A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness
Abstract
Tracking by assignment is well suited for tracking a varying number of divisible cells, but suffers from false positive detections. We reformulate tracking by assignment as a chain graph–a mixed directed-undirected probabilistic graphical model–and obtain a tracking simultaneously over all time steps from the maximum a-posteriori configuration. The model is evaluated on two challenging four-dimensional data sets from developmental biology. Compared to previous work, we obtain improved tracks due to an increased robustness against false positive detections and the incorporation of temporal domain knowledge.
Cite
Text
Kausler et al. "A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness." European Conference on Computer Vision, 2012. doi:10.1007/978-3-642-33712-3_11Markdown
[Kausler et al. "A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness." European Conference on Computer Vision, 2012.](https://mlanthology.org/eccv/2012/kausler2012eccv-discrete/) doi:10.1007/978-3-642-33712-3_11BibTeX
@inproceedings{kausler2012eccv-discrete,
title = {{A Discrete Chain Graph Model for 3d+t Cell Tracking with High Misdetection Robustness}},
author = {Kausler, Bernhard X. and Schiegg, Martin and Andres, Björn and Lindner, Martin S. and Köthe, Ullrich and Leitte, Heike and Wittbrodt, Jochen and Hufnagel, Lars and Hamprecht, Fred A.},
booktitle = {European Conference on Computer Vision},
year = {2012},
pages = {144-157},
doi = {10.1007/978-3-642-33712-3_11},
url = {https://mlanthology.org/eccv/2012/kausler2012eccv-discrete/}
}