Visual Interpretation of Hand Gestures for Human-Computer Interaction: A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
WACV '96 Proceedings of the 3rd IEEE Workshop on Applications of Computer Vision (WACV '96)
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Facial expression recognition from video sequences: temporal and static modeling
Computer Vision and Image Understanding - Special issue on Face recognition
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
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This paper proposes a novel hidden Markov model (HMM)-based gesture recognition method and applies it to the HCI to control a computer game. The novelty of the proposed method is two-folds. First one, the proposed method uses a continuous sequence of human motion as an input of HMM, instead of isolated data sequences or pre-segmented sequences of the data. The other one, it performs both segmentation and recognition of the human gesture automatically. To assess the validity of the proposed method, we applied the proposed system to a real game, Quake II, and then the results demonstrate that the proposed HMM can provide very useful information to enhance the discrimination between the different classes and reduce the computational cost.