TY - GEN
T1 - Robust Image alignment using third-order global motion estimation
AU - Keller, Y.
AU - Averbuch, A.
N1 - Place of conference:UK
PY - 2005
Y1 - 2005
N2 - The estimation of parametric global motion using non-linear optimization is a fundamental technique
in computer vision. Such schemes are able to recover various motion models (translation, rotation,
affine, projective) with subpixel accuracy. The parametric motion is computed using a first order
Taylor expansions of the registered images. But, it is limited to the estimation of small motions, and
while large translations and rotations can be coarsely estimated by Fourier domain algorithms, no
such techniques exist for affine and projective motions. This paper offers two contributions: First,
we improve the convergence properties by an order of magnitude using a second order Taylor expansion.
A third order convergence rate is achieved, compared to the second order convergence of prior
schemes. Second, we extend the third order algorithm using a symmetrical formulation which further
improves the convergence properties. The results are verified by rigorous analysis and experimental
trials.
AB - The estimation of parametric global motion using non-linear optimization is a fundamental technique
in computer vision. Such schemes are able to recover various motion models (translation, rotation,
affine, projective) with subpixel accuracy. The parametric motion is computed using a first order
Taylor expansions of the registered images. But, it is limited to the estimation of small motions, and
while large translations and rotations can be coarsely estimated by Fourier domain algorithms, no
such techniques exist for affine and projective motions. This paper offers two contributions: First,
we improve the convergence properties by an order of magnitude using a second order Taylor expansion.
A third order convergence rate is achieved, compared to the second order convergence of prior
schemes. Second, we extend the third order algorithm using a symmetrical formulation which further
improves the convergence properties. The results are verified by rigorous analysis and experimental
trials.
UR - https://scholar.google.co.il/scholar?q=Robust+Image+alignment+using+third-order+global+motion+estimation&btnG=&hl=en&as_sdt=0%2C5
M3 - Conference contribution
BT - British Machine Vision Conference (BMVC)
PB - Citeseer
ER -