Performance of optical flow techniques
International Journal of Computer Vision
Numerische Isotropieoptimierung von FIR-Filtern mittels Querglättung
Mustererkennung 1997, 19. DAGM-Symposium
A System-Theoretical View on Local Motion Estimation
SSIAI '02 Proceedings of the Fifth IEEE Southwest Symposium on Image Analysis and Interpretation
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
Wiener-optimized discrete filters for differential motion estimation
IWCM'04 Proceedings of the 1st international conference on Complex motion
Fundamental performance limits in image registration
IEEE Transactions on Image Processing
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Differential motion estimation in image sequences is based on measuring the orientation of local structures in spatio-temporal signal volumes. For this purpose, discrete filters which yield estimates of the local gradient are applied to the image sequence. Whereas previous approaches to filter optimization concentrate on the reduction of the systematical error of filters and motion models, the method presented in this paper is based on the statistical characteristics of the data. We present a method for adapting linear shift invariant filters to image sequences or whole classes of image sequences. We show how to simultaneously optimize derivative filters according to the systematical errors as well as to the statistical ones.