The study of human facial expressions is one of the most challenging domains in pattern research community. Each facial expression is generated by non-rigid object deformations and these deformations are person-dependent. Automatic recognition of facial expressions is a process primarily based on analysis of permanent and transient features of the face, which can be only assessed with errors of some degree. The expression recognition model is oriented on the specification of Facial Action Coding System (FACS) of Ekman and Friesen [Ekman, Friesen 1978]. The hard constraints on the scene processing and recording conditions set a limited robustness to the analysis. In order to manage the uncertainties and lack of information, we set a probabilistic oriented framework up. The goal of the project was to design and implement a system for automatic recognition of human facial expression in video streams. The results of the project are of a great importance for a broad area of applications that relate to both research and applied topics.