Phased Visualization of Facial Expressions Space using FCM Clustering

FCM 클러스터링을 이용한 표정공간의 단계적 가시화

  • 김성호 (상지대학교 컴퓨터정보공학부)
  • Published : 2008.02.28


This paper presents a phased visualization method of facial expression space that enables the user to control facial expression of 3D avatars by select a sequence of facial frames from the facial expression space. Our system based on this method creates the 2D facial expression space from approximately 2400 facial expression frames, which is the set of neutral expression and 11 motions. The facial expression control of 3D avatars is carried out in realtime when users navigate through facial expression space. But because facial expression space can phased expression control from radical expressions to detail expressions. So this system need phased visualization method. To phased visualization the facial expression space, this paper use fuzzy clustering. In the beginning, the system creates 11 clusters from the space of 2400 facial expressions. Every time the level of phase increases, the system doubles the number of clusters. At this time, the positions of cluster center and expression of the expression space were not equal. So, we fix the shortest expression from cluster center for cluster center. We let users use the system to control phased facial expression of 3D avatar, and evaluate the system based on the results.


Facial Motion Capture;Facial Expression Space;Fuzzy Clustering;Phased Visualization;Facial Expression Control


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