Numerical recipes in C: the art of scientific computing
Numerical recipes in C: the art of scientific computing
A morphable model for the synthesis of 3D faces
Proceedings of the 26th annual conference on Computer graphics and interactive techniques
An automatic modeling of human bodies from sizing parameters
I3D '03 Proceedings of the 2003 symposium on Interactive 3D graphics
Continuous capture of skin deformation
ACM SIGGRAPH 2003 Papers
The space of human body shapes: reconstruction and parameterization from range scans
ACM SIGGRAPH 2003 Papers
Made-to-Measure Technologies for an Online Clothing Store
IEEE Computer Graphics and Applications
Static and Dynamic Human Shape Modeling
ICDHM '09 Proceedings of the 2nd International Conference on Digital Human Modeling: Held as Part of HCI International 2009
Automated body feature extraction from 2D images
Expert Systems with Applications: An International Journal
Constructing 3D human model from front and side images
Expert Systems with Applications: An International Journal
An efficient human model customization method based on orthogonal-view monocular photos
Computer-Aided Design
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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 ‘knowledge' 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 input.