Digital PIV : A Challenge for Feature Based Tracking 1 )
نویسنده
چکیده
Motion tracking is an important step of the analysis of ow image sequences. However, Particle Image Velocimetry (PIV) techniques rarely use tracking methods developed in computer vision, they usually work with FFT and correlation based methods. Two major types of motion estimation algorithms exist: the optical ow and the feature based ones. Promising results have been obtained by applying optical ow techniques to PIV. The applicability of feature based tracking algorithms to PIV images is examined in this article. Two feature based and one optical ow based tracking algorithms are considered. Flow measurement and visualisation results for standard PIV sequences are presented. The aim of this work is to investigate the applicability and eeciency of the feature based tracking algorithms in ow velocity measurement. Flow visualisation and measurement of ow dynamics are important tasks appearing in the analysis and understanding of combustion processes, aeronautical phenomena, ame propagation, heat exchange problems, construction of artiicial heart pumps, etc. 8]. In particle image velocimetry applications, the uid is seeded with particles that follow the ow and eeciently scatter light. The uid is illuminated by a two-dimensional light sheet (laser beam). Conventionally, multiple exposure cameras are used to capture images of the ow at diierent time instants, and the images are recorded on photographic lm. By optical correlation methods applied point-by-point to the entire negative, the in-plane velocity of the particles between two consecutive images is determined. The obtained velocity eld is then used to estimate the instantaneous dynamics of the local uid.
منابع مشابه
Comparison of Tracking Techniques Applied to Digital PIV
Digital Particle Image Velocimetry (DPIV) aims at flow visualisation and measurement of flow dynamics in numerous applications, including hydrodynamics, combustion processes and aeronautical phenomena. The fluid is seeded with particles that follow the flow and efficiently scatter light. Traditionally, FFT-based correlation techniques have been used to estimate the displacements of the particle...
متن کاملDisplacement monitoring of a Long-Span Arch Railway Bridge using Digital Image Correlation (DIC)
There is an escalating demand for condition monitoring enhancement of transport infrastructures worldwide. Bridges are of vital importance in transportation infrastructure and need such monitoring. In this research, a non-contact vision-based technique called Digital Image Correlation (DIC) was used to calculate the bridge displacements. A high frame rate camera with 4K capability was used for ...
متن کاملApplying Feature Tracking to Particle Image Velocimetry
Particle Image Velocimetry (PIV) is a popular approach to flow visualisation and measurement in hydroand aerodynamic studies and applications [7]. The fluid is seeded with particles that follow the flow and make it visible. Traditionally, correlation techniques have been used to estimate the displacements of the particles in a digital PIV sequence. Recently, we have successfully applied to PIV ...
متن کاملAnalysis and Synthesis of Facial Expressions by Feature-Points Tracking and Deformable Model
Face expression recognition is useful for designing new interactive devices offering the possibility of new ways for human to interact with computer systems. In this paper we develop a facial expressions analysis and synthesis system. The analysis part of the system is based on the facial features extracted from facial feature points (FFP) in frontal image sequences. Selected facial feature poi...
متن کامل