Diffusion constructs in optical flow computation
1 July 2005 Diffusion constructs in optical flow computation
Joan V. Condell, Bryan W. Scotney, Philip J. Morrow
Author Affiliations +
Abstract
We develop techniques for the implementation of motion estimation. Optical flow estimation has been proposed as a preprocessing step for many high-level vision algorithms. Gradient-based approaches compute the spatio-temporal derivatives, differentiating the image with respect to time and thus computing the optical flow field. Horn and Schunck's method in particular is considered a benchmarking algorithm of gradient-based differential methods, useful and powerful, yet simple and fast. They formulated an optical flow constraint equation from which to compute optical flow, which cannot fully determine the flow but can give the component of the flow in the direction of the intensity gradient. An additional constraint must be imposed, introducing a supplementary assumption to ensure a smooth variation in the flow across the image. The brightness derivatives involved in the equation system were estimated by Horn and Schunck using first differences averaging. Gradient-based methods for optical flow computation can suffer from unreliability of the image flow constraint equation in areas of an image where local brightness function is nonlinear or where there are rapid spatial or temporal changes in the intensity function. Little and Verri suggested regularization to help the numerical stability of the solution. Usually this takes the form of smoothing of the function or surface by convolving before the derivative is taken. Smoothing has the effects of suppressing noise and ensuring differentiability of discontinuities. The method proposed is a finite element method, based on a triangular mesh, in which diffusion is added into the system of equations.
©(2005) Society of Photo-Optical Instrumentation Engineers (SPIE)
Joan V. Condell, Bryan W. Scotney, and Philip J. Morrow "Diffusion constructs in optical flow computation," Journal of Electronic Imaging 14(3), 033008 (1 July 2005). https://doi.org/10.1117/1.2039091
Published: 1 July 2005
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Diffusion

Tolerancing

Chemical elements

Optical flow

Image processing

Error analysis

Motion estimation

RELATED CONTENT

Monocular visual odometry-based 3D-2D motion estimation
Proceedings of SPIE (February 19 2018)
Motion estimation with diffusion
Proceedings of SPIE (March 19 2003)
Structure of the spectrograph ESOPO
Proceedings of SPIE (July 11 2008)
The cost of tolerancing
Proceedings of SPIE (August 28 2009)

Back to Top