Performance of optical flow techniques
International Journal of Computer Vision
The robust estimation of multiple motions: parametric and piecewise-smooth flow fields
Computer Vision and Image Understanding
Robot Vision
Numerical Recipes in C: The Art of Scientific Computing
Numerical Recipes in C: The Art of Scientific Computing
Hierarchical Estimation and Segmentation of Dense Motion Fields
International Journal of Computer Vision
3D Model Acquisition from Extended Image Sequences
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume II - Volume II
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
On the Spatial Statistics of Optical Flow
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Piecewise-Smooth Dense Optical Flow via Level Sets
International Journal of Computer Vision
Image Deblurring in the Presence of Impulsive Noise
International Journal of Computer Vision
Variational motion segmentation with level sets
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part I
Over-Parameterized Variational Optical Flow
International Journal of Computer Vision
A Variational Model for the Joint Recovery of the Fundamental Matrix and the Optical Flow
Proceedings of the 30th DAGM symposium on Pattern Recognition
Optical Flow Computation from an Asynchronised Multiresolution Image Sequence
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part I
Two Step Variational Method for Subpixel Optical Flow Computation
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Illumination-robust variational optical flow using cross-correlation
Computer Vision and Image Understanding
Variational method for super-resolution optical flow
Signal Processing
Study of strength tests with computer vision techniques
IWINAC'11 Proceedings of the 4th international conference on Interplay between natural and artificial computation: new challenges on bioinspired applications - Volume Part II
Dense versus Sparse Approaches for Estimating the Fundamental Matrix
International Journal of Computer Vision
Asynchronous frameless event-based optical flow
Neural Networks
Over-Parameterized optical flow using a stereoscopic constraint
SSVM'11 Proceedings of the Third international conference on Scale Space and Variational Methods in Computer Vision
Pyramid transform and scale-space analysis in image analysis
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
On performance analysis of optical flow algorithms
Proceedings of the 15th international conference on Theoretical Foundations of Computer Vision: outdoor and large-scale real-world scene analysis
| Hi-index | 0.01 |
We present a readily applicable way to go beyond the accuracy limits of current optical flow estimators. Modern optical flow algorithms employ the coarse to fine approach. We suggest to upgrade this class of algorithms, by adding over-fine interpolated levels to the pyramid. Theoretical analysis of the coarse to over-fine approach explains its advantages in handling flow-field discontinuities and simulations show its benefit for sub-pixel motion. By applying the suggested technique to various multi-scale optical flow algorithms, we reduced the estimation error by 10-30% on the common test sequences. Using the coarse to over-fine technique, we obtain optical flow estimation results that are currently the best for benchmark sequences.