Modeling and realization of image-based garment texture transfer.

We present an automated framework founded on texture transfer, facilitating the substitution of textures in garment images with specified ones for applications in garment design and online presentation. In contrast to previous methodologies, our approach achieves seamless texture transfer from a single image while preserving fold variations and shadow intricacies. Given a garment image and a texture image, we initially extract pixel-aligned features from the garment image and construct a parametric model of the garment through spatial sampling. The mesh structure is subsequently validated employing the Marching Cube algorithm. We then enhance the model quality through mesh optimization using a variational approach. Finally, we optimize parallax mapping to execute the texture transfer from the source texture image. Experimental results convincingly demonstrate the effectiveness of our method in achieving texture transfer in garment images while maintaining the fidelity of folds and shadows. [ABSTRACT FROM AUTHOR]