Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets
Heidemann G, Bekel H, Bax I, Saalbach A (2004)
In: Proceedings of the 17th International Conference on Pattern Recognition. J. Kittler MP, Nixon M (Eds); , 4. Cambridge, UK: IEEE: 487-490.
Konferenzbeitrag
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Autor*in
Heidemann, Gunther;
Bekel, Holger;
Bax, Ingo;
Saalbach, Axel
Herausgeber*in
J. Kittler, M. Petrou;
Nixon, M.
Einrichtung
Abstract / Bemerkung
Gesture recognition is a difficult task in computer vision due to the numerous degrees of freedom of a human hand. Fortunately, human gesture covers only a small part of the theoretical "configuration space" of a hand, so an appearance based representation of human gesture becomes tractable. A major problem, however, is the acquisition of appropriate labelled image data from which an appearance based representation can be built. In This work we apply self-organising maps for a visualisation of large amounts of segmented hands performing pointing gestures. Using a graphical interface, an easy labelling of the data set is facilitated. The labelled set is used to train a neural classification system, which is itself embedded in a larger architecture for the recognition of gestural reference to objects.
Erscheinungsjahr
2004
Titel des Konferenzbandes
Proceedings of the 17th International Conference on Pattern Recognition
Band
4
Seite(n)
487-490
Konferenz
17th International Conference on Pattern Recognition
Konferenzdatum
2004-08-23 – 2004-08-26
ISSN
1051-4651
Page URI
https://pub.uni-bielefeld.de/record/2714437
Zitieren
Heidemann G, Bekel H, Bax I, Saalbach A. Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets. In: J. Kittler MP, Nixon M, eds. Proceedings of the 17th International Conference on Pattern Recognition. Vol 4. Cambridge, UK: IEEE; 2004: 487-490.
Heidemann, G., Bekel, H., Bax, I., & Saalbach, A. (2004). Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets. In M. P. J. Kittler & M. Nixon (Eds.), Proceedings of the 17th International Conference on Pattern Recognition (Vol. 4, pp. 487-490). Cambridge, UK: IEEE. doi:10.1109/ICPR.2004.1333817
Heidemann, Gunther, Bekel, Holger, Bax, Ingo, and Saalbach, Axel. 2004. “Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets”. In Proceedings of the 17th International Conference on Pattern Recognition, ed. M. Petrou J. Kittler and M. Nixon, 4:487-490. Cambridge, UK: IEEE.
Heidemann, G., Bekel, H., Bax, I., and Saalbach, A. (2004). “Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets” in Proceedings of the 17th International Conference on Pattern Recognition, J. Kittler, M. P., and Nixon, M. eds., vol. 4, (Cambridge, UK: IEEE), 487-490.
Heidemann, G., et al., 2004. Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets. In M. P. J. Kittler & M. Nixon, eds. Proceedings of the 17th International Conference on Pattern Recognition. no.4 Cambridge, UK: IEEE, pp. 487-490.
G. Heidemann, et al., “Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets”, Proceedings of the 17th International Conference on Pattern Recognition, M.P. J. Kittler and M. Nixon, eds., vol. 4, Cambridge, UK: IEEE, 2004, pp.487-490.
Heidemann, G., Bekel, H., Bax, I., Saalbach, A.: Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets. In: J. Kittler, M.P. and Nixon, M. (eds.) Proceedings of the 17th International Conference on Pattern Recognition. 4, p. 487-490. IEEE, Cambridge, UK (2004).
Heidemann, Gunther, Bekel, Holger, Bax, Ingo, and Saalbach, Axel. “Hand Gesture Recognition: Self-Organising Maps as a Graphical User Interface for the Partitioning of Large Training Data Sets”. Proceedings of the 17th International Conference on Pattern Recognition. Ed. M. Petrou J. Kittler and M. Nixon. Cambridge, UK: IEEE, 2004.Vol. 4. 487-490.
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