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Note: Research in this publication was not performed at Janelia.
Object tracking is essential for a multitude of biomedical re- search projects. Automated methods are desired in order to avoid im- possible amounts of manual tracking efforts. However, automatically found solutions are not free of errors, and these errors again have to be identified and resolved manually. We propose six innovative ways for semi-automatic curation of automatically found tracking solutions. Respective user interactions are six simple operations: Inclusion and ex- clusion of objects and tracking decisions, specification of the number of objects, and one-click altering of object segmentations. We show how all proposed interactions can be elegantly incorporated into “assignment models” [1,2,3,4,5,6], an innovative and increasingly popular tracking paradigm. Given some user interaction, the tracking engine is capable of computing the respective globally optimal tracking solution efficiently, even benefitting from “warm start”-capabilities. We show that after in- teractively pointing at a single mistake, multiple segmentation and track- ing errors can be fixed automatically in one single re-evaluation, provably leading to the new, feedback-conscious global optimum.