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Deformable model for estimating clothed and naked human shapes from a single image

Authors :
Yu Guo
Bin Zhou
Xiaowu Chen
Qinping Zhao
Source :
The Visual Computer. 29:1187-1196
Publication Year :
2013
Publisher :
Springer Science and Business Media LLC, 2013.

Abstract

Estimation of human shape from images has numerous applications ranging from graphics to surveillance. A single image provides insufficient constraints (e.g. clothing), making human shape estimation more challenging. We propose a method to simultaneously estimate a person's clothed and naked shapes from a single image of that person wearing clothing. The key component of our method is a deformable model of clothed human shape. We learn our deformable model, which spans variations in pose, body, and clothes, from a training dataset. These variations are derived by the non-rigid surface deformation, and encoded in various low-dimension parameters. Our deformable model can be used to produce clothed 3D meshes for different people in different poses, which neither appears in the training dataset. Afterward, given an input image, our deformable model is initialized with a few user-specified 2D joints and contours of the person. We optimize the parameters of the deformable model by pose fitting and body fitting in an iterative way. Then the clothed and naked 3D shapes of the person can be obtained simultaneously. We illustrate our method for texture mapping and animation. The experimental results on real images demonstrate the effectiveness of our method.

Details

ISSN :
14322315 and 01782789
Volume :
29
Database :
OpenAIRE
Journal :
The Visual Computer
Accession number :
edsair.doi...........97a44b4c579c97e65214efccc87e3607