Abstract

In this paper a description is given of a computationally efficient algorithm, based on the two-dimensional fast Fourier transform (FFT), for the estimation of multiple translational motions from a sequence of images. The proposed algorithm relies on properties of the projection (Radon) transform to reduce the problem from three to two dimensions and is effective in isolating and reliably estimating several superimposed motions in the presence of moderate levels of noise. Furthermore, the reliance of this algorithm on a novel array processing technique for line detection allows for the efficient estimation of the motion parameters. It is shown that while the technique presented herein is not expected to exhibit the same performance as that of comparable techniques based on the three-dimensional FFT, it is an attractive alternative that makes modest sacrifices in performance for gains in computational complexity.

© 1996 Optical Society of America

Full Article  |  PDF Article
OSA Recommended Articles
Noise-insensitive image optimal flow estimation using higher-order statistics

El Mehdi Ismaili Alaoui, Elhassane Ibn-elhaj, and El Houssaine Bouyakhf
J. Opt. Soc. Am. A 26(5) 1212-1220 (2009)

Robust structure from motion estimation using inertial data

Gang Qian, Rama Chellappa, and Qinfen Zheng
J. Opt. Soc. Am. A 18(12) 2982-2997 (2001)

Performance bounds for estimating three-dimensional motion parameters from a sequence of noisy images

Ted J. Broida and Rama Chellappa
J. Opt. Soc. Am. A 6(6) 879-889 (1989)

References

You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Figures (13)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Tables (1)

You do not have subscription access to this journal. Article tables are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Equations (58)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription

Metrics

You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access OSA Member Subscription