Translator Disclaimer
Paper
6 September 2019 Demonstrating the robustness of frequency-domain correlation filters for 3D object recognition applications
Author Affiliations +
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.
© (2019) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kenia Picos, Ulises Orozco-Rosas, and Victor Diaz-Ramirez "Demonstrating the robustness of frequency-domain correlation filters for 3D object recognition applications", Proc. SPIE 11136, Optics and Photonics for Information Processing XIII, 111360O (6 September 2019); https://doi.org/10.1117/12.2528944
PROCEEDINGS
10 PAGES


SHARE
Advertisement
Advertisement
RELATED CONTENT


Back to Top