Gesture recognition with a Time-Of-Flight camera

Authors:
Eva Kollorz;Jochen Penne;Joachim Hornegger;Alexander Barke
Affiliations:
Institute of Pattern Recognition, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen 91058, Germany.;Institute of Pattern Recognition, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen 91058, Germany.;Institute of Pattern Recognition, Friedrich-Alexander-University Erlangen-Nuremberg, Erlangen 91058, Germany.;Department of Applied Research, Audi Electronics Venture GmbH, Gaimersheim 85080, Germany
Venue:
International Journal of Intelligent Systems Technologies and Applications
Year:
2008

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Abstract

This paper presents a new approach for gesture classification using x- and y- projections of the image and optional depth features. The system uses a 3D Time-Of-Flight (TOF) sensor which has the big advantage of simplifying hand segmentation. For the presented system, a Photonic-Mixer-Device (PMD) camera with a resolution of 160 × 120 pixels and a frame rate of 15 frames per second is used. The goal of our system is to recognise 12 different static hand gestures. The x- and y- projections and the depth features of the captured image are good enough to use a simple nearest neighbour classifier, resulting in a fast classification. To evaluate the system, a set of 408 images is recorded, 12 gestures from 34 persons. With a 'Leave-One-Out' evaluation, the recognition rate of the system is 94.61% and the classification time is about 30 msec on a standard PC.