  The use of Laplacian eigenbases has been shown to be fruitful in many
computer graphics applications. Today, state-of-the-art approaches to shape
analysis, synthesis, and correspondence rely on these natural harmonic bases
that allow using classical tools from harmonic analysis on manifolds. However,
many applications involving multiple shapes are obstacled by the fact that
Laplacian eigenbases computed independently on different shapes are often
incompatible with each other. In this paper, we propose the construction of
common approximate eigenbases for multiple shapes using approximate joint
diagonalization algorithms. We illustrate the benefits of the proposed approach
on tasks from shape editing, pose transfer, correspondence, and similarity.
