An adaptive confidence measure for optical flows based on linear subspace projections

Authors:
Claudia Kondermann;Daniel Kondermann;Bernd Jähne;Christoph Garbe
Affiliations:
Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany;Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany;Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany;Interdisciplinary Center for Scientific Computing, University of Heidelberg, Germany
Venue:
Proceedings of the 29th DAGM conference on Pattern recognition
Year:
2007

Citing 11
Cited 6

Multidimensional Orientation Estimation with Applications to Texture Analysis and Optical Flow

IEEE Transactions on Pattern Analysis and Machine Intelligence
Performance of optical flow techniques

International Journal of Computer Vision
On benchmarking optical flow

Computer Vision and Image Understanding - Special issue on empirical evaluation of computer vision algorithms
A Theoretical Framework for Convex Regularizers in PDE-Based Computation of Image Motion

International Journal of Computer Vision
The Minors of the Structure Tensor

Mustererkennung 2000, 22. DAGM-Symposium
Learning Parameterized Models of Image Motion

CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
Highly Accurate Optic Flow Computation with Theoretically Justified Warping

International Journal of Computer Vision
Knowledge Based Image Enhancement Using Neural Networks

ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 03
Optimal filters for extended optical flow

IWCM'04 Proceedings of the 1st international conference on Complex motion

Postprocessing of Optical Flows Via Surface Measures and Motion Inpainting

Proceedings of the 30th DAGM symposium on Pattern Recognition
Reconstructing Optical Flow Fields by Motion Inpainting

EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Complex motion models for simple optical flow estimation

Proceedings of the 32nd DAGM conference on Pattern recognition
Control of the Effects of Regularization on Variational Optic Flow Computations

Journal of Mathematical Imaging and Vision
A loop-consistency measure for dense correspondences in multi-view video

Image and Vision Computing
Quality assessment of non-dense image correspondences

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

Quantified Score

Hi-index	0.00

Visualization

Abstract

Confidence measures are important for the validation of optical flow fields by estimating the correctness of each displacement vector. There are several frequently used confidence measures, which have been found of at best intermediate quality. Hence, we propose a new confidence measure based on linear subspace projections. The results are compared to the best previously proposed confidence measures with respect to an optimal confidence. Using the proposed measure we are able to improve previous results by up to 31%.