Automated Acquisition of Lifelike 3D Human Models from Multiple Posture Data
In this paper we propose a method for the automated acquisition of 3D human models for real-time animation. The individual to be modelled is placed in a monochrome environment and captured simultaneously by a set of 16 calibrated cameras distributed on a metal support above and around the head. A number of image sets is taken from various postures. A binary volume model will then be reconstructed from each image set via a shape-from-silhouette approach. Based on the surface shape and a reliable 3D skeletonisation of the volume model, a parametric human body template is fitted to each captured posture independently. Finally, from the parameter sets obtained initially, one unique set of posture-invariant parameters and the corresponding multiple sets of posture-dependent parameters are estimated using iterative optimisation. The resulting model consists of a fully textured triangular surface mesh over a bone structure, ready to be used in real-time applications such as 3D video-conferencing or off-the-shelf multi-player games.
Keywordshuman models shape-from-silhouette 3D videoconferencing
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