Classification of optical flow by constraints

Authors:
Yusuke Kameda;Atsushi Imiya
Affiliations:
School of Science and Technology, Chiba University, Japan;Institute of Media and Information Technology, Chiba University, Japan
Venue:
CAIP'07 Proceedings of the 12th international conference on Computer analysis of images and patterns
Year:
2007

Citing 8
Cited 1

On the estimation of optical flow: relations between different approaches and some new results

Artificial Intelligence
A vector spline approximation

Journal of Approximation Theory
Performance of optical flow techniques

International Journal of Computer Vision
Computational anatomy: an emerging discipline

Quarterly of Applied Mathematics - Special issue on current and future challenges in the applications of mathematics
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint

Journal of Mathematical Imaging and Vision
Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)

Mathematical Problems in Image Processing: Partial Differential Equations and the Calculus of Variations (Applied Mathematical Sciences)
Approximation of vectors fields by thin plate splines with tension

Journal of Approximation Theory
Variational approach to cardiac motion estimation for small animals in tagged magnetic resonance imaging

PSIVT'06 Proceedings of the First Pacific Rim conference on Advances in Image and Video Technology

Hierarchical properties of multi-resolution optical flow computation

ECCV'12 Proceedings of the 12th international conference on Computer Vision - Volume 2

Quantified Score

Hi-index	0.00

Visualization

Abstract

In this paper, we analyse mathematical properties of spatial optical-flow computation algorithm. First by numerical analysis, we derive the convergence property on variational optical-flow computation method used for cardiac motion detection. From the convergence property of the algorithm, we clarify the condition for the scheduling of the regularisation parameters. This condition shows that for the accurate and stable computation with scheduling the regularisation coefficients, we are required to control the sampling interval for numerical computation.