In: IEEE CG&A special issue on Web Graphics, pp. Addison-Wesley, Reading (1999)Ĭordier, F., Seo, H., Magnenat-Thalmann, N.: Made-to-Measure Technologies for Online Clothing Store.

Addison-Wesley, Reading (2003)īlanz, B., Vetter, T.: A morphable model for the synthesis of 3D faces. 429–432 (2000)Īllen, B., Curless, B., Popovic, Z.: The space of human body shapes: reconstruction and parameterization from range scans. Korea Conference on Human Computer Interaction 2000, pp. This process is experimental and the keywords may be updated as the learning algorithm improves.Īhn, J.H., Sul, C.H., Park, E.K., Wohn, K.W.: Lan-based Optical Motion Capture System. These keywords were added by machine and not by the authors. Our technique has shown to reconstruct successfully human body models from minimum number images, even from a single image input. Texture coordinates are then generated by projecting the modified deformable model onto the front and back images. 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.

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.

3d body visualizer male