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

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樓主: 掩飾
11#
發(fā)表于 2025-3-23 10:49:22 | 只看該作者
Exploiting distant pointing gestures for object selection in a virtual environment,a virtual environment are discussed with respect to a required functionality, the implementation of a specific gesture detection module for distant pointing recognition is described, and the whole system design is tested for its task adequacy.
12#
發(fā)表于 2025-3-23 17:46:57 | 只看該作者
Detection of fingertips in human hand movement sequences,inger and of the thumb, finding the pointing-direction regardless of the operator’s pointing style, and detecting all 5 fingertips in hand movement sequences. The system is able to perform these tasks even when the fingertips are in an area with low contrast.
13#
發(fā)表于 2025-3-23 20:50:48 | 只看該作者
14#
發(fā)表于 2025-3-24 02:11:24 | 只看該作者
Automatische Messwerterfassung,computer science. I specify fundamental unsolved problems in the areas of naturalness, anthropology and systems building. I also suggest some things that we could do to make our research community stronger and more able to tackle these problems.
15#
發(fā)表于 2025-3-24 02:33:32 | 只看該作者
16#
發(fā)表于 2025-3-24 09:46:59 | 只看該作者
https://doi.org/10.1007/978-3-030-71685-1ing. It revealed that a highly informative, one-handed gesture with seemingly-interactive speech attracted attention when it had a slower stroke and/or a long post-stroke hold at the Center-Center space and upper position.
17#
發(fā)表于 2025-3-24 13:50:52 | 只看該作者
Phase-Change Phenomena and Two-Phase Flow,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.
18#
發(fā)表于 2025-3-24 15:50:04 | 只看該作者
Kriti Yadav,Anirbid Sircar,Manan Shahcues. Gestures are captured with a TUB-SensorGlove. The paper focuses on the description of the gesture recognition method (including data preprocessing) and describes experiments for the evaluation of the performance of the recognition method. The paper combines and further develops ideas from some of our previous work.
19#
發(fā)表于 2025-3-24 22:35:28 | 只看該作者
20#
發(fā)表于 2025-3-25 01:08:17 | 只看該作者
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