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Robust Object Classification Approach using Spherical Harmonics

Mukhaimar, A; Tennakoon, R; Lai, CY; Hoseinnezhad, R; Bab-Hadiashar, A; (2022) Robust Object Classification Approach using Spherical Harmonics. IEEE Access , 10 21541 -21553. 10.1109/ACCESS.2022.3151350. Green open access

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Abstract

Point clouds produced by either 3D scanners or multi-view images are often imperfect and contain noise or outliers. This paper presents an end-to-end robust spherical harmonics approach to classifying 3D objects. The proposed framework first uses the voxel grid of concentric spheres to learn features over the unit ball. We then limit the spherical harmonics order level to suppress the effect of noise and outliers. In addition, the entire classification operation is performed in the Fourier domain. As a result, our proposed model learned features that are less sensitive to data perturbations and corruptions. We tested our proposed model against several types of data perturbations and corruptions, such as noise and outliers. Our results show that the proposed model has fewer parameters, competes with state-of-art networks in terms of robustness to data inaccuracies, and is faster than other robust methods. Our implementation code is also publicly available1.

Type: Article
Title: Robust Object Classification Approach using Spherical Harmonics
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ACCESS.2022.3151350
Publisher version: http://dx.doi.org/10.1109/ACCESS.2022.3151350
Language: English
Additional information: This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/
Keywords: Harmonic analysis, Three-dimensional displays, Power harmonic filters, Point cloud compression, Shape, Convolution, Robustness
UCL classification: UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL
URI: https://discovery.ucl.ac.uk/id/eprint/10144612
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