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A Unified Theory for Steerable and Quadrature Filters.

K. Krajsek, and R. Mester. VISIGRAPP (Selected Papers), volume 4 of Communications in Computer and Information Science, page 201-214. Springer, (2006)

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Univ. -Prof. Dr. -Ing. Kai Hufendiek University of Stuttgart

Kai Waldner University of Stuttgart

Dr. Florian Kaiser University of Stuttgart

Manuel Kaiser University of Stuttgart

Robin Kaißner University of Stuttgart

Other publications of authors with the same name

Wiener-Optimized Discrete Filters for Differential Motion Estimation.K. Krajsek, and R. Mester. IWCM, volume 3417 of Lecture Notes in Computer Science, page 30-41. Springer, (2004)An Online Algorithm for Efficient and Temporally Consistent Subspace Clustering.V. Zografos, K. Krajsek, and B. Menze. ACCV (1), volume 10111 of Lecture Notes in Computer Science, page 353-368. Springer, (2016)A Maximum Likelihood Estimator for Choosing the Regularization Parameters in Global Optical Flow Methods.K. Krajsek, and R. Mester. ICIP, page 1081-1084. IEEE, (2006)Likelihood Functions for Errors-in-variables Models - Bias-free Local Estimation with Minimum Variance.K. Krajsek, C. Heinemann, and H. Scharr. VISAPP (3), page 270-279. SciTePress, (2014)Bayesian Model Selection for Optical Flow Estimation.K. Krajsek, and R. Mester. DAGM-Symposium, volume 4713 of Lecture Notes in Computer Science, page 142-151. Springer, (2007)A Riemannian approach for estimating orientation distribution function (ODF) images from high-angular resolution diffusion imaging (HARDI).K. Krajsek, and H. Scharr. CVPR, page 1019-1026. IEEE Computer Society, (2012)Probabilistic models and estimation: theoretical concepts for variational approaches to computer vision.K. Krajsek. Goethe University Frankfurt am Main, (2015)A Riemannian Bayesian Framework for Estimating Diffusion Tensor Images.K. Krajsek, M. Menzel, and H. Scharr. International Journal of Computer Vision, 120 (3): 272-299 (2016)A Unified Theory for Steerable and Quadrature Filters.K. Krajsek, and R. Mester. VISIGRAPP (Selected Papers), volume 4 of Communications in Computer and Information Science, page 201-214. Springer, (2006)Diffusion filtering without parameter tuning: Models and inference tools.K. Krajsek, and H. Scharr. CVPR, page 2536-2543. IEEE Computer Society, (2010)