active

We introduce an inexpensive position input device called the FieldMouse, with which a computer can tell the position of the device on paper or any flat surface without using special input tablets or position detection devices. A FieldMouse is a combination of an ID recognizer like a barcode reader and a mouse which detects relative movement of the device. Using a FieldMouse, a user first detects an ID on paper by using the barcode reader, and then drags it from the ID using the mouse. If the location of the ID is known, the location of the dragged FieldMouse can also be calculated by adding the amount of movement from the ID to the position of the FieldMouse. Using a FieldMouse in this way, any flat surface can work as a pointing device that supports absolute position input, just by putting an ID tag somewhere on the surface. A FieldMouse can also be used for enabling a graphical user interface (GUI) on paper or on any flat surface by analyzing the direction and the amount of mouse movement after detecting an ID. In this paper, we introduce how a FieldMouse can be used in various situations to enable computing in real-world environments.

Decision-theoretic optimization is becoming a popular tool in the user interface community, but creating accurate cost (or utility) functions has become a bottleneck --- in most cases the numerous parameters of these functions are chosen manually, which is a tedious and error-prone process. This paper describes ARNAULD, a general interactive tool for eliciting user preferences concerning concrete outcomes and using this feedback to automatically learn a factored cost function. We empirically evaluate our machine learning algorithm and two automatic query generation approaches and report on an informal user study.