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.

Shape analysis with anisotropic windowed Fourier transform / Melzi, Simone; Rodola, Emanuele; Castellani, Umberto; Bronstein, Michael M.. - (2016), pp. 470-478. (Intervento presentato al convegno 4th International Conference on 3D Vision, 3DV 2016 tenutosi a Stanford; USA) [10.1109/3DV.2016.57].

Shape analysis with anisotropic windowed Fourier transform

Melzi, Simone;Rodola, Emanuele;
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.
2016
4th International Conference on 3D Vision, 3DV 2016
3D shape; Shape analysis; Windowed Fourier Transform
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Shape analysis with anisotropic windowed Fourier transform / Melzi, Simone; Rodola, Emanuele; Castellani, Umberto; Bronstein, Michael M.. - (2016), pp. 470-478. (Intervento presentato al convegno 4th International Conference on 3D Vision, 3DV 2016 tenutosi a Stanford; USA) [10.1109/3DV.2016.57].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1228910
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