Abstract
This paper presents an hierarchical approach with neural networks to locate the positions of the fingertips in grey-scale images of human hands. The first chapters introduce and sum up the research done in this area. Afterwards, our hierarchical approach and the preprocessing of the grey-scale images are described. A low-dimensional encoding of the images is done by the means of Gabor-Filters and a special kind of artificial neural net, the LLM-net, is employed to find the positions of the fingertips. The capabilities of the system are demonstrated on three tasks: locating the tip of the forefinger and of the thumb, finding the pointing-direction regardless of the operator’s pointing style, and detecting all 5 fingertips in hand movement sequences. The system is able to perform these tasks even when the fingertips are in an area with low contrast.
This work is supported by the Ministry of Science and Research of North Rhine-Westphalia under the grant number IV A3-107 031 96 in the framework of the project called “The Virtual Knowledge Factory”.
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© 1998 Springer-Verlag
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Nölker, C., Ritter, H. (1998). Detection of fingertips in human hand movement sequences. In: Wachsmuth, I., Fröhlich, M. (eds) Gesture and Sign Language in Human-Computer Interaction. GW 1997. Lecture Notes in Computer Science, vol 1371. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0053001
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DOI: https://doi.org/10.1007/BFb0053001
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