

To disentangle and analyze neural pathways estimated from magnetic resonance imaging data, scientists need an interface to select 3D pathways. Broad adoption of such an interface requires the use of commodity input devices such as mice and pens, but these devices offer only two degrees of freedom. CINCH solves this problem by providing a marking interface for 3D pathway selection. CINCH interprets pen strokes as pathway selections in 3D using a marking language designed together with scientists. Its bimanual interface employs a pen and a trackball (see Figure 1), allowing alternating selections and scene rotations without changes of mode. CINCH was evaluated by observing four scientists using the tool over a period of three weeks as part of their normal work activity. Event logs and interviews revealed dramatic improvements in both the speed and quality of scientists' everyday work, and a set of principles that should inform the design of future 3D marking interfaces. More broadly, CINCH demonstrates the value of the iterative, participatory design process that catalyzed its evolution.

To disentangle and analyze neural pathways estimated from magnetic resonance imaging data, scientists need an interface to select 3D pathways. Broad adoption of such an interface requires the use of commodity input devices such as mice and pens, but these devices offer only two degrees of freedom. CINCH solves this problem by providing a marking interface for 3D pathway selection. CINCH interprets pen strokes as pathway selections in 3D using a marking language designed together with scientists. Its bimanual interface employs a pen and a trackball (see Figure 1), allowing alternating selections and scene rotations without changes of mode. CINCH was evaluated by observing four scientists using the tool over a period of three weeks as part of their normal work activity. Event logs and interviews revealed dramatic improvements in both the speed and quality of scientists' everyday work, and a set of principles that should inform the design of future 3D marking interfaces. More broadly, CINCH demonstrates the value of the iterative, participatory design process that catalyzed its evolution.

Computer sliders are a generic user input mechanism for specifying a numeric value from a range. For data visualization, the effectiveness of sliders may be increased by using the space inside the slider as
• an interactive color scale,
• a barplot for discrete data, and
• a density plot for continuous data.
The idea is to show the selected values in relation to the data and its distribution. Furthermore, the selection mechanism may be generalized using a painting metaphor to specify arbitrary, disconnected intervals while maintaining an intuitive user-interface.

Volumetric displays, which display imagery in true 3D space, are a promising platform for the display and manipulation of 3D data. To fully leverage their capabilities, appropriate user interfaces and interaction techniques must be designed. In this paper, we explore 3D selection techniques for volumetric displays. In a first experiment, we find a ray cursor to be superior to a 3D point cursor in a single target environment. To address the difficulties associated with dense target environments we design four new ray cursor techniques which provide disambiguation mechanisms for multiple intersected targets. Our techniques showed varied success in a second, dense target experiment. One of the new techniques, the depth ray, performed particularly well, significantly reducing movement time, error rate, and input device footprint in comparison to the 3D point cursor.

Designing interfaces for interactive handheld projectors is an exiting new area of research that is currently limited by two problems: hand jitter resulting in poor input control, and possible reduction of image resolution due to the needs of image stabilization and warping algorithms. We present the design and evaluation of a new interaction technique, called zoom-and-pick, that addresses both problems by allowing the user to fluidly zoom in on areas of interest and make accurate target selections. Subtle design features of zoom-and-pick enable pixel-accurate pointing, which is not possible in most freehand interaction techniques. Our evaluation results indicate that zoom-and-pick is significantly more accurate than the standard pointing technique described in our previous work.