Simplicial interpolation for animating the Hulk

Bengio, Julien Cohen; Goldenthal, Rony

doi:10.1145/2504459.2504468

Cited by 3 publications

(2 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Interpolation generally involves a trade-off between smoothness and overshoot: linear interpolation is not smooth, but the function takes on its extreme values exactly at the datapoints; increasing smoothness typically causes the interpolated function to "overshoot" or travel beyond the range of the data. Because overshoot in high-dimensional functions is difficult to visualize and control, [23] introduced a variant of pose space deformation that uses simple linear interpolation on the data simplices. ( [126] may have also used this idea, though it is difficult to say from the one-page description).…”

Section: Linear Interpolationmentioning

confidence: 99%

See 1 more Smart Citation

Learning from the Artist: Theory and Practice of Example-Based Character Deformation

Lewis¹

View full text Add to dashboard Cite

<p>Movie and game production is very laborious, frequently involving hundreds of person-years for a single project. At present this work is difficult to fully automate, since it involves subjective and artistic judgments. Broadly speaking, in this thesis we explore an approach that works with the artist, accelerating their work without attempting to replace them. More specifically, we describe an “example-based” approach, in which artists provide examples of the desired shapes of the character, and the results gradually improve as more examples are given. Since a character’s skin shape deforms as the pose or expression changes, or particular problem will be termed character deformation. The overall goal of this thesis is to contribute a complete investigation and development of an example-based approach to character deformation. A central observation guiding this research is that character animation can be formulated as a high-dimensional problem, rather than the two- or three-dimensional viewpoint that is commonly adopted in computer graphics. A second observation guiding our inquiry is that statistical learning concepts are relevant. We show that example-based character animation algorithms can be informed, developed, and improved using these observations. This thesis provides definitive surveys of example-based facial and body skin deformation. This thesis analyzes the two leading families of example-based character deformation algorithms from the point of view of statistical regression. In doing so we show that a wide variety of existing tools in machine learning are applicable to our problem. We also identify several techniques that are not suitable due to the nature of the training data, and the high-dimensional nature of this regression problem. We evaluate the design decisions underlying these example-based algorithms, thus providing the groundwork for a ”best practice” choice of specific algorithms. This thesis develops several new algorithms for accelerating example-based facial animation. The first algorithm allows unspecified degrees of freedom to be automatically determined based on the style of previous, completed animations. A second algorithm allows rapid editing and control of the process of transferring motion capture of a human actor to a computer graphics character. The thesis identifies and develops several unpublished relations between the underlying mathematical techniques. Lastly, the thesis provides novel tutorial derivations of several mathematical concepts, using only the linear algebra tools that are likely to be familiar to experts in computer graphics. Portions of the research in this thesis have been published in eight papers, with two appearing in premier forums in the field.</p>

show abstract

Section: Linear Interpolationmentioning

confidence: 99%

“…Each "point" is a location in the pose space, with an associated geometric pose of the creature. Computational geometry libraries such as qdelaunay can be used for this purpose [23]. After the simplices are obtained, interpolation can be performed using the ddimensional generalization of barycentric interpolation.…”

Section: Linear Interpolationmentioning

confidence: 99%

Learning from the Artist: Theory and Practice of Example-Based Character Deformation

Lewis¹

View full text Add to dashboard Cite

show abstract

Subspace clothing simulation using adaptive bases

et al. 2014

View full text Add to dashboard Cite

We present a new approach to clothing simulation using low-dimensional linear subspaces with temporally adaptive bases. Our method exploits full-space simulation training data in order to construct a pool of low-dimensional bases distributed across pose space. For this purpose, we interpret the simulation data as offsets from a kinematic deformation model that captures the global shape of clothing due to body pose. During subspace simulation, we select low-dimensional sets of basis vectors according to the current pose of the character and the state of its clothing. Thanks to this adaptive basis selection scheme, our method is able to reproduce diverse and detailed folding patterns with only a few basis vectors. Our experiments demonstrate the feasibility of subspace clothing simulation and indicate its potential in terms of quality and computational efficiency.

show abstract