DocumentCode :
2093523
Title :
Real-time visual recognition of facial gestures for human-computer interaction
Author :
Zelinsky, Alexander ; Heinzmann, Jochen
Author_Institution :
Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT, Australia
fYear :
1996
fDate :
14-16 Oct 1996
Firstpage :
351
Lastpage :
356
Abstract :
People naturally express themselves through facial gestures and expressions. Our goal is to build a facial gesture human-computer interface for use in robot applications. We have implemented an interface that tracks a person´s facial features in real time (30 Hz). Our system does not require special illumination nor facial makeup. By using multiple Kalman filters we accurately predict and robustly track facial features. This is despite disturbances and rapid movements of the head (including both translational and rotational motion). Since we reliably track the face in real-time we are also able to recognise motion gestures of the face. Our system can recognise a large set of gestures (13) ranging from “yes”, “no” and “may be” to detecting winks, blinks and sleeping
Keywords :
Kalman filters; face recognition; feature extraction; graphical user interfaces; robot vision; blinks; facial expressions; facial gestures; human-computer interaction; multiple Kalman filters; real-time visual recognition; robot applications; rotational motion; sleeping; translational motion; winks; Cameras; Face detection; Face recognition; Facial features; Hardware; Humans; Magnetic heads; Real time systems; Robustness; Tracking;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Automatic Face and Gesture Recognition, 1996., Proceedings of the Second International Conference on
Conference_Location :
Killington, VT
Print_ISBN :
0-8186-7713-9
Type :
conf
DOI :
10.1109/AFGR.1996.557290
Filename :
557290
Link To Document :
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