Virtual People: Capturing human models to populate virtual worlds
Hilton, A, Beresford, D, Gentils, T, Smith, R and Sun, W (1999) Virtual People: Capturing human models to populate virtual worlds In: Proceedings Computer Animation, 1999., 1999-05-26 - 1999-05-29, Geneva, Switzerland.
Available under License : See the attached licence file.
In this paper a new technique is introduced for automatically building recognisable moving 3D models of individual people. A set of multi-view colour images of a person are captured from the front, side and back using one or more cameras. Model-based reconstruction of shape from silhouettes is used to transform a standard 3D generic humanoid model to approximate the persons shape and anatomical structure. Realistic appearance is achieved by colour texture mapping from the multi-view images. Results demonstrate the reconstruction of a realistic 3D facsimile of the person suitable for animation in a virtual world. The system is low-cost and is reliable for large variations in shape, size and clothing. This is the first approach to achieve realistic model capture for clothed people and automatic reconstruction of animated models. A commercial system based on this approach has recently been used to capture thousands of models of the general public.
|Item Type:||Conference or Workshop Item (Conference Paper)|
|Divisions :||Faculty of Engineering and Physical Sciences > Electronic Engineering > Centre for Vision Speech and Signal Processing|
|Date :||May 1999|
|Identification Number :||10.1109/CA.1999.781210|
|Additional Information :||
Copyright 2008 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
|Depositing User :||Symplectic Elements|
|Date Deposited :||08 Feb 2012 13:09|
|Last Modified :||23 Sep 2013 19:00|
Actions (login required)
Downloads per month over past year