3D body reconstruction from photos based on range scan

  • Seo H
  • Yeo Y
  • Wohn K
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We present a data-driven shape model for reconstructing human body
models from one or more 2D photos. One of the key tasks in reconstructing
the 3D model from image data is shape recovery, a task done until
now in utterly geometric way, in the domain of human body modeling.
In contrast, we adopt a data-driven, parameterized deformable model
that is acquired from a collection of range scans of real human body.
The key idea is to complement the image-based reconstruction method
by leveraging the quality shape and statistic information accumulated
from multiple shapes of range-scanned people. In the presence of
ambiguity either from the noise or missing views, our technique has
a bias towards representing as much as possible the previously acquired
on the shape geometry. Texture coordinates are then generated by
projecting the modified deformable model onto the front and back
images. Our technique has shown to reconstruct successfully human
body models from minimum number images, even from a single image

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  • Hyewon Seo

  • Young In Yeo

  • Kwangyun Wohn

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