IEEE Transactions on Pattern Analysis and Machine Intelligence
Computation of component image velocity from local phase information
International Journal of Computer Vision
Three-dimensional computer vision: a geometric viewpoint
Three-dimensional computer vision: a geometric viewpoint
Performance of optical flow techniques
International Journal of Computer Vision
Determination of optical flow and its discontinuities using non-linear diffusion
ECCV '94 Proceedings of the third European conference on Computer Vision (Vol. II)
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Computation and analysis of image motion: a synopsis of current problems and methods
International Journal of Computer Vision
A mathematical study of the relaxed optical flow problem in the space BV(&OHgr;)
SIAM Journal on Mathematical Analysis
Computing optical flow via variational techniques
SIAM Journal on Applied Mathematics
Reliable Estimation of Dense Optical Flow Fields with Large Displacements
International Journal of Computer Vision
Images as Embedded Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images
International Journal of Computer Vision - Special issue on computer vision research at the Technion
Dense Estimation of Fluid Flows
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion
International Journal of Computer Vision
Diffusions and Confusions in Signal and Image Processing
Journal of Mathematical Imaging and Vision
Variational Optic Flow Computation with a Spatio-Temporal Smoothness Constraint
Journal of Mathematical Imaging and Vision
Probabilistic Detection and Tracking of Motion Boundaries
International Journal of Computer Vision - Special issue on Genomic Signal Processing
Optical-Flow Estimation while Preserving Its Discontinuities: A Variational Approach
ACCV '95 Invited Session Papers from the Second Asian Conference on Computer Vision: Recent Developments in Computer Vision
Motion Competition: Variational Integration of Motion Segmentation and Shape Regularization
Proceedings of the 24th DAGM Symposium on Pattern Recognition
Motion Competition: A Variational Approach to Piecewise Parametric Motion Segmentation
International Journal of Computer Vision
Highly Accurate Optic Flow Computation with Theoretically Justified Warping
International Journal of Computer Vision
A General Framework and New Alignment Criterion for Dense Optical Flow
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
A Low Dimensional Fluid Motion Estimator
International Journal of Computer Vision
Efficient Beltrami flow using a short time kernel
Scale Space'03 Proceedings of the 4th international conference on Scale space methods in computer vision
A variational framework for image segmentation combining motion estimation and shape regularization
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Variational motion segmentation with level sets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
A general framework for low level vision
IEEE Transactions on Image Processing
Dense estimation and object-based segmentation of the optical flow with robust techniques
IEEE Transactions on Image Processing
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
A Class of Generalized Laplacians on Vector Bundles Devoted to Multi-Channel Image Processing
Journal of Mathematical Imaging and Vision
Hi-index | 0.00 |
We evaluate the dense optical flow between two frames via variational approach. In this paper, a new framework for deriving the regularization term is introduced giving a geometric insight into the action of a smoothing term. The framework is based on the Beltrami paradigm in image denoising. It includes a general formulation that unifies several previous methods. Using the proposed framework we also derive two novel anisotropic regularizers incorporating a new criterion that requires co-linearity between the gradients of optical flow components and possibly the intensity gradient. We call this criterion "alignment" and reveal its existence also in the celebrated Nagel and Enkelmann's formulation. It is shown that the physical model of rotational motion of a rigid body, pure divergent/convergent flow and irrotational fluid flow, satisfy the alignment criterion in the flow field. Experimental tests in comparison to a recently published method show the capability of the new criterion in improving the optical flow estimations.