User target intention recognition from cursor position using kalman filter

Authors:
Gökçen Aslan Aydemir;Patrick M. Langdon;Simon Godsill
Affiliations:
Engineering Design Centre, University of Cambridge, Cambridge, United Kingdom;Engineering Design Centre, University of Cambridge, Cambridge, United Kingdom;Engineering Department, Cambridge, United Kingdom
Venue:
UAHCI'13 Proceedings of the 7th international conference on Universal Access in Human-Computer Interaction: design methods, tools, and interaction techniques for eInclusion - Volume Part I
Year:
2013

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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.