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 International Conference on Complex Systems (ICCS2007)

Methods of Motion Path Reconstruction with Uncertain Position Data

Edward Marcus
Marcus Laboratories USA

     Full text: Not available
     Last modified: October 24, 2007

Abstract
Methods of Motion Path Reconstruction with Uncertain Position Data

Natural examples of motion path reconstruction are abundant, and include cells translating through a microscope field, DNA sequence reconstructions, and ultrasound motion detection of moving cardiac tissues. In practice, when detected positions (or data strands) are fuzzy, a method to reconstruct these uncertainties into connected paths over time can be performed with single or multiple time-point steps. With single time-point stepping, path continuation is shown to encounter some error when particles collide, or become temporarily lost.

We are investigating new methods to improve single step continuation results with an extension to multiple time-point steps. With new methods, each particle’s detected positions over a multi-step interval form a combination of candidate path connections. These path connection combinations are then constructed into a branching data tree. On the tree, one particle is physically constrained to connect to only one branch - rendering some particle-to-path connections of the formulated tree to be mutually exclusive. If these conflicting motion combinations can be assessed in near real time, we anticipate substantial improvements to path reconstruction accuracies can be achieved.







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