Abstract
This paper introduces a novel and efficient segmentation method designed for articulated hand motion. The method is based on a graph representation of temporal structures in human hand-object interaction. Along with the method for temporal segmentation we provide an extensive new database of hand motions. The experiments performed on this dataset show that our method is capable of a fully automatic hand motion segmentation which largely coincides with human user annotations.
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Acknowledgement
We would like to thank Fraunhofer IAO for providing us with the CyberGlove used to record the motion data. We also thank the authors of [6] for providing source code of their method for comparison.
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Stollenwerk, K., Vögele, A., Krüger, B., Hinkenjann, A., Klein, R. (2016). Automatic Temporal Segmentation of Articulated Hand Motion. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2016. ICCSA 2016. Lecture Notes in Computer Science(), vol 9787. Springer, Cham. https://doi.org/10.1007/978-3-319-42108-7_33
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DOI: https://doi.org/10.1007/978-3-319-42108-7_33
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