%0 Book Section %1 noKey %A Kondermann, Claudia %A Mester, Rudolf %A Garbe, Christoph %B Computer Vision – ECCV 2008 %D 2008 %E Forsyth, David %E Torr, Philip %E Zisserman, Andrew %I Springer Berlin Heidelberg %K evaluation optical_flow performance %P 290-301 %R 10.1007/978-3-540-88690-7_22 %T A Statistical Confidence Measure for Optical Flows %U http://dx.doi.org/10.1007/978-3-540-88690-7_22 %V 5304 %X Confidence measures are crucial to the interpretation of any optical flow measurement. Even though numerous methods for estimating optical flow have been proposed over the last three decades, a sound, universal, and statistically motivated confidence measure for optical flow measurements is still missing. We aim at filling this gap with this contribution, where such a confidence measure is derived, using statistical test theory and measurable statistics of flow fields from the regarded domain. The new confidence measure is computed from merely the results of the optical flow estimator and hence can be applied to any optical flow estimation method, covering the range from local parametric to global variational approaches. Experimental results using state-of-the-art optical flow estimators and various test sequences demonstrate the superiority of the proposed technique compared to existing ’confidence’ measures. %@ 978-3-540-88689-1

@incollection{noKey, abstract = {Confidence measures are crucial to the interpretation of any optical flow measurement. Even though numerous methods for estimating optical flow have been proposed over the last three decades, a sound, universal, and statistically motivated confidence measure for optical flow measurements is still missing. We aim at filling this gap with this contribution, where such a confidence measure is derived, using statistical test theory and measurable statistics of flow fields from the regarded domain. The new confidence measure is computed from merely the results of the optical flow estimator and hence can be applied to any optical flow estimation method, covering the range from local parametric to global variational approaches. Experimental results using state-of-the-art optical flow estimators and various test sequences demonstrate the superiority of the proposed technique compared to existing ’confidence’ measures.}, added-at = {2013-10-22T16:25:03.000+0200}, author = {Kondermann, Claudia and Mester, Rudolf and Garbe, Christoph}, biburl = {https://www.bibsonomy.org/bibtex/2fc0947f345da06b97f0494a7d30598db/alex_ruff}, booktitle = {Computer Vision – ECCV 2008}, description = {A Statistical Confidence Measure for Optical Flows - Springer}, doi = {10.1007/978-3-540-88690-7_22}, editor = {Forsyth, David and Torr, Philip and Zisserman, Andrew}, interhash = {8f32c04649e09a0c7a48f92942b86585}, intrahash = {fc0947f345da06b97f0494a7d30598db}, isbn = {978-3-540-88689-1}, keywords = {evaluation optical_flow performance}, pages = {290-301}, publisher = {Springer Berlin Heidelberg}, series = {Lecture Notes in Computer Science}, timestamp = {2013-10-22T16:25:03.000+0200}, title = {A Statistical Confidence Measure for Optical Flows}, url = {http://dx.doi.org/10.1007/978-3-540-88690-7_22}, volume = 5304, year = 2008 }