Titlebook: Gesture and Sign Language in Human-Computer Interaction; International Gestur Ipke Wachsmuth,Martin Fröhlich Conference proceedings 1998 Sp

宽度

死亡率

panorama

High performance real-time gesture recognition using Hidden Markov Models,stem uses Hidden Markov Models (HMMs) as statistical classifier. These HMMs are trained on a database of 24 isolated gestures, performed by 14 different people. With the use of global motion features, a recognition rate of 92.9% is achieved for a person and background independent recognition.

Occupation

贪婪性

Neural architecture for gesture-based human-machine-interaction,al user in the operation field, followed by the aquisition and interpretaion of its gestural instructions. The whole approach is motivated in the context of a reliable operation scenario, but can be extended easily for other applications, such as videoconferencing.

温和女孩

doxazosin

乏味

Gesture-Based and haptic interaction for human skill acquisition, quantitative features extracted from the hand gesture analysis. Finally, it is planned to map the formalized skill into a robotics system, that will be able to grasp and manipulate non rigid objects, also facing unexpected situations.

裹住

Corpus of 3D natural movements and sign language primitives of movement,stem that allows the 3D description of movement trajectories in space. The main technical characteristics of the capture and pretreatment system are presented, and perspectives are highlighted for recognition and generation purposes.

Definitive