Direct manipulation blendshapes.

This paper introduces a simple direct manipulation algorithm for the popular blendshape facial animation approach. As is the case for body animation, direct manipulation of blendshape models is an inverse problem: when a single vertex is moved, the system must infer the movement of other points. The key to solving the inverse problem is the observation that the blendshape sliders are a semantic parameterization -- the corresponding blendshape targets have clear, interpretable functions. Distance in "slider space'' is easily computed and provides the necessary regularization for the inverse problem: The change in semantic position is minimized subject to interpolating the artist's direct manipulations. We give empirical and mathematical demonstrations that a single direct manipulation edit is often the equivalent of multiple slider edits, but the converse is also true, confirming the principle that both editing modes should be supported.

Compatible embedding for 2D shape animation.

We present new algorithms for the compatible embedding of 2D shapes. Such embeddings offer a convenient way to interpolate shapes having complex, detailed features. Compared to existing techniques, our approach requires less user input, and is faster, more robust, and simpler to implement, making it ideal for interactive use in practical applications. Our new approach consists of three parts. First, our boundary matching algorithm locates salient features using the perceptually motivated principles of scale-space and uses these as automatic correspondences to guide an elastic curve matching algorithm. Second, we simplify boundaries while maintaining their parametric correspondence and the embedding of the original shapes. Finally, we extend the mapping to shapes' interiors via a new compatible triangulation algorithm. The combination of our algorithms allows us to demonstrate 2D shape interpolation with instant feedback. The proposed algorithms exhibit a combination of simplicity, speed, and accuracy that has not been achieved in previous work.