### Abstract

Language | English |
---|---|

Journal | Journal of Electronic Imaging |

Volume | 14 |

Issue number | 3:0330 |

DOIs | |

Publication status | Published - Aug 2005 |

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**Diffusion Constructs in Optical Flow Computation.** / Condell, J; Scotney, BW; Morrow, PJ.

Research output: Contribution to journal › Article

TY - JOUR

T1 - Diffusion Constructs in Optical Flow Computation

AU - Condell, J

AU - Scotney, BW

AU - Morrow, PJ

PY - 2005/8

Y1 - 2005/8

N2 - 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.

AB - 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.

UR - http://spie.org/app/Publications/index.cfm?fuseaction=journals&type=jei

U2 - 10.1117/1.2039091

DO - 10.1117/1.2039091

M3 - Article

VL - 14

JO - Journal of Electronic Imaging

T2 - Journal of Electronic Imaging

JF - Journal of Electronic Imaging

SN - 1017-9909

IS - 3:0330

ER -