A novel three-dimensional surface reconstruction method for the complex fabrics based on the MVS

Abstract To solve the existing problems occurring in the field of digital fabric appearance analysis, such as information loss, visual expression difficulty and low accuracy, a novel three-dimensional (3-D) surface reconstruction method based on the multi-view stereo (MVS) technology was proposed for the appearance evaluation of complex fabrics in this paper. Initially, the fabric images were captured by the self-developed multiple image acquisition system. Subsequently, the dense point cloud of fabric surface could be obtained by the operations of feature point detection and matching, camera intrinsic and extrinsic parameter calculation, image pre-processing, sparse point cloud generation, patch expansion and patch filtering. For the sake of acquiring the high accuracy and great completeness of dense point cloud, planar patches with different scales were used to fit the fabric surface, the normalized cross correlation (NCC) algorithm was adopted to improve the accuracy of photo-consistency measurement, and besides, a derivative-free particle swarm optimization (PSO) method was applied to obtain the optimal patches. Our experimental results show that the fabric surface model could be reconstructed by this method accurately, which can be used to characterize the surface texture and 3D weaving profile of woven fabrics. The reconstructed 3D fabric surface model with high precision can be used not only for three-dimensional illustration or rendering but also for structural analysis, quality evaluation of fabric appearance and etc., it provides a useful solution for artificial intelligence production in the textile industry.

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