  The visual observation and tracking of cells and other micrometer-sized
objects has many different biomedical applications. The automation of those
tasks based on computer methods helps in the evaluation of such measurements.
In this work, we present a general purpose algorithm that excels at evaluating
deterministic behavior of micrometer-sized objects. Our concrete application is
the tracking of fast moving objects over large distances along deterministic
trajectories in a microscopic video. Thereby, we are able to determine
characteristic properties of the objects. For this purpose, we use a set of
basic algorithms, including blob recognition, feature-based shape recognition
and a graph algorithm, and combined them in a novel way. An evaluation of the
algorithms performance shows a high accuracy in the recognition of objects as
well as of complete trajectories. Moreover, a direct comparison to a similar
algorithm shows superior recognition rates.
