Evaluating Data-Driven Style Transformation for Gesturing Embodied Agents

نویسندگان

  • Alexis Héloir
  • Michael Kipp
  • Sylvie Gibet
  • Nicolas Courty
چکیده

This paper presents an empirical evaluation of a method called Style transformation which consists of modifying an existing gesture sequence in order to obtain a new style where the transformation parameters have been extracted from an existing captured sequence. This data-driven method can be used either to enhance key-framed gesture animations or to taint captured motion sequences according to a desired style.

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تاریخ انتشار 2008