Driver's face is a rich source of information for understanding driver behaviour. From the driver's face, one could get an idea of the driver's emotional state and where s/he looks at. In recent years, naturalistic driving studies and field operational tests have been conducted to collect driver behavioural data, which often includes video of the driver, from many drivers driving for an extended period of time. Due to the Data Privacy Act, it is desirable to make the driver video anonymous, while preserving the original facial expressions. This report describes our attempt to make a system that could do so. The system consists of two main steps: 1) face analysis and 2) face reconstruction. The face analysis step consists of an automatic Facial Action Coding System (FACS) coder based on Active Appearance Models (AAMs) and a classifier that analyses local deformations in the AAM shape mesh. The output from this step is FACS codes (Action Units) for each frame in the input video sequence, which are then used as an input to the face reconstruction, where the unidentified face is synthesized and visualised, preserving the facial expression of the input video