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deral Ministry of Education
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1g of WAVESCAN.
3D PARTICLE TRACKING VELOCIMETRY BASED ON
IMAGE AND OBJECT SPACE INFORMATION
J. Willneff
Institute of Geodesy and Photogrammetry, Swiss Federal Institute of Technology,
8093 Zurich, Switzerland, willneff@geod.baug.ethz.ch
Commission V, ICWG V/III
KEY WORDS: Tracking, Algorithms, Sequences, Multimedia, Measurement, Spatial, Temporal, Close Range
ABSTRACT:
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 hard- and
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
particle images separately. The previous 3D PTV solution at the In
by establishing the spatial and temporal correspondences between
stitute 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 possi
ble 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.
1. INTRODUCTION
For the determination of 3D-velocity fields in flows 3D PTV is
a well-established technique which can be used in various
measurement tasks. In comparison to some other flow
measurement techniques 3D PTV provides the Eulerian as well
the Lagrangian representation of the flow field. The existing 3D
PTV solution developed 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 combined use of image and object space based
information including a prediction of the particle motion is
leading to enhanced results in the velocity field determination.
The most important result from this work is a substantial
increase of the tracking rate in 3D PTV. This is of importance
mainly in the context of a Lagrangian analysis of particle
trajectories, which can be considered the actual domain of the
technique. A reliable Lagrangian flow analysis requires long
particle trajectories as integral time and length scales can only
be determined if long correlation lengths have been recorded.
But not only the length of the trajectories is important, also the
number of simultaneous trajectories should be large enough to
form a sufficient basis for a statistical analysis. Due to
interruptions of particle trajectories caused by unsolved
ambiguities the number of long trajectories decreases
exponentially with the trajectory length.
Very long trajectories over hundred and more time instances
could so far only be determined if the probability of ambiguities
is reduced by a low seeding density, thus concurrently reducing
the spatial resolution of the system and the basis for a statistical
analysis. 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.
Within the framework of a research project of the Swiss
National Science Foundation a new spatio-temporal matching
algorithm was developed and implemented. The technique has
reached a status of an operational and reliable measurement tool
used in hydrodynamics and space applications (Becker et al,
1995; Maas et al, 1997; Willneff and Maas, 2000).
2. HARDWARE SETUP
The technique is based on the recording of synchronous image
sequences of a flow visualized with small, neutrally buoyant
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