<XML><RECORDS><RECORD><REFERENCE_TYPE>31</REFERENCE_TYPE><REFNUM>7047</REFNUM><AUTHORS><AUTHOR>Ju,X.</AUTHOR><AUTHOR>Siebert,J.P.</AUTHOR></AUTHORS><YEAR>2001</YEAR><TITLE>Individualising Human Animation Models</TITLE><PLACE_PUBLISHED>Eurographics 2001 (Short Presentation), Manchester, UK, 2001 </PLACE_PUBLISHED><PUBLISHER>N/A</PUBLISHER><LABEL>Ju:2001:7047</LABEL><ABSTRACT>Realistic human body animation requires accurate body geometry, realistic textures and believable behaviours. Existing human animation models provide excellent tools to control articulated motion and body surface deformations according to body postures, but modelling a specific individual requires a large degree of skill and manual intervention. The advent of 3D imaging collection techniques means that the highly accurate 3D surface of a specific person can now be collected in a matter of milliseconds, but most captured 3D surfaces have little semantic information. 3D-MATIC Laboratory proposes combining 3D images of real people with existing human animation models to achieve highly realistic human animation models that virtual animation characters can be personalised into individuals. What is required is a method of conforming a generic human animation model to fit or ?clone? the 3D geometry scanned from a specific individual. Here we present recent work carried out in the 3D-MATIC Laboratory. Segmentation has been applied to the 3D human body surfaces to extract semantic information, which is necessary to find the segments of the scanned human body corresponding to those of the generic model. Establishing correspondences is essential for the surface conformation. After segmentation, a conformation procedure is applied to bring the generic model surfaces into close correspondence with those of the real-world 3D surface. </ABSTRACT><NOTES>Short Presentation</NOTES></RECORD></RECORDS></XML>