Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00) Crane Gesture Recognition Using Pseudo 3-D Hidden Markov Models Grenoble, France9 March 26-March 30 ISBN: 0-7695-0580-5
A recognition technique based on novel pseudo 3-D Hidden Markov Models, which can integrate spatial as well as temporal derived features are presented in this paper. The approach allows the recognition of dynamic gestures such as waving hands as well as static gestures such as standing in a special pose. Pseudo 3-D Hidden Markov Models (P3DHMMs) are an extension of the pseudo 2-D case, which has been successfully used for the classification of images and the recognition of faces. In the P3DHMM case the so-called superstates contain P2DHMMs and thus these models can generate whole image sequences. Our approach has been evaluated on a crane signal database, which consists of 12 different predefined gestures for maneuvering cranes.
Citation:
Stefan Müller, Stefan Eickeler, Gerhard Rigoll, "Crane Gesture Recognition Using Pseudo 3-D Hidden Markov Models," fg, pp.398, Fourth IEEE International Conference on Automatic Face and Gesture Recognition (FG'00), 2000 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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