Applying Feature Tracking to Particle Image Velocimetry

Digital PIV : A Challenge for Feature Based Tracking 1 )

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 optic...

Digital Particle Image Velocimetry: a challenge for feature based tracking

Particle Image Velocimetry by Feature Tracking

Feature Correlation for Particle Image Velocimetry: An Application of Pattern Recognition

Particle Image Velocimetry (NV) has been used successfully for measuring instantaneous two dimensional velocity fields. Analyzing PIV images involves matching particle images capwred sequentially. In the usual practice, correlation (autoor cross-correlation) is used to find the displacement (hence velocity) of the particles within a large number of small "interrogation areas" in the field of vi...

Analysis 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...