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 contrast, we adopt a data-driven, parameterized deformable model that is acquired from a collection of range scans of real human body. 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.
We present a data-driven shape model for reconstructing human body models from one or more 2D photos.