Nonlinear total variation based noise removal algorithms
Proceedings of the eleventh annual international conference of the Center for Nonlinear Studies on Experimental mathematics : computational issues in nonlinear science: computational issues in nonlinear science
An Algorithm for Total Variation Minimization and Applications
Journal of Mathematical Imaging and Vision
Lucas/Kanade meets Horn/Schunck: combining local and global optic flow methods
International Journal of Computer Vision
An Improved Algorithm for TV-L1 Optical Flow
Statistical and Geometrical Approaches to Visual Motion Analysis
Detection and Segmentation of Independently Moving Objects from Dense Scene Flow
EMMCVPR '09 Proceedings of the 7th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition
Illumination-robust variational optical flow with photometric invariants
Proceedings of the 29th DAGM conference on Pattern recognition
A duality based approach for realtime TV-L1 optical flow
Proceedings of the 29th DAGM conference on Pattern recognition
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
On improving the robustness of variational optical flow against illumination changes
Proceedings of the 4th ACM/IEEE international workshop on Analysis and retrieval of tracked events and motion in imagery stream
| Hi-index | 0.00 |
Vision-based motion perception builds primarily on the concept of optical flow. Modern optical flow approaches suffer from several shortcomings, especially in real, non-ideal scenarios such as traffic scenes. Non-constant illumination conditions in consecutive frames of the input image sequence are among these shortcomings. We propose and evaluate the application of intrinsically illumination-invariant census transforms within a dense state-of-the-art variational optical flow computation scheme. Our technique improves robustness against illumination changes, caused either by altering physical illumination or camera parameter adjustments. Since census signatures can be implemented quite efficiently, the resulting optical flow fields can be computed in real-time.