TY - GEN
T1 - Shape analysis with anisotropic windowed Fourier transform
AU - Melzi, Simone
AU - Rodola, Emanuele
AU - Castellani, Umberto
AU - Bronstein, Michael M.
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2016/12/15
Y1 - 2016/12/15
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85011310384
U2 - 10.1109/3DV.2016.57
DO - 10.1109/3DV.2016.57
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AN - SCOPUS:85011310384
T3 - Proceedings - 2016 4th International Conference on 3D Vision, 3DV 2016
SP - 470
EP - 478
BT - Proceedings - 2016 4th International Conference on 3D Vision, 3DV 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 4th International Conference on 3D Vision, 3DV 2016
Y2 - 25 October 2016 through 28 October 2016
ER -