3 D Graphics

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

By Zhigang Deng, Ulrich Neumann

"Data-Driven 3D Facial Animation" systematically describes the rising data-driven innovations built during the last ten years or so. even supposing data-driven 3D facial animation is used a growing number of in animation perform, so far there were only a few books that in particular deal with the innovations involved.

Comprehensive in scope, the e-book covers not just conventional lip-sync (speech animation), but additionally expressive facial movement, facial gestures, facial modeling, modifying and sketching, and facial animation moving. It offers an up to date reference resource for educational examine and for execs operating within the facial animation box. An edited quantity, the booklet brings jointly contributions from major researchers and practitioners operating in either academia and within the prime animation studios.

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A cluster can be a monophone, a biphone, a triphone, or even a quadrphone. Of course, not any combination of Vs and Cs is possible. There are standard charts to define valid clusters [15]. For example, a cluster kji is not possible in English. We believe that because there exists a most natural (if not unique) way of pronouncing a word as a sequence of syllables, this is also the best way to generate speech animation from the basic visyllable units. Our syllabification algorithm uses the basic definition of syllable and the set of valid clusters.

We first ensure the C0 continuity by computing all the gaps and automatically performing shift and stretch operations on individual visyllable segments to nullify the gaps. We observed two types of gaps across the demi-visyllable boundaries. In the first case, the entire segment needs a shift in order to be continuous with the previous and the subsequent segments. 46 T. D. Giacomo et al. This is when the boundary gap on either side of the segment is more or less of the same magnitude and no significant amplitude stretching is required after the shift.

The FMPs are derived from the statistical analysis of the entire visyllable data. FMPs are, in fact, the basis vectors computed as a result of the principal component analysis (PCA) of the facial motion capture data. The PCA results in a reduced-dimensional Fig. 6 The visyllable database using FMPs [30]. 40 T. D. Giacomo et al. Fig. 7 Real-time visyllable-based speech animation. representation of the original data by extracting the principal directions of variation. We have concluded that only eight parameters are sufficient to represent a speech posture, considerably reducing the amount of data required for the database.

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