 
Summary: Efficient Annotation of Vesicle Dynamics
in Video Microscopy
Leandro Corte´s, Student Member, IEEE, and Yali Amit, Member, IEEE
AbstractWe describe an algorithm for the efficient annotation of events of interest in video microscopy. The specific application
involves the detection and tracking of multiple possibly overlapping vesicles in total internal reflection fluorescent microscopy images.
A statistical model for the dynamic image data of vesicle configurations allows us to properly weight various hypotheses online. The
goal is to find the most likely trajectories given a sequence of images. The computational challenge is addressed by defining a
sequence of coarsetofine tests, derived from the statistical model, to quickly eliminate most candidate positions at each time frame.
The computational load of the tests is initially very low and gradually increases as the false positives become more difficult to eliminate.
Only at the last step are state variables estimated from a complete timedependent model. Processing time thus mainly depends on
the number of vesicles in the image and not on image size.
Index TermsTracking, object detection, statistical object modeling, coarsetofine computation, multiple object configurations,
fluorescence microscopy.
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1 INTRODUCTION
MODERN light microscopy can be coupled with digital
recording to produce large data sets which must often
be searched for specific organelles or sequences of events.
We were faced with a problem of this typethe identifica
tion in movies of vesicles that fuse to the cell membrane [23].
