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Real-Time Gesture R...
Real-Time Gesture Recognition Based On Motion Quality Analysis
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Jost, C. (författare)
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De Loor, P. (författare)
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Nedelec, A. (författare)
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Bevacqua, E. (författare)
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- Stankovic, Igor (författare)
- Gothenburg University,Göteborgs universitet,Institutionen för tillämpad informationsteknologi (GU),Department of Applied Information Technology (GU)
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(creator_code:org_t)
- IEEE, 2015
- 2015
- Engelska.
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Ingår i: Proceedings of the 2015 7th International Conference on Intelligent Technologies for Interactive Entertainment. - : IEEE. ; , s. 47-56
- Relaterad länk:
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http://eudl.eu/pdf/1...
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https://gup.ub.gu.se...
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https://doi.org/10.4...
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Abstract
Ämnesord
Stäng
- This paper presents a robust and anticipative real-time gesture recognition and its motion quality analysis module. By utilizing a motion capture device, the system recognizes gestures performed by a human, where the recognition process is based on skeleton analysis and motion features computation. Gestures are collected from a single person. Skeleton joints are used to compute features which are stored in a reference database, and Principal Component Analysis (PCA) is computed to select the most important features, useful in discriminating gestures. During real-time recognition, using distance measures, real-time selected features are compared to the reference database to find the most similar gesture. Our evaluation results show that: i) recognition delay is similar to human recognition delay, ii) our module can recognize several gestures performed by different people and is morphology-independent, and iii) recognition rate is high: all gestures are recognized during gesture stroke. Results also show performance limits.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
Nyckelord
- Gesture recognition
- Quality motion features
- Morphology independence
- Computer Science
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)