Human-computer interaction: input devices
ACM Computing Surveys (CSUR)
Eye finding via face detection for a foveated, active vision system
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
1996 IEEE TENCON
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
The Hand Mouse: GMM Hand-Color Classication and Mean Shift Tracking
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Intelligent wheelchair (IW) interface using face and mouth recognition
Proceedings of the 14th international conference on Intelligent user interfaces
"shooting a bird": game system using facial feature for the handicapped people
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Computer interface to use eye and mouse movement
MMM'07 Proceedings of the 13th International conference on Multimedia Modeling - Volume Part II
Welfare interface using multiple facial features tracking
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
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In this paper, an eye tracking method is presented using a neural network (NN) and mean-shift algorithm that can accurately detect and track user's eyes under the cluttered background. In the proposed method, to deal with the rigid head motion, the facial region is first obtained using skin-color model and connected-component analysis. Thereafter the eye regions are localized using neural network (NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, which enables our method to accurately detect users' eyes even if they put on glasses. Once the eye region is localized, they are continuously and correctly tracking by mean-shift algorithm. To assess the validity of the proposed method, it is applied to the interface system using eye movement and is tested with a group of 25 users through playing a ‘aligns games.' The results show that the system process more than 30 frames/sec on PC for the 320×240 size input image and supply a user-friendly and convenient access to a computer in real-time operation.