IEEE Transactions on Pattern Analysis and Machine Intelligence
Meeting people vitually: experiments in shared virtual environments
The social life of avatars
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
MPEG-4 Facial Animation: The Standard, Implementation and Applications
MPEG-4 Facial Animation: The Standard, Implementation and Applications
Geometry-Driven Photorealistic Facial Expression Synthesis
IEEE Transactions on Visualization and Computer Graphics
Parameterized facial expression synthesis based on MPEG-4
EURASIP Journal on Applied Signal Processing
Simplified facial animation control utilizing novel input devices: a comparative study
Proceedings of the 14th international conference on Intelligent user interfaces
Impact of Expressive Wrinkles on Perception of a Virtual Character's Facial Expressions of Emotions
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Facial action recognition for facial expression analysis from static face images
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Many approaches to the analysis and synthesis of facial expressions rely on automatically tracking landmark points on human faces. However, this approach is usually chosen because of ease of tracking rather than its ability to convey affect. We have conducted an experiment that evaluated the perceptual importance of 22 such automatically tracked feature points in a mental state recognition task. The experiment compared mental state recognition rates of participants who viewed videos of human actors and synthetic characters (physical android robot, virtual avatar, and virtual stick figure drawings) enacting various facial expressions. All expressions made by the synthetic characters were automatically generated using the 22 tracked facial feature points on the videos of the human actors. Our results show no difference in accuracy across the three synthetic representations, however, all three were less accurate than the original human actor videos that generated them. Overall, facial expressions showing surprise were more easily identifiable than other mental states, suggesting that a geometric approach to synthesis may be better suited toward some mental states than others.