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Demonstrating the robustness of frequency-domain correlation filters for 3D object recognition applications
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Paper Abstract

This paper proposes frequency-domain correlation filtering to solve object recognition of three-dimensional (3D) targets. We perform a linear correlation in the frequency domain between an input frame of the video sequence and a designed filter. This operation measures the correspondence between the two signals. In order to produce a high matching score, we design a bank of correlation filters, in which each filter contains unique information of the target in a single view and statistical parameters of the scene. In this paper, we demonstrate the feasibility of correlation filters used to solve 3D object recognition and their robustness to different image conditions such as noise, cluttered background, and geometrical distortions of the target. The evaluation performance presents a high accuracy in terms of quantitative metrics.

Paper Details

Date Published: 6 September 2019
PDF: 10 pages
Proc. SPIE 11136, Optics and Photonics for Information Processing XIII, 111360O (6 September 2019); doi: 10.1117/12.2528944
Show Author Affiliations
Kenia Picos, CETYS Univ. Baja California (Mexico)
Ulises Orozco-Rosas, CETYS Univ. Baja California (Mexico)
Victor Diaz-Ramirez, CITEDI-IPN (Mexico)


Published in SPIE Proceedings Vol. 11136:
Optics and Photonics for Information Processing XIII
Khan M. Iftekharuddin; Abdul A. S. Awwal; Victor H. Diaz-Ramirez; Andrés Márquez, Editor(s)

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