Text to visual synthesis with appearance models

This paper presents a new method named text to visual synthesis with appearance models (TEVISAM) for generating videorealistic talking heads. In a first step, the system learns a person-specific facial appearance model (PSFAM) automatically. PSFAM allows modeling all facial components (e.g. eyes, mouth, etc) independently and it will be used to animate the face from the input text dynamically. As reported by other researches, one of the key aspects in visual synthesis is the coarticulation effect. To solve such a problem, we introduce a new interpolation method in the high dimensional space of appearance allowing to create photorealistic and videorealistic avatars. In this work, preliminary experiments synthesizing virtual avatars from text are reported. Summarizing, in this paper we introduce three novelties: first, we make use of color PSFAM to animate virtual avatars; second, we introduce a non-linear high dimensional interpolation to achieve videorealistic animations; finally, thi...

• Type: Conference
• Year: 2003
• Where: ICIP
• Authors: Javier Melenchón, Fernando De la Torre, Ignasi Iriondo Sanz, Francesc Alías, Elisa Martínez, Lluís Vicent Safont
• Keywords: Facial Appearance Model, Facial Components, ICIP 2003, Image Processing, Method Named Text, Virtual Avatars, Visual Synthesis