A Liquid Crystal Tunable Filter (LCTF) camera could form part of an inexpensive system for color-aided target
tracking; however, the standard tracking techniques will need to be adapted to the cyclic color information where
only one wavelength is measured each timestep. A bayesian multi-hypothesis tracking algorithm is well adapted
for this scenario, as it allows for track association decisions to be delayed until complete spectra are gathered.
The design and tuning of bayesian multi-hypothesis tracker will be described and its behavior demonstrated for
a scenario in which a fixed-mounted LCTF camera is used in vehicle tracking.