TY  - JOUR
AU  - Egils Avots
AU  - Meysam Madadi
AU  - Sergio Escalera
AU  - Jordi Gonzalez
AU  - Xavier Baro
AU  - Paul Pallin
AU  - Gholamreza Anbarjafari
PY  - 2019//
TI  - From 2D to 3D geodesic-based garment matching
T2  - MTAP
JO  - Multimedia Tools and Applications
SP  - 25829–25853
VL  - 78
IS  - 18
KW  - Shape matching
KW  - Geodesic distance
KW  - Texture mapping
KW  - RGBD image processing
KW  - Gaussian mixture model
N2  - 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.
UR  - https://link.springer.com/article/10.1007/s11042-019-7739-5
L1  - http://refbase.cvc.uab.es/files/AME2019.pdf
UR  - http://dx.doi.org/10.1007/s11042-019-7739-5
N1  - HuPBA; ISE; 600.098; 600.119; 602.133
ID  - Egils Avots2019
ER  -