Visual recognition of pointing gestures for human-robot interaction

13 years 4 months ago

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In this paper, we present an approach for recognizing pointing gestures in the context of human–robot interaction. In order to obtain input features for gesture recognition, we perform visual tracking of head, hands and head orientation. Given the images provided by a calibrated stereo camera, color and disparity information are integrated into a multi-hypothesis tracking framework in order to ﬁnd the 3D-positions of the respective body parts. Based on the hands’ motion, an HMM-based classiﬁer is trained to detect pointing gestures. We show experimentally that the gesture recognition performance can be improved signiﬁcantly by using information about head orientation as an additional feature. Our system aims at applications in the ﬁeld of human–robot interaction, where it is important to do run-on recognition in real-time, to allow for robot egomotion and not to rely on manual initialization. Ó 2006 Elsevier B.V. All rights reserved.

Kai Nickel, Rainer Stiefelhagen

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