We propose Anisotropic Windowed Fourier Transform (AWFT), a framework for localized space-frequency analysis of deformable 3D shapes. With AWFT, we are able to extract meaningful intrinsic localized orientation-sensitive structures on surfaces, and use them in applications such as shape segmentation, salient point detection, feature point description, and matching. Our method outperforms previous approaches in the considered applications.

Melzi, S., Rodola, E., Castellani, U., Bronstein, M. (2016). Shape analysis with anisotropic windowed Fourier transform. In Proceedings - 2016 4th International Conference on 3D Vision, 3DV 2016 (pp.470-478). Institute of Electrical and Electronics Engineers Inc. [10.1109/3DV.2016.57].

Shape analysis with anisotropic windowed Fourier transform

Melzi, Simone;
2016

Abstract

We propose Anisotropic Windowed Fourier Transform (AWFT), a framework for localized space-frequency analysis of deformable 3D shapes. With AWFT, we are able to extract meaningful intrinsic localized orientation-sensitive structures on surfaces, and use them in applications such as shape segmentation, salient point detection, feature point description, and matching. Our method outperforms previous approaches in the considered applications.
Si
paper
3D shape; Shape analysis; Windowed Fourier Transform
English
4th International Conference on 3D Vision, 3DV 2016
9781509054077
Melzi, S., Rodola, E., Castellani, U., Bronstein, M. (2016). Shape analysis with anisotropic windowed Fourier transform. In Proceedings - 2016 4th International Conference on 3D Vision, 3DV 2016 (pp.470-478). Institute of Electrical and Electronics Engineers Inc. [10.1109/3DV.2016.57].
Melzi, S; Rodola, E; Castellani, U; Bronstein, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/350548
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