Download Data-Driven 3D Facial Animation by Zhigang Deng, Ulrich Neumann PDF

By Zhigang Deng, Ulrich Neumann

"Data-Driven 3D Facial Animation" systematically describes the rising data-driven concepts constructed over the past ten years or so. even supposing data-driven 3D facial animation is used increasingly more in animation perform, so far there were only a few books that in particular handle the concepts involved.

Comprehensive in scope, the publication covers not just conventional lip-sync (speech animation), but in addition expressive facial movement, facial gestures, facial modeling, enhancing and sketching, and facial animation moving. It offers an updated reference resource for educational examine and for execs operating within the facial animation box. An edited quantity, the publication brings jointly contributions from top researchers and practitioners operating in either academia and within the best animation studios.

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Benoit. A text-to-audovisual-speech synthesizer for French. In Proc. of the Int’l. Conf. on Spoken Language Processing (ICSLP), pages 2163–2166, 1996. 85. P. E. Magno, G. Perlin, and C. Zmarich. Labial coarticulation modeling for realistic facial animation. In Proc. of Int’l Conf. on Multimodal Interfaces 02, pages 505–510, Pittsburgh, PA, 2002. 86. A. E. Parent. Creating speech-synchronized animation. IEEE Trans. Vis. , 11(3):341–352, 2005. 87. C. Pelachaud. Communication and coarticulation in facial animation.

The tracking is robust for a normal condition, but weak at a changing of lighting condition [16, 17]. 1 Initialization The face features and its associated information are set during the initialization phase that will solve the main problem in facial feature differences between people. 2(a) shows this initialization step. In this phase, the program automatically recognizes salient regions to decide the initial feature positions. Therefore, no manual manipulation is required and the information around the features, the edge information, and the face color information are extracted automatically.

Among all possible mouth shapes, the best candidate is chosen according to a “highest energy” criterion from the database, which contains rules of a combination between the basic mouth shape and the edge appearance. 3(a) presents the simple rule contained in the database. The edge level value along the vertical line from the nose to the jaw, for different possible shape of the mouth and the corresponding detected edges, reveals • Closed mouth: In this case, the center edge appears strong, the other two edges normally appear weak, and teeth are hidden inside; thus, the edge is not detected.

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