TY - GEN
T1 - Demonstrating the robustness of frequency-domain correlation filters for 3D object recognition applications
AU - Picos, Kenia
AU - Orozco-Rosas, Ulises
AU - Diaz-Ramirez, Victor
N1 - Publisher Copyright:
© 2019 SPIE. Downloading of the abstract is permitted for personal use only.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - correlation flters
KW - frequency domain fltering
KW - object recognition
KW - three-dimensional estimation.
UR - http://www.scopus.com/inward/record.url?scp=85075786127&partnerID=8YFLogxK
U2 - 10.1117/12.2528944
DO - 10.1117/12.2528944
M3 - Contribución a la conferencia
AN - SCOPUS:85075786127
T3 - Proceedings of SPIE - The International Society for Optical Engineering
BT - Optics and Photonics for Information Processing XIII
A2 - Iftekharuddin, Khan M.
A2 - Awwal, Abdul A. S.
A2 - Diaz-Ramirez, Victor H.
A2 - Marquez, Andres
PB - SPIE
T2 - Optics and Photonics for Information Processing XIII 2019
Y2 - 13 August 2019 through 14 August 2019
ER -