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Carnegie Mellon Robotics Institute

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Abstract

Active Appearance Models (AAMs) are generative parametric models commonly used to track, recognise and synthesise faces in images and video sequences. In this paper we describe a method for transferring dynamic facial gestures between subjects in real-time. The main advantages of our approach are that: 1) the mapping is computed automatically and does not require high-level semantic information describing facial expressions or visual speech gestures. 2) The mapping is simple and intuitive, allowing expressions to be transferred and rendered in real-time. 3) The mapped expression can be constrained to have the appearance of the target producing the expression, rather than the source expression imposed onto the target face. 4) Near-videorealistic talking faces for new subjects can be created without the cost of recording and processing a complete training corpus for each. Our system enables face-to-face interaction with an avatar driven by an AAM of an actual person in real-time and we show examples of arbitrary expressive speech frames cloned across different subjects.

Notes

Associated Center(s) / Consortia: Vision and Autonomous Systems Center

Associated Lab(s) / Group(s): Face Group and Component Analysis

Associated Project(s): Facial Expression Analysis

Number of pages: 6

Text Reference

B. Theobald, Iain Matthews, Jeffrey Cohn, and S. Boker, "Real-time expression cloning using active appearance models," Proceedings of the ACM International Conference on Multimodal Interfaces (ICMI'07), 2007, pp. 134 - 139.

BibTeX Reference

@inproceedings{Matthews_2007_6013,
   author = "B. Theobald and Iain Matthews and Jeffrey Cohn and S. Boker",
   title = "Real-time expression cloning using active appearance models",
   booktitle = "Proceedings of the ACM International Conference on Multimodal Interfaces (ICMI'07)",
   pages = "134 - 139",
   year = "2007",
}

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