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Relevant bibliographies by topics / 3D body modelling

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Journal articles

Academic literature on the topic '3D body modelling'

Author: Grafiati

Published: 16 March 2023

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Journal articles on the topic "3D body modelling"

1

Arlt, Frank, and Amin Marach. "CAD modelling of a human 3D child body." International Journal of Industrial Ergonomics 22, no. 4-5 (1998): 333–41. http://dx.doi.org/10.1016/s0169-8141(97)00086-3.

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Špelić, Ivana, and Slavenka Petrak. "Complexity of 3D human body scan data modelling." TEKSTILEC 61, no. 4 (2018): 235–44. http://dx.doi.org/10.14502/tekstilec2018.61.235-244.

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Milosevic, Paula, and Slavica Bogovic. "3D technologies in individualized chest protector modelling." Textile & Leather Review 1, no. 2 (2018): 46–55. http://dx.doi.org/10.31881/tlr.2018.vol1.iss2.p46-55.a6.

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The application of 3D technology increases every day by discovering new ways of usage, which can make everyday life easier. It is most used in production of individualized items that become more accessible and fully customized to personal needs. 3D technologies such as 3D scanning, 3D modelling and additive technologies (3D printing) are used in various areas of human activity such as medicine, architecture, the movie industry, etc. In the clothing’s industry, 3D scanning the human body is digitized, which is after that used in computer software packages for custom-made clothing. Except for th

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4

Gu, Bingfei, Md Kawysar Ahmed, Zejun Zhong, and Juanfeng Jin. "3D female upper body modelling based on 2D images." International Journal of Clothing Science and Technology 32, no. 4 (2020): 471–82. http://dx.doi.org/10.1108/ijcst-03-2019-0042.

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Purpose With the rapid advancement of computer information technology, the traditional clothing industry has stridden towards automation and digitization that drive the growth of electronic commerce and line retailing. The purpose of this paper is to propose an approach on 3D upper body modelling based on the body measurements extracted by non-contact anthropometry. Design/methodology/approach Based on the frontal and side images of the human body, the body sizes were extracted through silhouette extraction, identification of landmarks and girth prediction. The generation rules of 15 character

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Tyson, Stephen, and Joost Herweijer. "Knowledge management and 3D modelling: overview and application to iterative 3D modelling workflows." APPEA Journal 51, no. 2 (2011): 683. http://dx.doi.org/10.1071/aj10063.

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As 3D reservoir modeling is effectively the centre stage in many multi-disciplinary reservoir management efforts, the need for effective knowledge management is paramount to ensure: Inclusion of pre-existing knowledge is in the model, including absent (or controversial knowledge), reflected in uncertainties. A definition of a modeling process comprehensively covers the reservoirs issues identified while leading to fit for purpose results in a given imposed time span. Storage of knowledge generated and a modeling audit trail during the modeling process to ensure adequate and efficient model upd

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Markiewicz, P. J., M. Tamal, P. J. Julyan, D. L. Hastings, and A. J. Reader. "High accuracy multiple scatter modelling for 3D whole body PET." Physics in Medicine and Biology 52, no. 3 (2007): 829–47. http://dx.doi.org/10.1088/0031-9155/52/3/021.

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7

Thelwell, Michael, Alice Bullas, Andreas Kühnapfel, et al. "Modelling of human torso shape variation inferred by geometric morphometrics." PLOS ONE 17, no. 3 (2022): e0265255. http://dx.doi.org/10.1371/journal.pone.0265255.

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Traditional body measurement techniques are commonly used to assess physical health; however, these approaches do not fully represent the complex shape of the human body. Three-dimensional (3D) imaging systems capture rich point cloud data that provides a representation of the surface of 3D objects and have been shown to be a potential anthropometric tool for use within health applications. Previous studies utilising 3D imaging have only assessed body shape based on combinations and relative proportions of traditional body measures, such as lengths, widths and girths. Geometric morphometrics (

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8

Rudolf, A., Z. Stjepanović, and A. Cupar. "DESIGN OF GARMENTS USING ADAPTABLE DIGITAL BODY MODELS." TEXTEH Proceedings 2021 (October 22, 2021): 9–17. http://dx.doi.org/10.35530/tt.2021.09.

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In recent years, the 3D design software has been mostly used to improve the garment design process by generating virtual 3D garment prototypes. Many researchers have been working on the development of 3D virtual garment prototypes using 3D body models and involving the 3D human body scanning in different postures. The focus of research in this field today relies on generating a kinematic 3D body model for the purposes of developing the individualized garments, the exploration of which is presented in this paper. The discussed area is also implemented in the Erasmus+ project OptimTex - Software

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9

Gou, J., W. Zhou, and L. Wu. "IMPLICIT THREE-DIMENSIONAL GEO-MODELLING BASED ON HRBF SURFACE." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W2 (October 5, 2016): 63–66. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w2-63-2016.

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Three-dimensional (3D) geological models are important representations of the results of regional geological surveys. However, the process of constructing 3D geological models from two-dimensional (2D) geological elements remains difficult and time-consuming. This paper proposes a method of migrating from 2D elements to 3D models. First, the geological interfaces were constructed using the Hermite Radial Basis Function (HRBF) to interpolate the boundaries and attitude data. Then, the subsurface geological bodies were extracted from the spatial map area using the Boolean method between the HRBF

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Kudzia, Pawel, Erika Jackson, and Genevieve Dumas. "Estimating body segment parameters from three-dimensional human body scans." PLOS ONE 17, no. 1 (2022): e0262296. http://dx.doi.org/10.1371/journal.pone.0262296.

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Body segment parameters are inputs for a range of applications. Participant-specific estimates of body segment parameters are desirable as this requires fewer prior assumptions and can reduce outcome measurement errors. Commonly used methods for estimating participant-specific body segment parameters are either expensive and out of reach (medical imaging), have many underlying assumptions (geometrical modelling) or are based on a specific subset of a population (regression models). Our objective was to develop a participant-specific 3D scanning and body segmentation method that estimates body

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