PT Journal
AU Egils Avots
   Meysam Madadi
   Sergio Escalera
   Jordi Gonzalez
   Xavier Baro
   Paul Pallin
   Gholamreza Anbarjafari
TI From 2D to 3D geodesic-based garment matching
SO Multimedia Tools and Applications
JI MTAP
PY 2019
BP 25829–25853
VL 78
IS 18
DI 10.1007/s11042-019-7739-5
DE Shape matching; Geodesic distance; Texture mapping; RGBD image processing; Gaussian mixture model
AB A new approach for 2D to 3D garment retexturing is proposed based on Gaussian mixture models and thin plate splines (TPS). An automatically segmented garment of an individual is matched to a new source garment and rendered, resulting in augmented images in which the target garment has been retextured using the texture of the source garment. We divide the problem into garment boundary matching based on Gaussian mixture models and then interpolate inner points using surface topology extracted through geodesic paths, which leads to a more realistic result than standard approaches. We evaluated and compared our system quantitatively by root mean square error (RMS) and qualitatively using the mean opinion score (MOS), showing the benefits of the proposed methodology on our gathered dataset.
ER