Abstract
Different types of cloth show distinctive appearances owing to their unique yarn-level geometrical details. Despite its importance in applications such as cloth rendering and simulation, capturing yarn-level geometry is nontrivial and requires special hardware, e.g., computed tomography scanners, for conventional methods. In this paper, we propose a novel method that can produce the yarn-level geometry of real cloth using a single micro-image, captured by a consumer digital camera with a macro lens. Given a single input image, our method estimates the large-scale yarn geometry by image shading, and the fine-scale fiber details can be recovered via the proposed fiber tracing and generation algorithms. Experimental results indicate that our method can capture the detailed yarn-level geometry of a wide range of cloth and reproduce plausible cloth appearances.
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Hong-yu WU, Xiao-wu CHEN, Chen-xu ZHANG, Bin ZHOU, and Qin-ping ZHAO declare that they have no conflict of interest.
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Project supported by the National Natural Science Foundation of China (Nos. 61532003 and 61902014) and the National Key Research and Development Plan, China (No. 2018YFC0831003)
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Wu, Hy., Chen, Xw., Zhang, Cx. et al. Modeling yarn-level geometry from a single micro-image. Frontiers Inf Technol Electronic Eng 20, 1165–1174 (2019). https://doi.org/10.1631/FITEE.1800693
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DOI: https://doi.org/10.1631/FITEE.1800693