Quasi-Periodic Spatiotemporal Filtering

This paper presents the online estimation of temporal frequency to
simultaneously detect and identify the quasi-periodic motion of an
object. We introduce color to increase discriminative power of a
reoccurring object and to provide robustness to appearance changes due
to illumination changes. Spatial contextual information is incorporated
by considering the object motion at different scales. We combined
spatiospectral Gaussian filters and a temporal reparameterized Gabor
filter to construct the online temporal frequency filter. We
demonstrate the online filter to respond faster and decay faster than
offline Gabor filters. Further, we show the online filter to be more
selective to the tuned frequency than Gabor filters. We contribute to
temporal frequency analysis in that we both identify ("what") and
detect ("when") the frequency. In color video, we demonstrate the
filter to detect and identify the periodicity of natural motion. The
velocity of moving gratings is determined in a real world example. We
consider periodic and quasi-periodic motion of both stationary and
non-stationary objects.