Models of people captured using current technology have limited realism due to the absence of photo-realistic color, missing data and noise in the measurements. There currently exists no automatic technique for generating animated models from captured 3-D data. 3-D humans for the web. It represents a brand new way for photo-realistic human model capture and a new paradigm for creating animated avatars of individual people. Initially, four images of a person standing in four specified postures are captured from the front, back and two sides.
Controlled illumination is used to reliably extract the silhouette outline for each camera view.
Correct identification of body parts is essential for realistic animation of the reconstructed avatars. A transformation algorithm is applied to each body part, which uniquely maps all points inside the silhouette contour of a captured image to a corresponding point inside the model silhouette. Transformations from multiple views are applied to the generic avatar to morph the three-dimensional shape to that of a particular person. Digital color information from the images is texture mapped onto the transformed generic model to create an avatar with the shape and appearance of the person. Finally, the anatomical structure from the generic avatar is transformed to enable seamless animation.