Abstract
This paper describes our approach to hand detection on a multitouch surface i.e. detecting how many hands are currently on the surface and associating each touch point to its corresponding hand. Our goal was to find a general software-based solution to this problem applicable to all multitouch surfaces regardless of their construction. We therefore approached hand detection with a limited amount of information: the position of each touch point. We propose HDCMD (Hand Detection with Clustering on Multitouch Displays), a simple clustering algorithm based on heuristics that exploit the knowledge of the anatomy of the human hand. The proposed hand detection algorithm’s accuracy evaluated on synthetic data (97%) significantly outperformed XMeans (21%) and DBScan (67%).
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Blažica, B., Vladušič, D., Mladenić, D. (2013). HDCMD: A Clustering Algorithm to Support Hand Detection on Multitouch Displays. In: Holzinger, A., Ziefle, M., Hitz, M., Debevc, M. (eds) Human Factors in Computing and Informatics. SouthCHI 2013. Lecture Notes in Computer Science, vol 7946. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39062-3_58
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DOI: https://doi.org/10.1007/978-3-642-39062-3_58
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