Performance of optical flow techniques
International Journal of Computer Vision
Numerische Isotropieoptimierung von FIR-Filtern mittels Querglättung
Mustererkennung 1997, 19. DAGM-Symposium
An iterative image registration technique with an application to stereo vision
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 2
Fundamental performance limits in image registration
IEEE Transactions on Image Processing
Signal and noise adapted filters for differential motion estimation
PR'05 Proceedings of the 27th DAGM conference on Pattern Recognition
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
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Differential motion estimation is based on detecting brightness changes in local image structures. Filters approximating the local gradient are applied to the image sequence for this purpose. Whereas previous approaches focus on the reduction of the systematical approximation error of filters and motion models, the method presented in this paper is based on the statistical characteristics of the data. We developed a method for adapting separable linear shift invariant filters to image sequences or whole classes of image sequences. Therefore, it is possible to optimize the filters according to the systematical errors as well as to the statistical ones.