A Calibration-Free Head Gesture Recognition System with Online Capability

NC Wöhler, U Grossekathöfer, A Dierker, Marc Hanheide, S Kopp, T Hermann

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)


In this paper, we present a calibration-free head gesture recognition system using a motion-sensor-based approach. For data acquisition we conducted a comprehensive study with 10 subjects. We analyzed the resulting head movement data with regard to separability and transferability to new subjects. Ordered means models (OMMs) were used for classification, since they provide an easy-to-use, fast, and stable approach to machine learning of time series. In result, we achieved classification rates of 85-95% for nodding, head shaking and tilting head gestures and good transferability. Finally, we show first promising attempts towards online recognition.
Original languageEnglish
Title of host publication2010 20th International Conference on Pattern Recognition (ICPR)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages4
ISBN (Print)978-1-4244-7542-1
Publication statusPublished - 26 Aug 2010
EventInternational Conference on Pattern Recognition (ICPR 2010), 20th - Istanbul, Turkey
Duration: 23 Aug 201026 Aug 2010


ConferenceInternational Conference on Pattern Recognition (ICPR 2010), 20th


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