Tracking talking faces with shape and appearance models

This paper presents a system that can recover and track the 3D speech movements of a speaker’s face for each image of a monocular sequence. To handle both the individual specificities of the speaker’s articulation and the complexity of the facial deformations during speech, speaker-specific articulated models of the face geometry and appearance are first built from real data. These face models are used for tracking: articulatory parameters are extracted for each image by an analysis-by-synthesis loop. The geometric model is linearly controlled by only seven articulatory parameters. Appearance is seen either as a classical texture map or through local appearance of a relevant subset of 3D points. We compare several appearance models: they are either constant or depend linearly on the articulatory parameters. We compare tracking results using these different appearance models with ground truth data not only in terms of recovery errors of the 3D geometry but also in terms of intelligibility enhancement provided by the movements.