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Göteborgs universitets publikationer

Real-Time Gesture Recognition Based On Motion Quality Analysis

Författare och institution:
C. Jost (-); P. De Loor (-); A. Nedelec (-); E. Bevacqua (-); Igor Stankovic (Institutionen för tillämpad informationsteknologi (GU))
Publicerad i:
Proceedings of the 2015 7th International Conference on Intelligent Technologies for Interactive Entertainment, s. 47-56
Konferensbidrag, refereegranskat
Sammanfattning (abstract):
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.
Ämne (baseras på Högskoleverkets indelning av forskningsämnen):
Data- och informationsvetenskap
Gesture recognition, Quality motion features, Morphology independence, Computer Science
Postens nummer:
Posten skapad:
2016-08-19 15:23

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