Face recognition in dynamic scenes
Stephen James McKenna, Shaogang Gong, Yogesh Raja · 1997
An integrated system for the acquisition, normalisation and recognition of moving faces in dynamic scenes is introduced. Four face recognition tasks are defined and it is argued that modelling person-specific probability densities in a generic face space using mixture models provides a technique applicable to all four tasks. The use of Gaussian colour mixtures for face detection and tracking is also described. Results are presented using data from the integrated system. 1 Introduction Face recognition in general and the recognition of moving people in natural scenes in particular, require a set of visual tasks to be performed robustly. These include (1) Acquisition: the detection and tracking of face-like image patches in a dynamic scene, (2) Normalisation: the segmentation, alignment and normalisation of the face images, and (3) Recognition: the representation and modelling of face images as identities, and the association of novel face images with known models. These tasks seem to b...