Simultaneous eye tracking and blink detection with interactive particle filters
EURASIP Journal on Advances in Signal Processing
An eye localization, tracking and blink pattern recognition system: Algorithm and evaluation
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
ICIC'09 Proceedings of the 5th international conference on Emerging intelligent computing technology and applications
Blink and wink detection for mouse pointer control
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
Combined head, lips, eyebrows, and eyelids tracking using adaptive appearance models
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Hierarchical On-line Appearance-Based Tracking for 3D head pose, eyebrows, lips, eyelids and irises
Image and Vision Computing
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Previous research in automatic facial expression recognition has been limited to recognition of gross expression categories (e.g., joy or anger) in posed facial behavior under well-controlled conditions (e.g., frontal pose and minimal out-of-plane head motion). We have developed a system that detects discrete and important facial actions, (e.g., eye blinking), in spontaneously occurring facial behavior with non-frontal pose, moderate out-of-plane head motion, and occlusion. The system recovers 3D motion parameters, stabilizes facial regions, extracts motion and appearance information, and recognizes discrete facial actions in spontaneous facial behavior. We tested the system in video data from a 2-person interview. Subjects were ethnically diverse, action units occurred during speech, and out-of-plane motion and occlusionfrom head motion and glasses were common. The video data were originally collected to answer substantive questions in psychology, and represent a substantial challenge to automated AU recognition. In analysis of 335 single and multiple blinks and non-blinks, the system achieved 98% accuracy.