Applying Kinect on the Development of a Customized 3D Mannequin
In the field of fashion design, 3D Mannequin is a kind
of assisting tool which could rapidly realize the design concepts.
While the concept of 3D Mannequin is applied to the computer added
fashion design, it will connect with the development and the
application of design platform and system. Thus, the situation
mentioned above revealed a truth that it is very critical to develop a
module of 3D Mannequin which would correspond with the necessity
of fashion design. This research proposes a concrete plan that
developing and constructing a system of 3D Mannequin with Kinect.
In the content, ergonomic measurements of objective human features
could be attained real-time through the implement with depth camera
of Kinect, and then the mesh morphing can be implemented through
transformed the locations of the control-points on the model by
inputting those ergonomic data to get an exclusive 3D mannequin
model. In the proposed methodology, after the scanned points from the
Kinect are revised for accuracy and smoothening, a complete human
feature would be reconstructed by the ICP algorithm with the method
of image processing. Also, the objective human feature could be
recognized to analyze and get real measurements. Furthermore, the
data of ergonomic measurements could be applied to shape morphing
for the division of 3D Mannequin reconstructed by feature curves. Due
to a standardized and customer-oriented 3D Mannequin would be
generated by the implement of subdivision, the research could be
applied to the fashion design or the presentation and display of 3D
virtual clothes. In order to examine the practicality of research
structure, a system of 3D Mannequin would be constructed with JAVA
program in this study. Through the revision of experiments the
practicability-contained research result would come out.
[1] C. K. Au, and Y. S. Ma, “Garment pattern definition, development and
application with associative feature approach,” Computers in Industry,
vol.61, pp.524-531, 2010.
[2] C. K. Au, and M. M. F. Yuen, “A semantic feature language for
sculptured object modeling,” Computer-Aided Design, vol.32, pp.
63-74,2000.
[3] S. M. Kim, and T. J. Kang, “Garment pattern generation from body scan
data,” Computer-Aided Design, vol.35, pp. 611-618, 2002.
[4] C. K. Au, and M. M. F. Yuen, “Feature-based reverse engineering of
mannequin for garment design,” Computer-Aided Design, vol.31, pp.
751-759,1999.
[5] J. McCartney, B. K. Hinds, and K. W. Chong, “Pattern flattening for
orthotropic materials,” Computer-Aided Design, vol.37, pp. 631-644,
2005.
[6] C. C. L. Wang, T. K. K. Chang, and M.M.F. Yuen, “From laser-scanned
data to feature human model: a system based on fuzzy logic concept,”
Computer-Aided Design, vol.35, pp. 241-253, 2003.
[7] C. C. L. Wang, Y. Wang, T. K. K. Chang, and M. M. F. Yuen, “Virtual
human modeling from photographs for garment industry,”
Computer-Aided Design, vol.35, pp. 577-589, 2003.
[8] C. C. L. Wang, Y. Wang, and M. M. F. Yuen, “Design automation for
customized apparel products,” Computer-Aided Design, vol.37, pp.
83-98, 2005.
[9] C. C. L. Wang, Y. Wang, and M. M. F. Yuen, “Feature based 3D garment
design through 2D sketches,” Computer-Aided Design, vol.35, pp.
659-672, 2002.
[10] J. Wang, G. Lu, W. Li, L. Chen, and Y. Sakaguti, “Interactive 3D garment
design with constrained contour curves and style curves,”
Computer-Aided Design, vol.41, pp. 614-625, 2009.
[11] D. L Son et al., Multi-finger interactions with papers on augmented
tabletops. In Proc. 3rd International Conference on Tangible and
Embedded Interaction,2009 ,pp. 267-274.
[12] J. Taylor et al, “The vitruvian manifold: inferring dense correspondences
for one-shot human pose estimation,” Microsoft Research, 2012.
[13] S. Izadi et al., Kinect Fusion: Real-time 3D reconstruction and interaction
using a moving depth camera. in Proc. 24th Annu. ACM symposium on
User interface software and technology,2011,pp. 559-568.
[14] R. A. Newcombe et al., Kinect Fusion: Real-time dense surface mapping
and tracking. In Proc. Mixed and Augmented Reality (ISMAR), 2011
10th IEEE International Symposium on, 2011, pp.127-136.
[15] W. D. Ueng, Lai JY and Doong JL. “Sweep-surface reconstruction from
three-dimensional measured data,” Computer-Aided Design, vol.30, pp.
791-805, 1998.
[16] P. J. Besl, and N. D. Mckay, “A method for registration of 3D shapes,”
IEEE Trans. Pattern Anal. Mach. Intell., vol.14, pp. 239-256, 1992.
[17] S. Rusinkiewicz, and M. Levoy, Efficient variants of the ICP algorithm.
In Proc. 3D Digital Imaging and Modeling, Int. Conf. on, 2001.
[18] S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model
acquisition,” ACM Trans. Graph., 2002.
[19] B. Huhle, T. Schairer, P. Jenke, and W. StraBer, “Fusion of range and
color images for denoising and resolution enhancement with a non-local
filter,” Computer Vision and Image Understanding, vol.114, pp.
1336-1345, 2010.
[20] S. W. Hsiao, and J. C. Chuang, “A Reverse Engineering Based Approach
for Product Form Design,” Design Studies, vol.24, pp. 155-171, 2003.
[21] K. C. Hui, and Y. Li, “A feature-based shape blending technique for
Industrial design,” Computer-Aided Design, vol.10, pp. 823-834, 1998.
[22] H. Q. Huang et al. “Block pattern generateon: From parameterzing human
bodies to fit feature-aligned and flattenable 3D garments,” Computers in
Industry, vol.63, pp. 680-691, 2012.
[23] J. Li, and G. Lu, “Customizing 3D garments based on volume
deformation,” Computers in Industry, vol.62, pp. 693-707, 2011.
[24] W. Ma, “Subdivision surface for CAD – an overview,” Computer-Aided
Design, vol.37, pp. 693-709, 2005.
[25] Y. Ke, S. Fan, W. Zhu, A. Li, F. Liu, and X. Shi, “Feature-based reverse
modeling strategies,” Computer-Aided Design, vol.38, pp. 485-506,
2006.
[26] Y. Ke, W. Zhu, F. Liu, X. Shi, “Constrained fitting for 2D profile-based
reverse modeling,” Computer-Aided Design, vol.38, pp. 101-114, 2006.
[27] J. Li, and G. Lu, “Customizing 3D garments based on volume
deformation,” Computers in Industry, vol. 62, pp. 693-707, 2011.
[1] C. K. Au, and Y. S. Ma, “Garment pattern definition, development and
application with associative feature approach,” Computers in Industry,
vol.61, pp.524-531, 2010.
[2] C. K. Au, and M. M. F. Yuen, “A semantic feature language for
sculptured object modeling,” Computer-Aided Design, vol.32, pp.
63-74,2000.
[3] S. M. Kim, and T. J. Kang, “Garment pattern generation from body scan
data,” Computer-Aided Design, vol.35, pp. 611-618, 2002.
[4] C. K. Au, and M. M. F. Yuen, “Feature-based reverse engineering of
mannequin for garment design,” Computer-Aided Design, vol.31, pp.
751-759,1999.
[5] J. McCartney, B. K. Hinds, and K. W. Chong, “Pattern flattening for
orthotropic materials,” Computer-Aided Design, vol.37, pp. 631-644,
2005.
[6] C. C. L. Wang, T. K. K. Chang, and M.M.F. Yuen, “From laser-scanned
data to feature human model: a system based on fuzzy logic concept,”
Computer-Aided Design, vol.35, pp. 241-253, 2003.
[7] C. C. L. Wang, Y. Wang, T. K. K. Chang, and M. M. F. Yuen, “Virtual
human modeling from photographs for garment industry,”
Computer-Aided Design, vol.35, pp. 577-589, 2003.
[8] C. C. L. Wang, Y. Wang, and M. M. F. Yuen, “Design automation for
customized apparel products,” Computer-Aided Design, vol.37, pp.
83-98, 2005.
[9] C. C. L. Wang, Y. Wang, and M. M. F. Yuen, “Feature based 3D garment
design through 2D sketches,” Computer-Aided Design, vol.35, pp.
659-672, 2002.
[10] J. Wang, G. Lu, W. Li, L. Chen, and Y. Sakaguti, “Interactive 3D garment
design with constrained contour curves and style curves,”
Computer-Aided Design, vol.41, pp. 614-625, 2009.
[11] D. L Son et al., Multi-finger interactions with papers on augmented
tabletops. In Proc. 3rd International Conference on Tangible and
Embedded Interaction,2009 ,pp. 267-274.
[12] J. Taylor et al, “The vitruvian manifold: inferring dense correspondences
for one-shot human pose estimation,” Microsoft Research, 2012.
[13] S. Izadi et al., Kinect Fusion: Real-time 3D reconstruction and interaction
using a moving depth camera. in Proc. 24th Annu. ACM symposium on
User interface software and technology,2011,pp. 559-568.
[14] R. A. Newcombe et al., Kinect Fusion: Real-time dense surface mapping
and tracking. In Proc. Mixed and Augmented Reality (ISMAR), 2011
10th IEEE International Symposium on, 2011, pp.127-136.
[15] W. D. Ueng, Lai JY and Doong JL. “Sweep-surface reconstruction from
three-dimensional measured data,” Computer-Aided Design, vol.30, pp.
791-805, 1998.
[16] P. J. Besl, and N. D. Mckay, “A method for registration of 3D shapes,”
IEEE Trans. Pattern Anal. Mach. Intell., vol.14, pp. 239-256, 1992.
[17] S. Rusinkiewicz, and M. Levoy, Efficient variants of the ICP algorithm.
In Proc. 3D Digital Imaging and Modeling, Int. Conf. on, 2001.
[18] S. Rusinkiewicz, O. Hall-Holt, and M. Levoy, “Real-time 3D model
acquisition,” ACM Trans. Graph., 2002.
[19] B. Huhle, T. Schairer, P. Jenke, and W. StraBer, “Fusion of range and
color images for denoising and resolution enhancement with a non-local
filter,” Computer Vision and Image Understanding, vol.114, pp.
1336-1345, 2010.
[20] S. W. Hsiao, and J. C. Chuang, “A Reverse Engineering Based Approach
for Product Form Design,” Design Studies, vol.24, pp. 155-171, 2003.
[21] K. C. Hui, and Y. Li, “A feature-based shape blending technique for
Industrial design,” Computer-Aided Design, vol.10, pp. 823-834, 1998.
[22] H. Q. Huang et al. “Block pattern generateon: From parameterzing human
bodies to fit feature-aligned and flattenable 3D garments,” Computers in
Industry, vol.63, pp. 680-691, 2012.
[23] J. Li, and G. Lu, “Customizing 3D garments based on volume
deformation,” Computers in Industry, vol.62, pp. 693-707, 2011.
[24] W. Ma, “Subdivision surface for CAD – an overview,” Computer-Aided
Design, vol.37, pp. 693-709, 2005.
[25] Y. Ke, S. Fan, W. Zhu, A. Li, F. Liu, and X. Shi, “Feature-based reverse
modeling strategies,” Computer-Aided Design, vol.38, pp. 485-506,
2006.
[26] Y. Ke, W. Zhu, F. Liu, X. Shi, “Constrained fitting for 2D profile-based
reverse modeling,” Computer-Aided Design, vol.38, pp. 101-114, 2006.
[27] J. Li, and G. Lu, “Customizing 3D garments based on volume
deformation,” Computers in Industry, vol. 62, pp. 693-707, 2011.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:70369", author = "Shih-Wen Hsiao and Rong-Qi Chen", title = "Applying Kinect on the Development of a Customized 3D Mannequin", abstract = "In the field of fashion design, 3D Mannequin is a kind
of assisting tool which could rapidly realize the design concepts.
While the concept of 3D Mannequin is applied to the computer added
fashion design, it will connect with the development and the
application of design platform and system. Thus, the situation
mentioned above revealed a truth that it is very critical to develop a
module of 3D Mannequin which would correspond with the necessity
of fashion design. This research proposes a concrete plan that
developing and constructing a system of 3D Mannequin with Kinect.
In the content, ergonomic measurements of objective human features
could be attained real-time through the implement with depth camera
of Kinect, and then the mesh morphing can be implemented through
transformed the locations of the control-points on the model by
inputting those ergonomic data to get an exclusive 3D mannequin
model. In the proposed methodology, after the scanned points from the
Kinect are revised for accuracy and smoothening, a complete human
feature would be reconstructed by the ICP algorithm with the method
of image processing. Also, the objective human feature could be
recognized to analyze and get real measurements. Furthermore, the
data of ergonomic measurements could be applied to shape morphing
for the division of 3D Mannequin reconstructed by feature curves. Due
to a standardized and customer-oriented 3D Mannequin would be
generated by the implement of subdivision, the research could be
applied to the fashion design or the presentation and display of 3D
virtual clothes. In order to examine the practicality of research
structure, a system of 3D Mannequin would be constructed with JAVA
program in this study. Through the revision of experiments the
practicability-contained research result would come out.", keywords = "3D Mannequin, kinect scanner, interactive closest
point, shape morphing, subdivision.", volume = "9", number = "7", pages = "1235-6", }
{
"title": "Applying Kinect on the Development of a Customized 3D Mannequin",
"abstract": "In the field of fashion design, 3D Mannequin is a kind\r\nof assisting tool which could rapidly realize the design concepts.\r\nWhile the concept of 3D Mannequin is applied to the computer added\r\nfashion design, it will connect with the development and the\r\napplication of design platform and system. Thus, the situation\r\nmentioned above revealed a truth that it is very critical to develop a\r\nmodule of 3D Mannequin which would correspond with the necessity\r\nof fashion design. This research proposes a concrete plan that\r\ndeveloping and constructing a system of 3D Mannequin with Kinect.\r\nIn the content, ergonomic measurements of objective human features\r\ncould be attained real-time through the implement with depth camera\r\nof Kinect, and then the mesh morphing can be implemented through\r\ntransformed the locations of the control-points on the model by\r\ninputting those ergonomic data to get an exclusive 3D mannequin\r\nmodel. In the proposed methodology, after the scanned points from the\r\nKinect are revised for accuracy and smoothening, a complete human\r\nfeature would be reconstructed by the ICP algorithm with the method\r\nof image processing. Also, the objective human feature could be\r\nrecognized to analyze and get real measurements. Furthermore, the\r\ndata of ergonomic measurements could be applied to shape morphing\r\nfor the division of 3D Mannequin reconstructed by feature curves. Due\r\nto a standardized and customer-oriented 3D Mannequin would be\r\ngenerated by the implement of subdivision, the research could be\r\napplied to the fashion design or the presentation and display of 3D\r\nvirtual clothes. In order to examine the practicality of research\r\nstructure, a system of 3D Mannequin would be constructed with JAVA\r\nprogram in this study. Through the revision of experiments the\r\npracticability-contained research result would come out.",
"keywords": [
"3D Mannequin",
"kinect scanner",
"interactive closest\r\npoint",
"shape morphing",
"subdivision."
],
"authors": [
"Shih-Wen Hsiao",
"Rong-Qi Chen"
],
"values": 9,
"issue": 7,
"issn": null,
"page_start": 1235,
"page_end": 6,
"year": "2015",
"doi": "https://doi.org/10.5281/zenodo.1107493",
"journal": "International Journal of Mechanical, Industrial and Aerospace Sciences",
"categories": [
"Industrial and Manufacturing Engineering"
],
"files": [
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