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Journal Article

Estimating Body Shape of Dressed Humans

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44590

Hasler,  Nils
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45557

Stoll,  Carsten
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45618

Thormählen,  Thorsten
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45312

Rosenhahn,  Bodo
Computer Graphics, MPI for Informatics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons45449

Seidel,  Hans-Peter
Computer Graphics, MPI for Informatics, Max Planck Society;

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Citation

Hasler, N., Stoll, C., Thormählen, T., Rosenhahn, B., & Seidel, H.-P. (2009). Estimating Body Shape of Dressed Humans. Computers & Graphics, 33(3), 211-216. doi:10.1016/j.cag.2009.03.026.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000F-19A7-B
Abstract
The paper presents a method to estimate the detailed 3D body shape of a person even if heavy or loose clothing is worn. The approach is based on a space of human shapes, learned from a large database of registered body scans. Together with this database we use as input a 3D scan or model of the person wearing clothes and apply a fitting method, based on ICP (iterated closest point) registration and Laplacian mesh deformation. The statistical model of human body shapes enforces that the model stays within the space of human shapes. The method therefore allows us to compute the most likely shape and pose of the subject, even if it is heavily occluded or body parts are not visible. Several experiments demonstrate the applicability and accuracy of our approach to recover occluded or missing body parts from 3D laser scans.