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Estimating the motion of plant root cells from in vivo confocal laser scanning microscopy images
Ist Teil von
Machine vision and applications, 2010-10, Vol.21 (6), p.921-939
Ort / Verlag
Berlin/Heidelberg: Springer-Verlag
Erscheinungsjahr
2010
Quelle
SpringerLink
Beschreibungen/Notizen
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.