Wind has major effect on plants, from growth changes to windbreaks. Therefore, there is a crucial need for non-invasive methods to describe and quantify the complex motion of a plant induced by wind. In this paper two methods based on video sequences analysis are studied. An adaptation of the classical Particle Image Velocimetry method (nat-PIV) is compared with a tracking method based on the optical flow method of Lukas and Kanade, initialized with the features selection method of Shi and Tomasi (ST + KLT). Both methods were benchmarked on an experiment on a walnut tree in open-field conditions submitted to different wind flows at different periods of the year and equipped with 3D magnetic tracking. The metrological assessment was performed in two steps. We first tested if the results given by both methods were significantly different. Secondly, a direct assessment of the two methods versus 3D magnetic tracking was performed. The ST + KLT method proved to be more accurate and robust than nat-PIV one. The outputs of the ST + KLT method are independent of the foliage density, wind velocity and of light gradient intrinsic to outdoor scene. The implementation of ST + KLT method developed for this study in Matlab is freely available.