Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects…
Abstract
Examines the fifthteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.
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Jin Young Jung, Seonkoo Chee and InHwan Sul
Increasingly 3D printing is used for parts of garments or for making whole garments due to their flexibility and comfort and for functionalizing or enhancing the aesthetics of the…
Abstract
Purpose
Increasingly 3D printing is used for parts of garments or for making whole garments due to their flexibility and comfort and for functionalizing or enhancing the aesthetics of the final garment and hence adding value. Many of these applications rely on complex programming of the 3D printer and are usually provided by the vendor company. This paper introduces a simpler, easier platform for designing 3D-printed textiles, garments and other artifacts, by predicting the optimal orientation of the target objects to minimize the use of plastic filaments.
Design/methodology/approach
The main idea is based on the shadow-casting analogy, which assumes that the volume of the support structure is similar to that of the shadow from virtual sunlight. The triangular elements of the target object are converted into 3D pixels with integer-based normal vectors and real-numbered coordinates via vertically sparse voxelization. The pixels are classified into several groups and their noise is suppressed using a specially designed noise-filtering algorithm called slot pairing. The final support structure volume information was rendered as a two-dimensional (2D) figure, similar to a medical X-ray image. Thus, the authors named their method modified support structure tomography.
Findings
The study algorithm showed an error range of no more than 1.6% with exact volumes and 6.8% with slicing software. Moreover, the calculation time is only several minutes for tens of thousands of mesh triangles. The algorithm was verified for several meshes, including the cone, sphere, Stanford bunny and human manikin.
Originality/value
Simple hardware, such as a CPU, embedded system, Arduino or Raspberry Pi, can be used. This requires much less computational resources compared with the conventional g-code generation. Also, the global and local support structure is represented both quantitatively and graphically via tomographs.
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As an extended work of the previous paper (Sul, 2010), this paper provides a guideline information for an anonymous garment pattern in sewing process. The purpose of this paper is…
Abstract
Purpose
As an extended work of the previous paper (Sul, 2010), this paper provides a guideline information for an anonymous garment pattern in sewing process. The purpose of this paper is to first, provide garment pattern database. By simply taking pictures of garment patterns, the shape database is constructed. Once the shape database is prepared, data retrieval can be done by image indexing, i.e., simply inserting garment pattern boundary shape again to the database. Using shock graph methodology, the pattern sets used for database preparation can be exactly retrieved. Second, to find the nearest shape of a given input pattern shape in the database. If the input garment pattern shape does not exist in the database, the shape matching algorithm provides the next similar pattern data. The user, who is assumed to be non-expert in garment sewing process, can easily predict the position and combination information of various patterns.
Design/methodology/approach
Image processing is used to construct the garment pattern shape database. The boundary shapes are extracted from the photographs of garment patterns and their shape recognition information, especially shock graph, is also recorded for later pattern data retrieval.
Findings
Using the image processing technique, garment patterns can be converted to electronic format easily. Also the prepared pattern database can be used for finding the nearest shape of an additional given input garment pattern. Patterns with irregular shapes were retrieved easily, while those with a simple shape, such as rectangle, showed a little erroneous result.
Originality/value
Shape recognition has been adopted in various industrial areas, except for garment sewing process. Using the provided methodology, garment pattern shapes can be easily saved and retrieved only by taking pictures of them.
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Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects…
Abstract
Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.
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The purpose of this paper is to determine the possibility of implementing parallel processing feature of graphic processor unit (GPU) in garment drape simulation.
Abstract
Purpose
The purpose of this paper is to determine the possibility of implementing parallel processing feature of graphic processor unit (GPU) in garment drape simulation.
Design/methodology/approach
Velocity‐Verlet method based on explicit integration is used to drape triangular table cloth meshes. Both drape simulation and collision detection engines are converted to GPU version. Simulation speeds of simple linear algebra and actual free fall table cloth simulation are compared with those of the central processing unit (CPU) version.
Findings
There is apparent calculation speed increase when the parallel computation of GPU is implemented. But the current GPUs have several limits for general purpose computation, so the original CPU version algorithm should be split and modified to be used in GPU.
Originality/value
This paper implemented GPU parallel processing technique in both drape simulation and collision detection. Voxel‐based method is used to find possible collision pairs. Triangular meshes, which are more difficult to implement than quadrilateral ones in GPU programming, are successfully implemented.
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The purpose of this paper is to combine patterns from different garment sets and preview garment styles in 3D apparel design by giving sewing names to patterns and sewing edges.
Abstract
Purpose
The purpose of this paper is to combine patterns from different garment sets and preview garment styles in 3D apparel design by giving sewing names to patterns and sewing edges.
Design/methodology/approach
A new rule for 3D garment sewing is made. Unlike conventional vertex number‐based method, patterns and their edges are given specific names. If two edges have a same edge name, they make a sewing line. Thus, patterns from different garments can be combined and draped with this method. Numbers of boundary mesh nodes were controlled using B‐Spline to combine sewing edges of different lengths.
Findings
It is found that by only assigning names to patterns and sewing edges, garment style can be previewed by substituting patterns.
Originality/value
Styles and details of garments can be previewed in 3D by mixing patterns of different garment sets like in 2D technical flat sketching. Even patterns with different edge lengths can be combined by controlling the pattern meshes using B‐Spline.
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The purpose of this paper is to develop a new and simple methodology for fabric collision detection and response.
Abstract
Purpose
The purpose of this paper is to develop a new and simple methodology for fabric collision detection and response.
Design/methodology/approach
A 3D triangle‐to‐triangle collision problem was converted to simple 2D point‐in‐triangle problem using pre‐computed 4×4 transformation matrices. The object space was partitioned using voxels to find easily collision pair triangles. k‐DOP was used to find inter‐pattern collisions.
Findings
Complex 3D collision detection problem is solved by simple matrix operations. Voxel‐based space partitioning and k‐DOP‐based hierarchical methods are successfully applied to garment simulation.
Originality/value
This paper shows that the collision matrix method can cover from triangle‐to‐point to triangle‐to‐triangle collision with mathematical validity and can be simply implemented in garment simulation.
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The purpose of this paper is to find automatic post‐processing scheme to give textures and motion data to three dimensional (3D) body scan data.
Abstract
Purpose
The purpose of this paper is to find automatic post‐processing scheme to give textures and motion data to three dimensional (3D) body scan data.
Design/methodology/approach
Semi‐implicit particle‐based method was applied to post‐processing of 3D body scan data. The template avatar mesh was draped onto the target scan data and the texture/motion data were transferred to regenerated body. Automatic body feature detection was used to correlate the template body with the target body.
Findings
Using semi‐implicit particle method, there are advantages in both computational stability and accuracy. The calculation is done in a few minutes and even data with many holes could be used.
Originality/value
There are several researches for body feature detection and scan body regeneration but this paper aims for fully automatic method which needs no human intervention. The semi‐implicit particle method, which is popularly used for cloth simulation, is applied to body data regeneration. The conventional 3D body scan data, which had no colors and motions can be given textures and motions with this approach. And even the face can be freely interchanged with the use of external face generation software.