL: Korean Body Measurement Data Based Parametric Human Model  

Choi, Byeoli (KAIST, Graduate School of Culture and Technology)
Lee, Sung-Hee (KAIST, Graduate School of Culture and Technology)
Publication Information
Journal of the Korea Computer Graphics Society / v.28, no.4, 2022 , pp. 1-11 More about this Journal
Abstract
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.
Keywords
Geometric Modeling; 3D human model; body shape; optimization; skinning;
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Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 김용규, 김덕수-.(2021).3차원 형상 복원을 위한 점진적 점유예측 네트워크.컴퓨터그래픽스학회논문지,27(3),65-74.
2 박정호, 박상훈, 윤승현.(2020).형상 차이 기반 홀 패치의 파라미트릭블렌딩 기법.컴퓨터그래픽스학회논문지,26(3),39-48.
3 D. Anguelov, P. Srinivasan, D. Koller, S. Thrun, J. Rodgers, and J. Davis, "Scape: Shape completion and animation of people," ACM Trans. Graph., vol. 24, no. 3, p. 408-416, jul 2005. [Online]. Available: https://doi.org/10.1145/1073204. 1073207   DOI
4 G. Pons-Moll, J. Romero, N. Mahmood, and M. J. Black, "Dyna: A model of dynamic human shape in motion," ACM Trans. Graph., vol. 34, no. 4, jul 2015. [Online]. Available: https://doi.org/10.1145/2766993   DOI
5 H. Xu, E. G. Bazavan, A. Zanfir, W. T. Freeman, R. Suk- thankar, and C. Sminchisescu, "Ghum ghuml: Generative 3d human shape and articulated pose models," in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2020.
6 M. Loper, N. Mahmood, and M. J. Black, "Mosh: Motion and shape capture from sparse markers," ACM Trans. Graph., vol. 33, no. 6, nov 2014. [Online]. Available: https://doi.org/10.1145/2661229.2661273   DOI
7 M. Kocabas, N. Athanasiou, and M. J. Black, "Vibe: Video inference for human body pose and shape estimation," in Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 2020.
8 G. Pavlakos, V. Choutas, N. Ghorbani, T. Bolkart, A. A. A. Osman, D. Tzionas, and M. J. Black, "Expressive body capture: 3d hands, face, and body from a single image," in Proceedings IEEE Conf. on Computer Vision and Pattern Recognition (CVPR), June 2019, pp. 10975-10985. [Online]. Available: http://smpl-x.is.tue.mpg.de
9 Y. Chen, Z. Liu, and Z. Zhang, "Tensor-based human body modeling," in Proceedings of the IEEE Conference on Com- puter Vision and Pattern Recognition (CVPR), June 2013.
10 B. Allen, B. Curless, and Z. Popovi c, "The space of human body shapes: Reconstruction and parameterization from range scans," ACM Trans.Graph., vol. 22, no. 3, p. 587-594, 2003.   DOI
11 H. Seo, F. Cordier, and N. Magnenat-Thalmann, "Synthesiz- ing animatable body models with parameterized shape modifications," in SCA '03, 2003.
12 M. Loper, N. Mahmood, J. Romero, G. Pons-Moll, and M. J. Black, "SMPL: A skinned multi-person linear model," ACM Trans. Graphics (Proc. SIGGRAPH Asia), vol. 34, no. 6, pp. 248:1-248:16, Oct. 2015.
13 K. Robinette, S. Blackwell, H. Daanen, M. Boehmer, and S. Fleming, "Civilian American and European surface anthropometry resource(Caesar)," USA, p. 74, June 2002.
14 T. von Marcard, B. Rosenhahn, M. Black, and G. Pons-Moll, "Sparse inertial poser: Automatic 3d human pose estimation from sparse imus," Computer Graphics Forum 36(2), Proceedings of the 38th Annual Conference of the European Association for Computer Graphics (Eurographics), 2017. [Online]. Available:/brokenurl#Video
15 A. Kanazawa, M. J. Black, D. W. Jacobs, and J. Malik, "End-toend recovery of human shape and pose," in 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2018, pp. 7122-7131.
16 A. A. A. Osman, T. Bolkart, and M. J. Black, "STAR: A sparse trained articulated human body regressor," pp. 598-613.
17 H. Seo, F. Cordier, and N. Thalmann, "Synthesizing animatable body models with parameterized shape modifications," 07 2003.
18 "SizeKorea, " 2020, [Online] Available : https://sizekorea.kr/human-meas-search/3d-human-shape/intro/
19 S.Agarwal, K.Mierle, and T.C.S. Team, "Ceres Solver, " 3 2022. [Online]. Available : https://github.com/ceres-solver/ceres-solver
20 문지혜, 박상훈, 윤승현.(2022).3D Magic Wand: 하모닉 필드를 이용한 메쉬 분할 기법.컴퓨터그래픽스학회논문지,28(1),11-19.
21 H. Joo, T. Simon, and Y. Sheikh, "Total capture: A 3d deformation model for tracking faces, hands, and bodies," 06 2018, pp. 8320-8329.
22 주은정, 최명걸.(2020).정적 드레이프를 이용한 니트 옷감의 시뮬레이션 파라미터 추정.컴퓨터그래픽스학회논문지,26(5),15-24.
23 N. Mahmood, N. Ghorbani, N. F. Troje, G. Pons-Moll, and M. J. Black, "Amass: Archive of motion capture as surface shapes," 2019 IEEE/CVF International Conference on CVomputer Vision(ICCV), pp. 5441-5450, 2019.