A model-based hand gesture recognition system
Machine Vision and Applications
Hand Posture Classification and Recognition using the Modified Census Transform
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Hand tracking in bimanual movements
Image and Vision Computing
Gesture-based interaction and communication: automated classification of hand gesture contours
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
SOMM: Self organizing Markov map for gesture recognition
Pattern Recognition Letters
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
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In this paper we present a system that performs automatic gesture recognition. The system consists of two main components: (i) A unified technique for segmentation and tracking of face and hands using a skin detection algorithm along with handling occlusion between skin objects to keep track of the status of the occluded parts. This is realized by combining 3 useful features, namely, color, motion and position. (ii) A static and dynamic gesture recognition system. Static gesture recognition is achieved using a robust hand shape classification, based on PCA subspaces, that is invariant to scale along with small translation and rotation transformations. Combining hand shape classification with position information and using DHMMs allows us to accomplish dynamic gesture recognition.