Abstract-In this paper, a new conditional formulation of classical filtering methods is proposed. This formulation is dedicated to image sequence based tracking. These conditional filters allow solving systems whose measurements and state equation are estimated from the image data. In particular, the model that is considered for point tracking combines a state equation relying on the optical flow constraint and measurements provided by a matching technique. Based on this, two point trackers are derived. The first one is a linear tracker well-suited to image sequences exhibiting global dominant motion. This filter is determined through the use of a new estimator, called the conditional linear minimum variance estimator. The second one is a nonlinear tracker, implemented from a conditional particle filter. It allows tracking of points whose motion may be only locally described. These conditional trackers significantly improve results in some general situations. In particular, they allow dealing with noisy sequences, abrupt changes of trajectories, occlusions and cluttered background.
In this work, we report on electrical and fluid-dynamics studies concerning the flow induced by a sliding discharge (SD). This kind of discharge was created with a three electrode system configuration: one excited with ac and the others with a dc negative voltage. The SD was activated on a quiescent fluid at atmospheric pressure. The flow field induced by the SD was analysed by measurements undertaken with Pitot probes and Schlieren Image Velocimetry. Under the conditions of our experiments two "jet flows", that blown towards the interelectrode space, were induced from the air exposed electrodes. As a consequence of the mutual interaction of these two flows and of the magnitude of each flow, a resulting plume like planar jet of adjustable direction (0-180º) could be formed. A robust control of the axis direction of the plume could be achieved by modifying the ac voltage value.
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