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PL EN. Widoczny [Schowaj] Abstrakt. Adres strony. Pomiary Automatyka Kontrola. Barczewska, K. Gesture recognition based on 9DOF inertial sensor. Gesture recognition may be applied to control of computer applica-tions and electronic devices as an alternative to standard human-machine interfaces. Nine volunteers were asked to perform 10 different gestures shown in Fig. The gesture data base consisting of files with triaxial acceleration and orientation signals was created.

In the first step the data were divided into training and testing sets. Using this method the authors chose representative signals to indi-vidual and generalized exemplars data base from the training set. The DTW algorithm was also used in the classification process. Different recognition approaches were tested basing on acceleration-only, orientation-only and acceleration-orientation signals.

The results listed in Tab. The modification proposed by the authors Section 3 improved the recognition rate by 10 percentage points. The next step of im-proving the designed recognition system is application of an inertial system with a bluetooth module and real-time gesture classification. Opis fizyczny. Drozd, A. Chapter 4: Dynamic Time Warping. Springer Verlag Typ dokumentu.

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PL EN. Widoczny [Schowaj] Abstrakt. Adres strony. Pomiary Automatyka Kontrola. Barczewska, K. Gesture recognition based on 9DOF inertial sensor. Gesture recognition may be applied to control of computer applica-tions and electronic devices as an alternative to standard human-machine interfaces.

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