This work addresses the Huawei/3DLife Grand Challenge, presenting a novel method for the analysis of dance movements. The approach focuses on the decomposition of the dance movements into elementary motions. Placing this problem into a probabilistic framework, we propose to exploit Gaussian processes to accurately model the different components of the decomposition. The preliminary results, presented in this paper, are very promising. In particular, two applications are considered, illustrating the relevance of the proposed approach, namely the correction of tracking errors and the smoothing of some movements of the teacher to help toward the dance learning.