Estimating the motion of plant root cells from in vivo confocal laser scanning microscopy images |
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Authors: | Timothy J Roberts Stephen J McKenna Cheng-Jin Du Nathalie Wuyts Tracy A Valentine A Glyn Bengough |
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Affiliation: | (4) Department of Computer Science and Engineering, The Chinese University of Hong Kong, |
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Abstract: | Images of cellular structures in growing plant roots acquired using confocal laser scanning microscopy have some unusual properties
that make motion estimation challenging. These include multiple motions, non-Gaussian noise and large regions with little
spatial structure. In this paper, a method for motion estimation is described that uses a robust multi-frame likelihood model
and a technique for estimating uncertainty. An efficient region-based matching approach was used followed by a forward projection
method. Over small timescales the dynamics are simple (approximately locally constant) and the change in appearance small.
Therefore, a constant local velocity model is used and the MAP estimate of the joint probability over a set of frames is recovered.
Occurrences of multiple modes in the posterior are detected, and in the case of a single dominant mode, motion is inferred
using Laplace’e method. The method was applied to several Arabidopsis thaliana root growth sequences with varying levels of success. In addition, comparative results are given for three alternative motion
estimation approaches, the Kanade–Lucas–Tomasi tracker, Black and Anandan’s robust smoothing method, and Markov random field
based methods. |
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Keywords: | |
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