In this paper we present an integrated system for face detection, tracking and recognition in complex scenes. The face detector is based on colour skin models, with adaptation to cope with non-stationary colour distributions over time. The face model is tracked along the sequence with a particle filter by comparing its colour histogram with the colour histogram of the sample position by means of the Bhattacharyya coefficient. Face identification is based on statistical deformable models, as Active Shape Models (ASM) and Active Appearance Models (AAM) for feature extraction and a multiclass Support Vector Machine as classifier. We have tested both models with a database of 100 faces verifying the best performance of the AAM model compared with the ASM model.