Construction and visualisation of three-dimensional facial statistics

This paper presents a new method for the construction of three-dimensional (3D) probabilistic facial averages and demonstrates the potential for applications in clinical craniofacial research and patient assessment. Averages are constructed from a database of registered laser-range scans and photographic images using feature based image warping. Facial features are extracted using a template of connected contours, adapted to each subject interactively using snakes. Each subject's images are warped to the average template shape and the mean depth, colour and covariance matrix is found at each point. Statistical comparison of individuals with an average or between two averages is visualised by converting the probabilities to a coloured texture map.