A Method for Enforcing Integrability in Shape from Shading Algorithms
IEEE Transactions on Pattern Analysis and Machine Intelligence
Scale-Space and Edge Detection Using Anisotropic Diffusion
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
Diffusion Kernels on Graphs and Other Discrete Input Spaces
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
An Algebraic Approach to Surface Reconstruction from Gradient Fields
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Evolving spanning trees using the heat equation
CAIP'05 Proceedings of the 11th international conference on Computer Analysis of Images and Patterns
What is the range of surface reconstructions from a gradient field?
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
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A combinatorial method is used to reconstruct a surface by integrating a field of surface normals. An affinity function is defined over pairs of adjacent locations. This function is based on the surface’s principal curvature directions, which are intrinsic and can be estimated from the surface normals. The values of this locally supported function are propagated over the field of surface normals using a diffusion process. The surface normals are then regularised, by computing the weighted sum of the affinity evolved over time. Finally, the surface is reconstructed by integrating along integration paths that maximise the total affinity. Preliminary experimental results are shown for different degrees of evolution under the presence of noise.