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Distance Corrections01:15

Distance Corrections

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To achieve precise distance measurements, especially in surveying and construction, certain corrections must be applied to account for potential sources of error like the standardization errors, temperature variations, and slope adjustments.Standardization error emerges when measurement equipment undergoes changes, such as wear, repairs, or weather impacts. To address this, surveyors compare the equipment’s readings to a standard. This process identifies any deviation that might lead to...
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Evaluating the Accuracy of Fabric Mechanical Digitization Methods.

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    AI-based fabric digitization shows competitive accuracy for 3D virtual design, reducing physical prototyping. This study validates AI methods against traditional mechanical testing using the Cusick drape test.

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    Area of Science:

    • Apparel industry
    • 3D virtual design
    • Textile science

    Background:

    • The apparel industry is increasingly adopting 3D virtual design, enabled by simulation and digitization technologies.
    • Digital twins are crucial for virtual garment testing and refinement, minimizing physical prototypes.
    • Accurate fabric drape behavior capture is essential for garment aesthetics and function, but traditional digitization is labor-intensive and costly.

    Purpose of the Study:

    • To evaluate the accuracy of AI-based fabric digitization methods compared to traditional techniques.
    • To address the knowledge gap regarding the reliability of AI in fabric digitization for 3D virtual design.
    • To provide a benchmark for assessing fabric drape behavior using the Cusick drape test.

    Main Methods:

    • A reference digitization pipeline was established using traditional mechanical testing.
    • A comparative study assessed six commercial digitization methods (traditional and AI-based) on diverse fabrics.
    • The Cusick drape test was employed to measure fabric drape behavior for real and digitized samples.

    Main Results:

    • AI-based fabric digitization methods demonstrated competitive accuracy against real-world measurements.
    • The study identified areas where AI methods can be further improved for enhanced precision.
    • A publicly available dataset of fabric properties and drape metrics was created.

    Conclusions:

    • AI-based digitization offers a viable and potentially more efficient alternative to traditional methods in the apparel industry.
    • Further research and development can optimize AI algorithms for even greater accuracy in fabric drape simulation.
    • The provided dataset will facilitate future advancements in virtual fashion design and textile analysis.