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@inproceedings{1490221,
author = {Akbaş, Cem Emre and Ulman, Vladimír and Maška, Martin and Jug, Florian and Kozubek, Michal},
address = {Switzerland},
booktitle = {Computer Vision – ECCV 2018 Workshops},
doi = {http://dx.doi.org/10.1007/978-3-030-11024-6_34},
edition = {LNCS 11134},
editor = {Laura Leal-Taixé, Stefan Roth},
keywords = {Label fusion; Image annotation; Segmentation labels; Tracking labels},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Switzerland},
isbn = {978-3-030-11023-9},
pages = {446-454},
publisher = {Springer Nature},
title = {Automatic Fusion of Segmentation and Tracking Labels},
url = {https://link.springer.com/chapter/10.1007/978-3-030-11024-6_34},
year = {2019}
}
TY - JOUR
ID - 1490221
AU - Akbaş, Cem Emre - Ulman, Vladimír - Maška, Martin - Jug, Florian - Kozubek, Michal
PY - 2019
TI - Automatic Fusion of Segmentation and Tracking Labels
PB - Springer Nature
CY - Switzerland
SN - 9783030110239
KW - Label fusion
KW - Image annotation
KW - Segmentation labels
KW - Tracking labels
UR - https://link.springer.com/chapter/10.1007/978-3-030-11024-6_34
L2 - https://link.springer.com/chapter/10.1007/978-3-030-11024-6_34
N2 - Labeled training images of high quality are required for developing well-working analysis pipelines. This is, of course, also true for biological image data, where such labels are usually hard to get. We distinguish human labels (gold corpora) and labels generated by computer algorithms (silver corpora). A naturally arising problem is to merge multiple corpora into larger bodies of labeled training datasets. While fusion of labels in static images is already an established field, dealing with labels in time-lapse image data remains to be explored. Obtaining a gold corpus for segmentation is usually very time-consuming and hence expensive. For this reason, gold corpora for object tracking often use object detection markers instead of dense segmentations. If dense segmentations of tracked objects are desired later on, an automatic merge of the detection-based gold corpus with (silver) corpora of the individual time points for segmentation will be necessary. Here we present such an automatic merging system and demonstrate its utility on corpora from the Cell Tracking Challenge. We additionally release all label fusion algorithms as freely available and open plugins for Fiji (https://github.com/xulman/CTC-FijiPlugins).
ER -
AKBA$\backslash$C S, Cem Emre, Vladimír ULMAN, Martin MAŠKA, Florian JUG and Michal KOZUBEK. Automatic Fusion of Segmentation and Tracking Labels. In Laura Leal-Taixé, Stefan Roth. \textit{Computer Vision – ECCV 2018 Workshops}. LNCS 11134. Switzerland: Springer Nature, 2019, p.~446-454. ISBN~978-3-030-11023-9. Available from: https://dx.doi.org/10.1007/978-3-030-11024-6\_{}34.
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