pen-based

We explore a variety of interaction and visualization techniques for fluid navigation, segmentation, linking, and annotation of digital videos. These techniques are developed within a concept prototype called LEAN that is designed for use with pressure-sensitive digitizer tablets. These techniques include a transient position+velocity widget that allows users not only to move around a point of interest on a video, but also to rewind or fast forward at a controlled variable speed. We also present a new variation of fish-eye views called twist-lens, and incorporate this into a position control slider designed for the effective navigation and viewing of large sequences of video frames. We also explore a new style of widgets that exploit the use of the pen's pressure-sensing capability, increasing the input vocabulary available to the user. Finally, we elaborate on how annotations referring to objects that are temporal in nature, such as video, may be thought of as links, and fluidly constructed, visualized and navigated.

High precision parameter manipulation tasks typically require adjustment of the scale of manipulation in addition to the parameter itself. This paper introduces the notion of Zoom Sliding, or Zliding, for fluid integrated manipulation of scale (zooming) via pressure input while parameter manipulation within that scale is achieved via x-y cursor movement (sliding). We also present the Zlider (Figure 1), a widget that instantiates the Zliding concept. We experimentally evaluate three different input techniques for use with the Zlider in conjunction with a stylus for x-y cursor positioning, in a high accuracy zoom and select task. Our results marginally favor the stylus with integrated isometric pressure sensing tip over bimanual techniques which separate zooming and sliding controls over the two hands. We discuss the implications of our results and present further designs that make use of Zliding.

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.

As technical as we have become, modern computing has not permeated many important areas of our lives, including mathematics education which still involves pencil and paper. In the present study, twenty high school geometry students varying in ability from low to high participated in a comparative assessment of math problem solving using existing pencil and paper work practice (PP), and three different interfaces: an Anoto-based digital stylus and paper interface (DP), pen tablet interface (PT), and graphical tablet interface (GT). Cognitive Load Theory correctly predicted that as interfaces departed more from familiar work practice (GT > PT > DP), students would experience greater cognitive load such that performance would deteriorate in speed, attentional focus, meta-cognitive control, correctness of problem solutions, and memory. In addition, low-performing students experienced elevated cognitive load, with the more challenging interfaces (GT, PT) disrupting their performance disproportionately more than higher performers. The present results indicate that Cognitive Load Theory provides a coherent and powerful basis for predicting the rank ordering of users' performance by type of interface. In the future, new interfaces for areas like education and mobile computing could benefit from designs that minimize users' load so performance is more adequately supported.

In this paper, we describe our work on developing a system to support the personalization of a captured public experience. Specifically, we are interested in providing students with the ability to personalize the capture of the lecture experiences as part of the Classroom 2000 project. We discuss the issues and challenges involved in designing a system that performs live integration of personal streams of information with multiple other streams of information made available to it through an environment designed to capture public information.

We present SketchREAD, a multi-domain sketch recognition engine capable of recognizing freely hand-drawn diagrammatic sketches. Current computer sketch recognition systems are difficult to construct, and either are fragile or accomplish robustness by severely limiting the designer's drawing freedom. Our system can be applied to a variety of domains by providing structural descriptions of the shapes in that domain; no training data or programming is necessary. Robustness to the ambiguity and uncertainty inherent in complex, freely-drawn sketches is achieved through the use of context. The system uses context to guide the search for possible interpretations and uses a novel form of dynamically constructed Bayesian networks to evaluate these interpretations. This process allows the system to recover from low-level recognition errors (e.g., a line misclassified as an arc) that would otherwise result in domain level recognition errors. We evaluated Sketch-READ on real sketches in two domains--family trees and circuit diagrams--and found that in both domains the use of context to reclassify low-level shapes significantly reduced recognition error over a baseline system that did not reinterpret low-level classifications. We also discuss the system's potential role in sketch based user interfaces.

Informal prototyping tools have shown great potential in facilitating the early stage design of user interfaces. How-ever, continuous interactions, an important constituent of highly interactive interfaces, have not been well supported by previous tools. These interactions give continuous visual feedback, such as geometric changes of a graphical object, in response to continuous user input, such as the movement of a mouse. We built Monet, a sketch-based tool for proto-typing continuous interactions by demonstration. In Monet, designers can prototype continuous widgets and their states of interest using examples. They can also demonstrate com-pound behaviors involving multiple widgets by direct ma-nipulation. Monet allows continuous interactions to be eas-ily integrated with event-based, discrete interactions. Con-tinuous widgets can be embedded into storyboards and their states can condition or trigger storyboard transitions. Monet achieves these features by employing continuous function approximation and statistical classification techniques, without using any domain specific knowledge or assuming any application semantics. Informal feedback showed that Monet is a promising approach to enabling more complete tool support for early stage UI design.

SketchWizard allows designers to create Wizard of Oz prototypes of pen-based user interfaces in the early stages of design. In the past, designers have been inhibited from participating in the design of pen-based interfaces because of the inadequacy of paper prototypes and the difficulty of developing functional prototypes. In SketchWizard, designers and end users share a drawing canvas between two computers, allowing the designer to simulate the behavior of recognition or other technologies. Special editing features are provided to help designers respond quickly to end-user input. This paper describes the SketchWizard system and presents two evaluations of our approach. The first is an early feasibility study in which Wizard of Oz was used to prototype a pen-based user interface. The second is a laboratory study in which designers used SketchWizard to simulate existing pen-based interfaces. Both showed that end users gave valuable feedback in spite of delays between end-user actions and wizard updates.