Texture mapping for 3D painting using geodesic distance

Xu, Songgang; Keyser, John

doi:10.1145/2556700.2566650

Cited by 4 publications

(1 citation statement)

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“…There exist various techniques for conducting a map-ping from 2D image texture space to a 3D surface. Some examples are intermediate 3D shape [5], direct drawing onto the object [15], or using an exponential fast marching method by applying geodesic distance [37,34]. Many researchers have devoted special attention trying to enhance the realism of virtual garment representation during the last decade [7].…”

Section: Literature Reviewmentioning

confidence: 99%

From 2D to 3D Geodesic-based Garment Matching

Madadi¹,

Avots²,

Escalera³

et al. 2018

Preprint

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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 by 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 mean square error (MSE) and qualitatively using the mean opinion score (MOS), showing the benefits of the proposed methodology on our gathered dataset.

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