Recognizing Facial Expressions in Image Sequences Using Local Parameterized Models of Image Motion
International Journal of Computer Vision
Face Recognition: Features Versus Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
Detection and Tracking of Facial Features in Video Sequences
MICAI '00 Proceedings of the Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Human Action Tracking Guided by Key-Frames
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Face recognition: A literature survey
ACM Computing Surveys (CSUR)
Recovering 3D Human Body Configurations Using Shape Contexts
IEEE Transactions on Pattern Analysis and Machine Intelligence
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This paper explores a novel endeavor of deploying only four active-tracking cameras and fundamental vision-based technologies for 3D motion capture of a full human body figure, which includes facial expression, motion of fingers of both hands and a whole body. The proposed methods suggest alternatives to extract motion parameters of the mentioned body parts from four single-view image sequences. The proposed ellipsoidal model- and flow-based facial expression motion capture solution tackles both 3D head pose and non-rigid facial motion effectively and we observe that a set of 22 self-defined feature points suffice the expression representation. The body figure and fingers motion capture is solved with a combination of articulated model and flow-based methods.