Abstract
This paper discusses user target intention recognition algorithms for pointing – clicking tasks to reduce users’ pointing time and difficulty. Predicting targets by comparing the bearing angles to targets proposed as one of the first algorithms [1] is compared with a Kalman Filter prediction algorithm. Accuracy and sensitivity of prediction are used as performance criteria. The outcomes of a standard point and click experiment are used for performance comparison, collected from both able-bodied and impaired users.
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Aydemir, G.A., Langdon, P.M., Godsill, S. (2013). User Target Intention Recognition from Cursor Position Using Kalman Filter. In: Stephanidis, C., Antona, M. (eds) Universal Access in Human-Computer Interaction. Design Methods, Tools, and Interaction Techniques for eInclusion. UAHCI 2013. Lecture Notes in Computer Science, vol 8009. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39188-0_45
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DOI: https://doi.org/10.1007/978-3-642-39188-0_45
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