3D Gesture recognition: an evaluation of user and system performance


Wright, M., Lin, C.-J., O'Neill, E., Cosker, D. and Johnson, P., 2011. 3D Gesture recognition: an evaluation of user and system performance. In: Lyons, K., Hightower, J. and Huang, E. M., eds. Pervasive Computing - 9th International Conference, Pervasive 2011, San Francisco, USA, June 12-15, 2011. Proceedings. Berlin: Springer, pp. 294-313. (Lecture Notes in Computer Science; 6696)

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    We report a series of empirical studies investigating gesture as an interaction technique in pervasive computing. In our first study, participants generated gestures for given tasks and from these we identified archetypal common gestures. Furthermore, we discovered that many of these user-generated gestures were performed in 3D. We implemented a computer vision based 3D gesture recognition system and applied it in a further study in which participants used the common gestures generated in the first study. We investigated the trade off between system performance and human performance and preferences, deriving design recommendations. We achieved 84% recognition accuracy by our prototype 3D gesture recognition system after tuning it through the use of simple heuristics. The most popular gestures from Study 1 were regarded by participants in Study 2 as best matching the task they represented, and they produced the fewest recall errors.


    Item Type Book Sections
    CreatorsWright, M., Lin, C.-J., O'Neill, E., Cosker, D. and Johnson, P.
    EditorsLyons, K., Hightower, J. and Huang, E. M.
    DepartmentsFaculty of Science > Computer Science
    Publisher StatementJohnson_Pervasive_2011_294.pdf: The original publication is available at
    ID Code24786
    Additional InformationConference paper from the 9th International Conference on Pervasive Computing, Pervasive 2011. 12-15 June 2011. San Francisco, CA, United States.


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