We proposed spatiotemporal filter velocimetry (SFV) based on a frequency analysis of time-series spatiotemporally-filtered particle images, which conisits of an imaging system using a highspeed camera and a software program for image processing by a computer. Main features of SFV are (1) velocity of a single tracer particle is measurable, so that accuracy, spatial and temporal resolutions can be as high as LDV, (2) simultaneous measurement of two velocity components is possible at arbitrary multiple points in recorded particle images, (3) it is applicable to flows with low concentration of tracer particles, (4) processing conditions such as an interrogation area, a pattern of spatial filter, a shift frequency and a frequency evaluation method can be easily optimized after recording particle images, (5) translational velocity of a pattern such as bubble and wave velocities can be measured and (6) it is applicable to non-rectangular interrogation regions by using coordinate transformation. In this report, we breifly explain the principle of SFV and present several applications of SFV to demonstrate its potential.
