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This paper considers the task of closed curve filtering for visual tracking. Segmentation-based visual tracking strategies provide the closed curve measurements to filter. This paper discusses the derivation of a local, linear description for planar curve variation and curve uncertainty. It consists of a family of non-intersecting trajectories transverse to a given curve. Along one of the single-dimensional...
Online contour-based tracking is considered through the estimation perspective. We propose a recursive dynamic filtering solution to the tracking problem. The state of the target is described by a pose state which represents the ensemble movement and a shape state which represents the local deformations. The shape state of the filter is described implicitly by a probability field with prediction and...
This paper proposes a procedure to characterize segmentation-based visual tracking performance with respect to imaging noise. It identifies how imaging noise affects the target segmentation as measured through local shape metrics (Sobolev and Laplace metrics). Such a procedure would be an important calibration step prior to implementing a visual tracking filter for a given need. We utilize the Bhattacharyya...
Imaging mass spectrometry can be used to reveal spatial distributions of multiple molecular species in a 2D biological sample. Due to the large amount of data produced by this technology, it is difficult and time-consuming to manually extract meaningful results from imaging mass spectrometry experimentation. We have developed and implemented an original approach to easily and consistently process...
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