In this paper, two methods are proposed to analyse skeleton data recorded by the Kinect v2 sensor using Kalman filter and Tobit Kalman filter in order to minimize the noise of the acquisition device due to occlusions, self occlusions e.t.c. The skeleton data are three-dimensional spatial coordinates that record movements of an individual's joints. The variance of the noise process is estimated using the likelihood function. In order to include into the model restrictive conditions based on the joints displacements per frame, we apply the Tobit Kalman Filter. Experiments on skeleton data show that the Tobit Kalman filter corrects better the noise than the Kalman filter.