  We describe and characterize a method for estimating the pressure field
corresponding to velocity field measurements, such as those obtained by using
particle image velocimetry. The pressure gradient is estimated from a time
series of velocity fields for unsteady calculations or from a single velocity
field for quasi-steady calculations. The corresponding pressure field is
determined based on median polling of several integration paths through the
pressure gradient field in order to reduce the effect of measurement errors
that accumulate along individual integration paths. Integration paths are
restricted to the nodes of the measured velocity field, thereby eliminating the
need for measurement interpolation during this step and significantly reducing
the computational cost of the algorithm relative to previous approaches. The
method is validated by using numerically-simulated flow past a stationary,
two-dimensional bluff body and a computational model of a three-dimensional,
self-propelled anguilliform swimmer to study the effects of spatial and
temporal resolution, domain size, signal-to-noise ratio, and out-of-plane
effects. Particle image velocimetry measurements of a freely-swimming jellyfish
medusa and a freely-swimming lamprey are analyzed using the method to
demonstrate the efficacy of the approach when applied to empirical data.
