Parametric optical flow without correspondence for moving sensors

Gary E. Whitten

doi:10.1117/12.45463

1 March 1991 Parametric optical flow without correspondence for moving sensors

Gary E. Whitten

Proceedings Volume 1468, Applications of Artificial Intelligence IX; (1991) https://doi.org/10.1117/12.45463
Event: Orlando '91, 1991, Orlando, FL, United States

Abstract

Optical flow fields (which describe image domain motion) extracted from sequences of images acquired with moving sensors have many practical applications including motion analysis, moving target cueing, surface reconstruction and hazard avoidance. It is well known that, for the general optical flow problem, a constraint exists that relates the local change in intensity to image gradient and describes the optical flow component parallel to the gradient. However, the component perpendicular to the gradient is unconstrained, and therefore, the optical flow field can not be determined directly-usually it is necessary to appeal to some other constraint, such as smoothness, which generally requires costly iterative or relaxation techniques. For the special, but important, case of optical flow induced by sensor motion, a model for the motion provides additional constraints. If, in addition, the scene is assumed to be roughly planar, the optical flow can be characterized by six parameters and found directly without iteration or determining correspondence. These parameters can be readily and robustly calculated by performing a least squares fit to data uniformly sampled from the image sequence. We develop the necessary equations and relations, show results of this approach using real imagery and demonstrate that it is applicable to important real problems.

Citation Download Citation

Gary E. Whitten "Parametric optical flow without correspondence for moving sensors", Proc. SPIE 1468, Applications of Artificial Intelligence IX, (1 March 1991); https://doi.org/10.1117/12.45463

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available