Algorithmic improvements for 3D-3C volumetric PTV processing

The study of fluid mechanics benefits greatly from the acquisition of volumetric velocity fields with high spatial and temporal resolution. Volumetric 3-component Velocimetry (V3V^TM) (Pereira et al., EXIF 2000) is one such technique in which multiple high-speed, high-resolution, and low-noise cameras are used to capture the Lagrangian motion of tracer particles distributed throughout a measurement volume. This presentation describes an improved volumetric PTV algorithm building on Dense Particle Identification and Reconstruction (Boomsma and Troolin, Lisbon 2018). Additional feedback loops are utilized to drastically reduce the occurrence of ghost particles. A probabilistic algorithm for solving an assignment problem is presented. This algorithm is utilized for solving both camera and temporal particle correspondences. Time information is used in order to map the unique paths of a large quantity of individual particles resulting in both velocity and acceleration information obtained within a reasonable processing time. A detailed analysis of the algorithms as well as videos of extracted experimental flow fields will be presented and discussed.