부산대학교 도서관

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.