Images of cellular structures in growing plant roots acquired using confocal laser scanning microscopy (CLSM) have some unusual properties that make motion estimation challenging. These include multiple mo- tions, 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 un- certainty. 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. Occur- rences 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 se- quences 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.