In order to investigate large information spaces effectively, it is often necessary to employ navigation mechanisms that allow users to view information at different scales. Some tasks require frequent movements and scale changes to search for details and compare them. We present a model that makes predictions about user performance on such comparison tasks with different interface options. A critical factor embodied in this model is the limited capacity of visual working memory, allowing for the cost of visits via fixating eye movements to be compared to the cost of visits that require user interaction with the mouse. This model is tested with an experiment that compares a zooming user interface with a multi-window interface for a multiscale pattern matching task. The results closely matched predictions in task performance times; however error rates were much higher with zooming than with multiple windows. We hypothesized that subjects made more visits in the multi-window condition, and ran a second experiment using an eye tracker to record the pattern of fixations. This revealed that subjects made far more visits back and forth between pattern locations when able to use eye movements than they made with the zooming interface. The results suggest that only a single graphical object was held in visual working memory for comparisons mediated by eye movements, reducing errors by reducing the load on visual working memory. Finally we propose a design heuristic: extra windows are needed when visual comparisons must be made involving patterns of a greater complexity than can be held in visual working memory.

This paper reports the development of a real-time human-computer interface (HCI) system that enables a human operator to more effectively utilize the large volume of quantitative data (navigation, scientific, and vehicle status) generated in real-time by the sensor suites of underwater ro botic vehicles. The system provides interactive 3-D graphical interfaces that display, under user control, the quantitative spatial and temporal sensor data presently available to pilots and users only as two-dimensional plots and numerical dis plays. The system can presently display real-time bathymetric renderings of the sea-floor based upon vehicle navigation and sonar sensor data; vehicle trajectory data; a variety of scalar valued sensor data; and geo-referenced targets and waypoints. We report the accuracy of the real-time navigation and bathymetric sonar data processing by comparing the real-time sonar bathymetry of our test tank floor to a high-resolution laser scan of the same tank floor. The real-time sonar bathymetry is shown to compare favorably to the laser scan data

It is common for 3D visualization systems to provide multiple points of view to a user, but there have been many solutions to the problem of linking these views so that users can understand the spatial relationships between them. Toward developing guidelines for view-linking devices, we have carried out two experiments that compare the utility of three different classes of linking devices: a directional proxy, tethers from one view to another, and a track-up map coupling. The task we apply them to is what we call the multi-perspective identification task: subjects are asked to identify an item seen in a local, forward-looking view in the context of a global, overhead view. Our results indicate that the directional proxy is the most beneficial device, and that the track-up map coupling is also beneficial. The results suggest that tethers provide little benefit. The results also suggest that when multiple local views are present, it may be beneficial to emphasize one window as being of primary interest.

Zooming and multiple windows are two techniques designed to address the focus-in-context problem. We present a theoretical model of performance that models the relative benefits of these techniques when used by humans for completing a task involving comparisons between widely separated groups of objects. The crux of the model is its cognitive component: the strength of multiple windows comes in the way they aid visual working memory. The task to which we apply our model is multiscale comparison, in which a user begins with a known visual pattern and searches for an identical or similar pattern among distracters. The model predicts that zooming should be better for navigating between a few distant locations when demands on visual memory are low, but that multiple windows are more efficient when demands on visual memory are higher, or there are several distant locations that must be investigated. To evaluate our model we conducted an experiment in which users performed a multiscale comparison task using both zooming and multiple-window interfaces. The results confirm the general predictions of our model.