Abstract
With the development of computer science, especially the application of 3D scanning technology in garment design, intelligent modeling is realized, which is impossible to achieve in traditional design methods. In this paper, we propose the 3D model construction of human garments based on the motion recovery structure method. The eigenmatrix is obtained from the camera parameters, and the transformation matrix is calculated by matching the image feature points with the help of scale-invariant feature conversion algorithm to realize the 3D reconstruction technology of human garments based on multiview image sequences. The effectiveness of this method is verified through experiments, and it has good robustness and accuracy. Through the form of style modeling, the design thinking and method can be extended to form a more reasonable garment structure and guide the innovation of garment production mode.
Highlights
As computer vision technology is widely used in various fields such as virtual reality and digital cities, more convenient and efficient acquisition and construction of 3D models of human clothing have become a current research hotspot, which in turn promotes the improvement of computer vision algorithms and applications [1,2,3]. e use of relevant algorithms to construct 3D models of features from multiview image sequences captured with ordinary digital cameras has the advantages of wide use and convenient application, and they are most widely used in the field of 3D model construction [4,5,6,7]
The point cloud data of the human body are captured using a modern 3D scanning system, which is used as the basic input for building the 3D virtual model. en, according to the initial design sketch, the paper pattern of the garment is drawn on it using the relevant design software [9]. en, the latest 3D fitting software CLO3D can be used to generate the 2D paper pattern directly into a 3D virtual garment
We propose a 3D model construction of human clothing based on the motion recovery structure method
Summary
As computer vision technology is widely used in various fields such as virtual reality and digital cities, more convenient and efficient acquisition and construction of 3D models of human clothing have become a current research hotspot, which in turn promotes the improvement of computer vision algorithms and applications [1,2,3]. e use of relevant algorithms to construct 3D models of features from multiview image sequences captured with ordinary digital cameras has the advantages of wide use and convenient application, and they are most widely used in the field of 3D model construction [4,5,6,7]. E new interaction design development process includes 5 objects: human body, virtual mannequin, 3D garment, 2D paper pattern, and physical garment. We propose a 3D model construction of human clothing based on the motion recovery structure method. We obtain the eigenmatrix from the camera parameters, match the image feature points with the help of scale-invariant feature conversion algorithm, calculate the transformation matrix, and realize the 3D reconstruction technology of human clothing based on multiview image sequences [10]. 2. Related Work e current research on the algorithm for constructing 3D models of human clothing based on multiview image sequences has been focused by scholars on two aspects: image sources and algorithm improvement. Is paper constructs 3D models of human garments based on SfM and uses multiview image sequences and computer vision techniques to extract, match, and reconstruct features of the image sequences in 3D
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