Interactively exploring multidimensional datasets requires frequent switching among a range of distinct but inter-related tasks (e.g., producing different visuals based on different column sets, calculating new variables, and observing the interactions between sets of data).
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November 2007
We present a practical technique for using a writer-independent recognition engine to improve the accuracy and speed while reducing the training requirements of a writer-dependent symbol recognizer. Our writer-dependent recognizer uses a set of binary classifiers based on the AdaBoost learning algorithm, one for each possible pairwise symbol comparison. Each classifier consists of a set of weak learners, one of which is based on a writer-independent handwriting recognizer.
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September 2007
We present Drawing on Air, a haptic-aided input technique for drawing controlled 3D curves through space. Drawing on Air addresses a control problem with current 3D modeling approaches based on sweeping movement of the hands through the air. While artists praise the immediacy and intuitiveness of these systems, a lack of control makes it nearly impossible to create 3D form beyond quick design sketches or gesture drawings.
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