Statistical Generation of 3D Facial Animable Models
نویسندگان
چکیده
This article reports results of a modeling system that is part of a larger project which seeks to achieve perceptually realistic animations of 3D models driven by speech. This system generates individualized animatable 3D face models driven by “muscles” and compatible with MPEG-4. Our main contribution is in the use of an extensive facial database and statistical techniques to generate plausible facial models from limited data: from a single image using eigenface-like statistical recognition techniques, from descriptions (identikit) or randomly within the parameters of the population represented in the facial database. An interactive module and a musclebased animation player are also part of the system.
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تاریخ انتشار 2002