Abstract
Mathematical modeling of the dynamic behavior of physical systems, gives computers that mimic the capabilities to intelligently monitor and predict their evolutionary characteristics. In this paper, we present a system for tracking the time-varying features of non-rigid objects in images of evolving scenes, using the elastic string model of planar contours, which permits the inference and prediction of the quantitative parameters that characterize evolutionary behavior. The goal of our work is to dynamically track non-rigid objects in video sequences, using object alignment techniques based on the properties of the elastic string. We present experimental results of growth cone and neurite tracking in cell growth and motion studies.
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