Automatic Identification of Wrist Position in a Virtual Environment for Garment Design
Source abstract
Abstract
Abstract With the development of virtual reality, computer-aided design has shown its strength in the garment product development process. Wrist position corresponds to the styloid process of the ulna (SPU). Due the problem that the SPU position is usually not the finest position of the forearm, the wrist position identification in the 3D clothing design is quite important. This paper proposes a method that uses a fixed-step search algorithm based on existing proportion methods to determine the position of the SPU. The accuracy and efficiency of the proposed method has been validated using 100 samples by comparison with the existing methods. It can be fully applied to a virtual 3D-to-2D garment prototyping process and ensure the automation of this process.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: 3D Shape Modeling and Analysis · Textile materials and evaluations · Advanced Vision and Imaging
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Fashion Engineering , Shanghai University of Engineering Science , Shanghai , China
College of Textile and Clothing Engineering , Soochow University , Suzhou , China
References (45)
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1. Agarwal G, Koehl L, Zeng X, et al. (2009) An intelligent system for supporting design of fashion oriented personalized fabric products.
2. Baek S-Y and Lee K. (2012) Parametric human body shape modeling framework for human-centered product design. Computer-aided design 44: 56–67.10.1016/j.cad.2010.12.006 ↗
3. Bartle A, Sheffer A, Kim VG, et al. (2016) Physics-driven pattern adjustment for direct 3D garment editing. ACM Trans. Graph. 35: 50:51–50:11.10.1145/2897824.2925896 ↗
4. Camba JD, Contero M and Company P. (2016) Parametric CAD modeling: An analysis of strategies for design reusability. Computer-Aided Design 74: 18–31.10.1016/j.cad.2016.01.003 ↗
5. Chaw Hlaing E, Krzywinski S and Roedel H. (2013) Garment prototyping based on scalable virtual female bodies. International Journal of Clothing Science & Technology 25: 184–197.10.1108/09556221311300200 ↗
6. Chen M and Li X. (2011) Algorithm for extracting end feature point of 3D scanning human body model. International Congress on Image & Signal Processing.10.1109/CISP.2011.6100313 ↗
7. Chen Z, Tang K and Joneja A. (2013) Fast and automatic identification of contours for girth measurement on 3D human models with variant postures. Computer-Aided Design and Applications 10: 321–337.10.3722/cadaps.2013.321-337 ↗
8. Chen X, Tao X, Zeng X, et al. (2015) Control and optimization of human perception on virtual garment products by learning from experimental data. Knowledge-Based Systems 87: 92–101.10.1016/j.knosys.2015.05.031 ↗
9. Dong M, LIU K, HONG Y, et al. (2018) A body measurements and sensory evaluation-based classification of lower body shapes for developing customized pants design. Industria Textila 69: 111–117.10.35530/IT.069.02.1381 ↗
10. Hall WS. (1896) The changes in the proportions of the human body during the period of growth. The Journal of the Anthropological Institute of Great Britain & Ireland 25: 21–46.10.2307/2842466 ↗
11. Hong Y, Bruniaux P, Zeng X, et al. (2018a) Design and evaluation of personalized garment block for atypical morphology using the knowledge-supported virtual simulation method. Textile Research Journal 88: 1721–1734.10.1177/0040517517708537 ↗
12. Hong Y, Bruniaux P, Zeng X, et al. (2017a) Virtual reality-based collaborative design method for designing customized garment for disabled people with scoliosis. International Journal of Clothing Science 29: 226–237.10.1108/IJCST-07-2016-0077 ↗
13. Hong Y, Bruniaux P, Zeng X, et al. (2018b) Visual-simulation-based personalized garment block design method for physically disabled people with scoliosis (PDPS). Autex Research Journal 18: 35–45.10.1515/aut-2017-0001 ↗
14. Hong Y, Bruniaux P, Zhang J, et al. (2018c) Application of 3D-TO-2D garment design for atypical morphology: a design case for physically disabled people with scoliosis. Industria Textila 69: 59–64.10.35530/IT.069.01.1377 ↗
15. Hong Y, Zeng X, Bruniaux P, et al. (2018d) Garment opening position evaluation using kinesiological analysis of dressing activities: Case study of physically disabled people with scoliosis (PDPS). Textile Research Journal 88: 2303–2318.10.1177/0040517517720503 ↗
16. Hong Y, Zeng X, Bruniaux P, et al. (2017b) Interactive virtual try-on based three-dimensional garment block design for disabled people of scoliosis type. Textile Research Journal 87: 1261–1274.10.1177/0040517516651105 ↗
17. Hong Y, Zeng X, Bruniaux P, et al. (2017c) Collaborative 3D-to-2D tight-fitting garment pattern design process for scoliotic people. FIBRES & TEXTILES in Eastern Europe.10.5604/01.3001.0010.4637 ↗
18. Huang J, Kwok T-H and Zhou C. (2019) Parametric design for human body modeling by wireframe-assisted deep learning. Computer-Aided Design 108: 19–29.10.1016/j.cad.2018.10.004 ↗
19. Jian S, Peng L and Wei J. (2013) 3D Garment Design of the Computer Virtual Reality Environment. Applied Mechanics and Materials 484–485: 1041–1044.10.4028/www.scientific.net/AMM.484-485.1041 ↗
20. Jiang L, Ye J, Sun L, et al. (2019) Transferring and fitting fixed-sized garments onto bodies of various dimensions and postures. Computer-Aided Design 106: 30–42.10.1016/j.cad.2018.08.002 ↗
21. Kim S, Jeong Y, Lee Y, et al. (2010) 3D pattern development of tight-fitting dress for an asymmetrical female manikin. Fibers and Polymers 11: 142–146.10.1007/s12221-010-0142-5 ↗
22. Krzywinski S and Siegmund J. (2017) 3D Product Development for Loose-Fitting Garments Based on Parametric Human Models. IOP Conference Series: Materials Science and Engineering. IOP Publishing, 152006.10.1088/1757-899X/254/15/152006 ↗
23. Kulinska M, BRUNIAUX P, Ainamo A, et al. (2016) Virtual mannequins and garment parametrization. Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference. World Scientific, 984–989.10.1142/9789813146976_0152 ↗
24. Kobayashi M, Berger RA, Nagy L, et al. (1997) Normal kinematics of carpal bones: a three-dimensional analysis of carpal bone motion relative to the radius. Journal of Biomechanics 30: 787–793.10.1016/S0021-9290(97)00026-2 ↗
25. Krzywinski S and Siegmund J. (2017) 3D Product Development for Loose-Fitting Garments Based on Parametric Human Models. IOP Conference Series: Materials Science and Engineering. IOP Publishing, 152006.10.1088/1757-899X/254/15/152006 ↗
26. Kulinska M, BRUNIAUX P, Ainamo A, et al. (2016) Virtual mannequins and garment parametrization. Uncertainty Modelling in Knowledge Engineering and Decision Making: Proceedings of the 12th International FLINS Conference. World Scientific, 984–989.10.1142/9789813146976_0152 ↗
27. Leong I-F, Fang J-J and Tsai M-J. (2007) Automatic body feature extraction from a marker-less scanned human body. Computer-Aided Design 39: 568–582.10.1016/j.cad.2007.03.003 ↗
28. Lin Y-L and Wang M-JJ. (2011) Automated body feature extraction from 2D images. Expert Systems with Applications 38: 2585–2591.10.1016/j.eswa.2010.08.048 ↗
29. Liu Y-J, Zhang D-L and Yuen MM-F. (2010) A survey on CAD methods in 3D garment design. Computers in Industry 61: 576–593.10.1016/j.compind.2010.03.007 ↗
30. Magnenat-Thalmann N, Kevelham B, Volino P, et al. (2011) 3D Web-Based Virtual Try On of Physically Simulated Clothes. Computer-Aided Design and Applications 8: 163–174.10.3722/cadaps.2011.163-174 ↗
31. Meng Y, Wang CC and Jin X. (2012) Flexible shape control for automatic resizing of apparel products. Computer-aided design 44: 68–76.10.1016/j.cad.2010.11.008 ↗
32. Montagna G, Carvalho H, Catarino AP, et al. (2012) Ergonomic garment design for a seamless instrumented swimsuit. 4th International Conference on Applied Human Factors and Ergonomics (AHFE). USAsa Publishing, 1204–1213.
33. Ouellet S and Michaud F. (2018) Enhanced automated body feature extraction from a 2D image using anthropomorphic measures for silhouette analysis. Expert Systems with Applications 91: 270–276.10.1016/j.eswa.2017.09.006 ↗
34. Pietka E, Kaabi L, Kuo ML, et al. (1993) Feature extraction in carpal-bone analysis. IEEE Transactions on Medical Imaging 12: 44–49.10.1109/42.222665 ↗
35. Vitali, A., &and Rizzi, C. (2017). A virtual environment to emulate tailor's work. Computer-Aided Design and Applications, 14(5), 671–679.10.1080/16864360.2016.1273584 ↗
36. Wang CCL. (2005) Parameterization and parametric design of mannequins. Computer-Aided Design 37: 83–98.10.1016/j.cad.2004.05.001 ↗
37. Wang CCLC. (2013) Digital Human Body.10.1007/978-1-4471-4360-4_2 ↗
38. Wang CC, Chang TK and Yuen MM. (2003a) From laser-scanned data to feature human model: a system based on fuzzy logic concept. Computer-Aided Design 35: 241–253.10.1016/S0010-4485(01)00209-3 ↗
39. Wang CC, Wang Y, Chang TK, et al. (2003b) Virtual human modeling from photographs for garment industry. Computer-Aided Design 35: 577–589.10.1016/S0010-4485(02)00080-5 ↗
40. Wang CC, Wang Y and Yuen MM. (2003c) Feature based 3D garment design through 2D sketches. Computer-aided design 35: 659–672.10.1016/S0010-4485(02)00091-X ↗
41. Wang CC, Wang Y and Yuen MM. (2005) Design automation for customized apparel products. Computer-aided design 37: 675–691.10.1016/j.cad.2004.08.007 ↗
42. Zhang D, Liu Y, Wang J, et al. (2018) An integrated method of 3D garment design. The journal of the Textile Institute 109: 1595–1605.10.1080/00405000.2018.1436638 ↗
43. Zhang D, Wang J and Yang Y. (2014) Design 3D garments for scanned human bodies. Journal of Mechanical Science Technology 28: 2479–2487.10.1007/s12206-014-0605-5 ↗
44. Zhang Y, Wang CC and Ramani K. (2016) Optimal fitting of strain-controlled flattenable mesh surfaces. The International Journal of Advanced Manufacturing Technology 87: 2873–2887.10.1007/s00170-016-8669-2 ↗
45. Zhong Y, Jiang J, Wang Z, et al. (2011) 3D Garment Prototyping from 2D Drawings.10.1007/978-3-642-21402-8_41 ↗