We present an algorithm for underwater robots to
track mobile targets, and specifically human divers, by detecting
periodic motion. Periodic motion is typically associated with
propulsion underwater and specifically with the kicking of
human swimmers. By computing local amplitude spectra in
a video sequence, we find the location of a diver in the robot’s
field of view. We use the Fourier transform to extract the
responses of varying intensities in the image space over time
to detect characteristic low frequency oscillations to identify
an undulating flipper motion associated with typical gaits. In
case of detecting multiple locations that exhibit large lowfrequency
energy reponses, we combine the gait detector with
other methods to eliminate false detections. We present results
of our algorithm on open-ocean video footage of swimming
divers, and also discuss possible extensions and enhancements
of the proposed approach for tracking other objects that exhibit
low-frequency oscillatory motion.