Research map / 3D vision / Face and shape
Efficient Deformable Shape Correspondence via Multiscale Spectral Manifold Wavelets Preservation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Replace descriptor-based constraints with multiscale spectral manifold wavelet preservation and alternating map updates | Functional map correspondence · FAUST, SCAPE, and TOSCA | average geodesic error (×10−3): FAUST: 137.8 -> 10.9; SCAPE: 157.0 -> 11.3; TOSCA: 148.7 -> 16.1 | Helped |
| Use multiscale spectral manifold wavelet preservation with iterative filtering | Functional map correspondence · FAUST, SCAPE, and TOSCA | average runtime (s): FAUST: 0.37; SCAPE: 0.67; TOSCA: 1.94 | Helped |
| Use the proposed method instead of SmoothShells | Shape correspondence · FAUST, SCAPE, and TOSCA | average runtime (s): FAUST: 142.4 -> 2.4; SCAPE: 216.1 -> 4.6; TOSCA: 678.2 -> 58.1 | Helped |
| Use the proposed method instead of SmoothShells | Shape correspondence · FAUST, SCAPE, and TOSCA | average geodesic error (×10−3): FAUST: 12.4 -> 10.9; SCAPE: 15.8 -> 11.3; TOSCA: 17.2 -> 16.1 | Mixed |
| Use tight wavelet frames and compute the functional map by filtering rather than solving a large linear system | Multiscale wavelet functional maps · Shape correspondence | computational efficiency | Helped |
| Use three alternating updates of functional and pointwise maps | Multiscale wavelet functional maps · Shape correspondence | correspondence quality | Helped |
| Use approximate nearest-neighbor search and subsampling for pointwise map recovery | Multiscale wavelet functional maps · Shape correspondence | computational efficiency | Helped |
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