Authors:
Jan Hubený
;
Vladimír Ulman
and
Pavel Matula
Affiliation:
Centre for Biomedical Image Analysis, Faculty of Informatics Masaryk University, Czech Republic
Keyword(s):
Live-cell imaging, motion tracking, 3D imaging, variational optical flow.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Computer Vision, Visualization and Computer Graphics
;
Human-Computer Interaction
;
Matching Correspondence and Flow
;
Methodologies and Methods
;
Motion and Tracking
;
Motion, Tracking and Stereo Vision
;
Pattern Recognition
;
Physiological Computing Systems
Abstract:
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.