3d Particle Tracking Velocimetry Based on Image and Object Space Information

The 3D Particle Tracking Velocimetry (PTV) offers a flexible technique for the determination of velocity fields in flows. In the past decade the successful research work performed by the Institute of Geodesy and Photogrammetry at ETH Zurich led to an operational and reliable measurement tool used in hydrodynamics and space applications. In cooperation with the Institute of Hydromechanics and Water Resources Management at ETH Zurich further progress has been achieved in the improvement of the existing hardand software solutions. Regarding the hardware setup the acquisition system used at the ETH Zurich was upgraded from offline to online image digitization. Major progress was made on the software implementation. Within the framework of a research project of the Swiss National Science Foundation a new spatio-temporal matching algorithm was developed, implemented and tested. In former approaches the reconstruction of the particle trajectories was done in two steps by establishing the spatial and temporal correspondences between particle images separately. The previous 3D PTV solution at the Institute of Geodesy and Photogrammetry applying an object space based tracking algorithm was improved in a way that the redundant information in image and object space is exploited more efficiently. The new method uses a combination of image and object space based information to establish the spatio-temporal correspondences between particle positions of consecutive time steps. The redundant image coordinate observations combined with the prediction for the next particle position should allow the establishment of spatio-temporal connections even when the velocity field has a high density or the movement of the tracer particles is fast. The use of image and object space based information in combination with a prediction of the particle motion was intended to lead to enhanced results in the velocity field determination. In the case of ambiguities particle trajectories are often interrupted for only a few time steps. With the new algorithm these gaps can be bridged reliably and even the continuation of a trajectory is possible when the redundant information is exploited in a correct way. The most important result of this work is a substantial increase of the tracking rate in 3D PTV. A reduction of the trajectory interruptions due to unsolved ambiguities can multiply the yield of long trajectories and thus the usefulness of the results of 3D PTV, which further enlarges the application potential of the technique. Compared to the former implementation the tracking efficiency has been increased up to 40 % depending on the data set. The latest developments of the algorithmic aspects of 3D PTV are described and some examples of the successful application of the method are given in this paper.