"Estimating Large Local Motion in Live-Cell Imaging Using Variational Optical Flow" . "Estimating Large Local Motion in Live-Cell Imaging Using Variational Optical Flow"@en . . "Barcelona, Spain" . "3"^^ . . "RIV/00216224:14330/07:00020059" . "14330" . "Portugal" . . "Huben\u00FD, Jan" . "P(GD102/05/H050), P(LC535), Z(MSM0021622419)" . "VISAPP 2007 Second International Conference On Computer Vision Theory And Applications, Proceedings" . "3"^^ . "420461" . . . . "RIV/00216224:14330/07:00020059!RIV10-GA0-14330___" . "978-972-8865-74-0" . "[F2E67C50CB47]" . "live-cell imaging motion tracking 3D imaging variational optical flow"@en . . "000250107900082" . . . "2007-03-08+01:00"^^ . . "Estimating Large Local Motion in Live-Cell Imaging Using Variational Optical Flow" . . . . "INSTICC PRESS" . . . . . "7"^^ . "Ulman, Vladim\u00EDr" . . . "The paper studies the application of state-of-the-art variational optical flow methods for motion tracking of fluorescently labeled targets in living cells. Four variants of variational optical flow methods suitable for this task are briefly described and evaluated in terms of the average angular error. Artificial ground-truth image sequences were generated for the purpose of this evaluation. The aim was to compare the ability of those methods to estimate local divergent motion and their suitability for data with combined global and local motion. Parametric studies were performed in order to find the most suitable parameter adjustment. It is shown that a selected optimally tuned method tested on real 3D input data produced satisfactory results. Finally, it is shown that by using appropriate numerical solution, reasonable computational times can be achieved even for 3D image sequences."@en . "Matula, Pavel" . "Estimating Large Local Motion in Live-Cell Imaging Using Variational Optical Flow"@en . "The paper studies the application of state-of-the-art variational optical flow methods for motion tracking of fluorescently labeled targets in living cells. Four variants of variational optical flow methods suitable for this task are briefly described and evaluated in terms of the average angular error. Artificial ground-truth image sequences were generated for the purpose of this evaluation. The aim was to compare the ability of those methods to estimate local divergent motion and their suitability for data with combined global and local motion. Parametric studies were performed in order to find the most suitable parameter adjustment. It is shown that a selected optimally tuned method tested on real 3D input data produced satisfactory results. Finally, it is shown that by using appropriate numerical solution, reasonable computational times can be achieved even for 3D image sequences." .