TY - JOUR
T1 - Homography estimation from a single-point correspondence using template matching and particle swarm optimization
AU - Diaz-Ramirez, Victor H.
AU - Juarez-Salazar, Rigoberto
AU - Zheng, Juan
AU - Hernandez-Beltran, Jose Enrique
AU - Márquez, Andrés
N1 - Publisher Copyright:
© 2022 Optica Publishing Group
PY - 2022/3/1
Y1 - 2022/3/1
N2 - Existing feature-based methods for homography estimation require several point correspondences in two images of a planar scene captured from different perspectives. These methods are sensitive to outliers, and their effectiveness depends strongly on the number and accuracy of the specified points. This work presents an iterative method for homography estimation that requires only a single-point correspondence. The homography parameters are estimated by solving a search problem using particle swarm optimization, by maximizing a match score between a projective transformed fragment of the input image using the estimated homography and a matched filter constructed from the reference image, while minimizing the reprojection error. The proposed method can estimate accurately a homography from a single-point correspondence, in contrast to existing methods, which require at least four points. The effectiveness of the proposed method is tested and discussed in terms of objective measures by processing several synthetic and experimental projective transformed images.
AB - Existing feature-based methods for homography estimation require several point correspondences in two images of a planar scene captured from different perspectives. These methods are sensitive to outliers, and their effectiveness depends strongly on the number and accuracy of the specified points. This work presents an iterative method for homography estimation that requires only a single-point correspondence. The homography parameters are estimated by solving a search problem using particle swarm optimization, by maximizing a match score between a projective transformed fragment of the input image using the estimated homography and a matched filter constructed from the reference image, while minimizing the reprojection error. The proposed method can estimate accurately a homography from a single-point correspondence, in contrast to existing methods, which require at least four points. The effectiveness of the proposed method is tested and discussed in terms of objective measures by processing several synthetic and experimental projective transformed images.
UR - http://www.scopus.com/inward/record.url?scp=85124807731&partnerID=8YFLogxK
U2 - 10.1364/AO.444847
DO - 10.1364/AO.444847
M3 - Artículo
C2 - 35297829
AN - SCOPUS:85124807731
SN - 1559-128X
VL - 61
SP - D63-D74
JO - Applied Optics
JF - Applied Optics
IS - 7
ER -