Abstract
This paper presents a method to decompose a field of surface normals (needle-map). A diffusion process is used to model the flow of height information induced by a field of surface normals. The diffusion kernel can be decomposed into eigenmodes, each corresponding to approximately independent modes of variation of the flow. The surface normals can then be diffused using a modified kernel with the same eigenmodes but different coefficients. When used as part of a surface integration process, this procedure allows choosing the trade-off between local and global influence of each eigenmode in the modified field of surface normals. This graph-spectral method is illustrated with surface normals extracted from a face. Experiments are carried with local affinity functions that convey both the intrinsic and extrinsic geometry of the surface, and an information-theoretic definition of affinity.
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