Real-time subject-specific head and facial mimic animation system using a contactless kinect sensor and system of systems approach
Résumé
Facial palsies due to stroke, accidental and sportive injuries or sometimes without etiology, affect the professional and personal lives of involved patients. These disorders are not only a functional handicap but also a social integration impairment. The recovery of facial mimics with a normal and symmetrical facial expression allows involved patients to improve their living conditions and social identity. Current approaches lack of visual feedbacks. To monitor facial mimics and head movements in a quantitative and objective manners, a computer-aided animation system needs to be developed. Numerous systems have been proposed using single camera, stereo camera, 3-D scanner, and Kinect approaches. In particular, Kinect contactless sensor has been proven to be very suitable for 3-D facial simulation applications. However, little studies have employed the Kinect sensor for real-time head animation applications. Consequently, this study developed a real-time head and facial mimic animation system using the contactless Kinect sensor and the system of systems approach. To evaluate the accuracy of the subject-specific Kinect-based geometrical models, magnetic resonance imaging (MRI) data were used. As results, the mean distance deviation between generated Kinect-based and reconstructed MRI-based geometrical head models are approximately 1 mm for two tested subjects. The generation times are 9.7 s +/- 0.3 and 0.046 s +/- 0.005 by using the full facial landmarks and MPEG-4 facial landmarks respectively. Real-time head and facial mimic animations were illustrated. Particularly, the system could be executed at a very high framerate (60 fps). Further developments relate to the integration of texture information and internal structures such as a skull and muscle network to develop a full subject specific head and facial mimic animation system for facial mimic rehabilitation.