The Earth Mover's Distance as a Metric for Image Retrieval
International Journal of Computer Vision
Texture Mapping Using Surface Flattening via Multidimensional Scaling
IEEE Transactions on Visualization and Computer Graphics
Convex Optimization
A Theoretical and Computational Framework for Isometry Invariant Recognition of Point Cloud Data
Foundations of Computational Mathematics
Laplace-Beltrami eigenfunctions for deformation invariant shape representation
SGP '07 Proceedings of the fifth Eurographics symposium on Geometry processing
Möbius voting for surface correspondence
ACM SIGGRAPH 2009 papers
Salient spectral geometric features for shape matching and retrieval
The Visual Computer: International Journal of Computer Graphics
Global intrinsic symmetries of shapes
SGP '08 Proceedings of the Symposium on Geometry Processing
Deformation-driven shape correspondence
SGP '08 Proceedings of the Symposium on Geometry Processing
A concise and provably informative multi-scale signature based on heat diffusion
SGP '09 Proceedings of the Symposium on Geometry Processing
Full and Partial Symmetries of Non-rigid Shapes
International Journal of Computer Vision
International Journal of Computer Vision
Volumetric heat kernel signatures
Proceedings of the ACM workshop on 3D object retrieval
Shape Recognition with Spectral Distances
IEEE Transactions on Pattern Analysis and Machine Intelligence
Non-rigid shape matching using geometry and photometry
ACCV'09 Proceedings of the 9th Asian conference on Computer Vision - Volume Part III
On bending invariant signatures for surfaces
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recovering and analyzing 3D models of branched structures using computer vision: a review
Proceedings of the 27th Conference on Image and Vision Computing New Zealand
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Detecting similarity between non-rigid shapes is one of the fundamental problems in computer vision. While rigid alignment can be parameterized using a small number of unknowns representing rotations, reflections and translations, non-rigid alignment does not have this advantage. The majority of the methods addressing this problem boil down to a minimization of a distortion measure. The complexity of a matching process is exponential by nature, but it can be heuristically reduced to a quadratic or even linear for shapes which are smooth two-manifolds. Here we model shapes using both local and global structures, and provide a hierarchical framework for the quadratic matching problem.